d2.1 forestry pilot definition - databio · 2017. 7. 5. · d2.1 – forestry pilot definition...

This document is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 732064. It is the property of the DataBio consortium and shall not be distributed or reproduced without the formal approval of the DataBio Management Committee.

Project Acronym: DataBio

Grant Agreement number: 732064 (H2020-ICT-2016-1 – Innovation Action)

Project Full Title: Data-Driven Bioeconomy

Project Coordinator: INTRASOFT International

DELIVERABLE

D2.1 – Forestry Pilot Definition

Dissemination level PU -Public

Type of Document Report

Contractual date of delivery M06 – 30/6/2017

Deliverable Leader Renne Tergujeff, VTT

Status - version, date Final – v1.0, 30/6/2017

WP / Task responsible WP2 / T2.1

Keywords: Forestry, pilot, big data, modelling, user analysis,

user requirements, stakeholders

D2.1 – Forestry Pilot Definition H2020 Contract No. 732064 Final – v1.0, 30/6/2017

Dissemination level: PU -Public

Executive Summary The objective of WP2 Forestry Pilot is to demonstrate through real life applications how Big

Data can boost the forestry sector. The three main pilots, carried out in four countries, are

built around practical cases from forestry.

Task 2.1 Co-innovative preparations specifies the needs of users and other stakeholders. Its

main objective is to come up with requirements by analysing each pilot case. A user and

stakeholder study is produced to specify the most beneficial areas of interest from different

points of view. Alternative solution technologies are reviewed together with pilot

stakeholders and users. Based on this, a set of scenarios are constructed for the forestry

sector. Functional requirements are defined from the scenarios and used as input for the case

specification, development and piloting. Subtasks concerning scenarios and use cases are

organized iteratively around working cycles. The results are the pilot cases definitions

including requirements specifications, implementation and evaluation plans.

The organizations that were planned to participate in this task, and their respective planned

work effort in person-months, are VTT (6), SPACEBEL (2), METSAK (4), IBM (2), MHGS (6),

Fraunhofer (4), Tragsa (6), FMI (2) CSEM (2), OGCE (6) and e-geos (6).

The deliverable D2.1 Forestry Pilot Definition specifies the pilot case definitions, requirement

specifications, as well as implementation and evaluation plans.



Deliverable Leader: Renne Tergujeff (VTT)

Contributors:

Anu Kosunen (METSAK), Petr Lukeš (FMI), Philippe Ledent

(SPACEBEL), Jesús Estrada Villegas (TRAGSA), Asunción Roldán

Zamarrón (TRAGSA), Laura Maria Luquero Ramos (TRAGSA),

Seppo Huurinainen (MHGS), Veli-Matti Plosila (MHGS)

Reviewers: Seppo Huurinainen (MHGS), Jorge Casado Álvarez (TRAGSA),

William Ouellette (SPACEBEL)

Approved by: Athanasios Poulakidas (INTRASOFT)

Document History

Version Date Contributor(s) Description

0.1 31/03/2017 Initial TOC draft

0.2 03/05/2017 Updated draft

0.3 31/05/2017 Updated draft

0.4 09/06/2017 Updated draft based on the cross-WP

deliverable templates

0.5 16/06/2017 First complete draft for review

0.6 21/06/2017 Second complete draft for review

0.7 26/06/2017 Reviewed draft

0.8 26/06/2017 Reviewed and edited draft

0.9 29/06/2017 Updated to enhance clarity and to

harmonize between D1.1/D2.1/D3.1

1.0 30/06/2017 Compliance to submission format and

minor changes



Table of Contents EXECUTIVE SUMMARY ..................................................................................................................................... 2

TABLE OF CONTENTS ........................................................................................................................................ 4

TABLE OF FIGURES ........................................................................................................................................... 6

LIST OF TABLES ................................................................................................................................................ 7

DEFINITIONS, ACRONYMS AND ABBREVIATIONS ............................................................................................. 9

INTRODUCTION .................................................................................................................................... 10

1.1 PROJECT SUMMARY ..................................................................................................................................... 10 1.2 DOCUMENT SCOPE ...................................................................................................................................... 13 1.3 DOCUMENT STRUCTURE ............................................................................................................................... 13

SUMMARY ............................................................................................................................................ 14

2.1 OVERVIEW ................................................................................................................................................. 14 2.2 PILOT MODELLING FRAMEWORK ..................................................................................................................... 15 2.3 PILOT INTRODUCTIONS ................................................................................................................................. 18

2.3.1 Wuudis .......................................................................................................................................... 21 2.4 PILOT CASE DEFINITIONS ............................................................................................................................... 21 2.5 BIG DATA ASSETS ......................................................................................................................................... 22 2.6 EVALUATION PLANS ..................................................................................................................................... 23 2.7 IMPLEMENTATION PLANS .............................................................................................................................. 23

PILOT 2.2.1: EASY DATA SHARING AND NETWORKING ......................................................................... 27

3.1 PILOT OVERVIEW ......................................................................................................................................... 27 3.1.1 Pilot introduction .......................................................................................................................... 27 3.1.2 Pilot overview................................................................................................................................ 27

3.2 PILOT CASE DEFINITION ................................................................................................................................. 32 3.2.1 Stakeholders and user stories ....................................................................................................... 32 3.2.2 Motivation and strategy ............................................................................................................... 34 3.2.3 Scope and limitations .................................................................................................................... 35

3.3 PILOT MODELLING WITH ARCHIMATE .............................................................................................................. 35 3.3.1 DataBio forestry pilot 2.2.1 motivation view ................................................................................ 35 3.3.2 DataBio forestry pilot 2.2.1 strategy view .................................................................................... 36

3.4 BIG DATA INFRASTRUCTURE: COMPONENTS AND BDVA CLASSIFICATION ............................................................... 39 3.5 PILOT EVALUATION PLAN ............................................................................................................................... 40

3.5.1 High level goals and KPIs .............................................................................................................. 40 3.6 INITIAL ROADMAP ........................................................................................................................................ 40

PILOT 2.2.2: MONITORING AND CONTROL TOOLS FOR FOREST OWNERS ............................................. 42



4.3 PILOT MODELLING WITH ARCHIMATE .............................................................................................................. 49 4.3.1 DataBio forestry pilot 2.2.2 motivation view ................................................................................ 49



4.3.2 DataBio forestry pilot 2.2.2 strategy view .................................................................................... 51 4.4 BIG DATA INFRASTRUCTURE: COMPONENTS AND BDVA CLASSIFICATION ............................................................... 53 4.5 PILOT EVALUATION PLAN ............................................................................................................................... 54


PILOT 2.3.1: FOREST DAMAGE REMOTE SENSING ................................................................................. 57



5.3 PILOT MODELLING WITH ARCHIMATE .............................................................................................................. 64 5.3.1 DataBio forestry pilot 2.3.1 motivation view ................................................................................ 64 5.3.2 DataBio forestry pilot 2.3.1 strategy view .................................................................................... 66



PILOT 2.3.2-FH: MONITORING OF FOREST HEALTH ............................................................................... 71



6.3 PILOT MODELLING WITH ARCHIMATE .............................................................................................................. 77 6.3.1 DataBio forestry pilot 2.3.2-FH motivation view .......................................................................... 77 6.3.2 DataBio forestry pilot 2.3.2-FH strategy view ............................................................................... 79



PILOT 2.3.2-IAS: INVASIVE ALIEN SPECIES CONTROL AND MONITORING .............................................. 84



7.3 PILOT MODELLING WITH ARCHIMATE .............................................................................................................. 90 7.3.1 DataBio forestry pilot 2.3.2-IAS motivation view .......................................................................... 90 7.3.2 DataBio forestry pilot 2.3.2-IAS strategy view .............................................................................. 90


7.5.1 High level goals and KPIs .............................................................................................................. 93



7.6 INITIAL ROADMAP ........................................................................................................................................ 93

PILOT 2.4.1: WEB-MAPPING SERVICE FOR GOVERNMENT DECISION MAKING ...................................... 95



8.3 PILOT MODELLING WITH ARCHIMATE .............................................................................................................. 99 8.3.1 DataBio forestry pilot 2.4.1 motivation view ................................................................................ 99 8.3.2 DataBio forestry pilot 2.4.1 strategy view .................................................................................. 100

8.4 BIG DATA INFRASTRUCTURE: COMPONENTS AND BDVA CLASSIFICATION ............................................................. 101 8.5 PILOT EVALUATION PLAN ............................................................................................................................. 102

8.5.1 High level goals and KPIs ............................................................................................................ 102 8.6 INITIAL ROADMAP ...................................................................................................................................... 102

PILOT 2.4.2: SHARED MULTIUSER FOREST DATA ENVIRONMENT ........................................................ 104

9.1 PILOT OVERVIEW ....................................................................................................................................... 104 9.1.1 Pilot introduction ........................................................................................................................ 104 9.1.2 Pilot overview.............................................................................................................................. 104

9.2 PILOT CASE DEFINITION ............................................................................................................................... 107 9.2.1 Stakeholders and user stories ..................................................................................................... 107 9.2.2 Motivation and strategy ............................................................................................................. 107 9.2.3 Scope and limitations .................................................................................................................. 108

9.3 PILOT MODELLING WITH ARCHIMATE ............................................................................................................ 108 9.3.1 DataBio forestry pilot 2.4.2 motivation view .............................................................................. 108 9.3.2 DataBio forestry pilot 2.4.2 strategy view .................................................................................. 109

9.4 BIG DATA INFRASTRUCTURE: COMPONENTS AND BDVA CLASSIFICATION ............................................................. 111 9.5 PILOT EVALUATION PLAN ............................................................................................................................. 112

9.5.1 High level goals and KPIs ............................................................................................................ 112 9.6 INITIAL ROADMAP ...................................................................................................................................... 113

REFERENCES ....................................................................................................................................... 115

Table of Figures FIGURE 1: ARCHIMATE 3.0 MODELLING FRAMEWORK. ..................................................................................................... 15 FIGURE 2: RELATIONSHIPS OF THE MOTIVATION ELEMENTS ................................................................................................ 18 FIGURE 3: RELATIONSHIPS OF THE STRATEGY ELEMENTS .................................................................................................... 18 FIGURE 4: TIMELINE OF PILOT 2.2.1, EASY DATA SHARING AND NETWORKING ....................................................................... 23 FIGURE 5: TIMELINE OF PILOT 2.2.2, MONITORING AND CONTROL TOOLS FOR FOREST OWNERS ............................................... 24 FIGURE 6: TIMELINE OF PILOT 2.3.1, FOREST DAMAGE REMOTE SENSING ............................................................................. 24 FIGURE 7: TIMELINE OF PILOT 2.3.2-FH, MONITORING OF FOREST HEALTH .......................................................................... 25 FIGURE 8: TIMELINE OF PILOT 2.3.2-IAS, INVASIVE ALIEN SPECIES CONTROL AND MONITORING ................................................ 25 FIGURE 9: TIMELINE OF PILOT 2.4.1, WEB-MAPPING SERVICE FOR THE GOVERNMENT DECISION MAKING ................................... 26 FIGURE 10: TIMELINE OF PILOT 2.4.2, SHARED MULTIUSER FOREST DATA ENVIRONMENT ........................................................ 26 FIGURE 11: PILOT ESTATE FORESTRY DATA TRANSFERRED INTO WUUDIS FROM THE FORESTRY AUTHORITY SYSTEM (METSAAN.FI) .... 28 FIGURE 12: DATA SHARING IN WUUDIS ......................................................................................................................... 29 FIGURE 13: FORESTRY A1 MOTIVATION VIEW ................................................................................................................. 36



FIGURE 14: FORESTRY A1 FOREST USER MOTIVATION VIEW .............................................................................................. 36 FIGURE 15: FORESTRY A1 STRATEGY VIEW ..................................................................................................................... 37 FIGURE 16: FORESTRY A1 FOREST USER STRATEGY VIEW .................................................................................................. 37 FIGURE 17: BIG DATA COMPONENTS AND ASSETS IN PILOT 2.2.1: EASY DATA SHARING AND NETWORKING ................................. 39 FIGURE 18: TIMELINE OF PILOT 2.2.1, EASY DATA SHARING AND NETWORKING ..................................................................... 41 FIGURE 19: FORESTRY A2 MOTIVATION VIEW ................................................................................................................. 50 FIGURE 20: FORESTRY A2 FOREST OWNER MOTIVATION VIEW ........................................................................................... 50 FIGURE 21: FORESTRY A2 STRATEGY VIEW ..................................................................................................................... 51 FIGURE 22: FORESTRY A2 FOREST OWNER STRATEGY VIEW ............................................................................................... 52 FIGURE 23: BIG DATA COMPONENTS AND ASSETS IN PILOT 2.2.2: MONITORING AND CONTROL TOOLS FOR FOREST OWNERS .......... 53 FIGURE 24: WUUDIS MOBILE APP FOR OBSERVATION REPORTING ........................................................................................ 55 FIGURE 25: TIMELINE OF PILOT 2.2.2, MONITORING AND CONTROL TOOLS FOR FOREST OWNERS ............................................. 56 FIGURE 26: PILOT FORESTY, RANGUNKORPI COOPERATIVE FORESTY, ON THE WUUDIS SERVICE ................................................. 58 FIGURE 27: FORESTRY B1 MOTIVATION VIEW ................................................................................................................. 65 FIGURE 28: FORESTRY B1 STRATEGY VIEW ..................................................................................................................... 66 FIGURE 29: BIG DATA COMPONENTS AND ASSETS IN PILOT 2.3.1 FOREST DAMAGE REMOTE SENSING ....................................... 68 FIGURE 30: TIMELINE OF PILOT 2.3.1, FOREST DAMAGE REMOTE SENSING ........................................................................... 70 FIGURE 31: FORESTRY B1-FH MOTIVATION VIEW ........................................................................................................... 78 FIGURE 32: FORESTRY B1-FH STRATEGY VIEW ................................................................................................................ 79 FIGURE 33: BIG DATA COMPONENTS AND ASSETS IN PILOT 2.3.2-FH: MONITORING OF FOREST HEALTH .................................... 81 FIGURE 34: TIMELINE OF PILOT 2.3.2-FH, MONITORING OF FOREST HEALTH ........................................................................ 83 FIGURE 35: FORESTRY B2-IAS MOTIVATION VIEW .......................................................................................................... 90 FIGURE 36: FORESTRY B2-IAS STRATEGY VIEW ............................................................................................................... 91 FIGURE 37: BIG DATA COMPONENTS AND ASSETS IN PILOT 2.3.2-IAS: INVASIVE ALIEN SPECIES CONTROL AND MONITORING ......... 92 FIGURE 38: TIMELINE OF PILOT 2.3.2-IAS, INVASIVE ALIEN SPECIES CONTROL AND MONITORING .............................................. 94 FIGURE 39: FORESTRY C1 MOTIVATION VIEW ................................................................................................................. 99 FIGURE 40: FORESTRY C1 STRATEGY VIEW ................................................................................................................... 100 FIGURE 41: BIG DATA COMPONENTS AND ASSETS IN PILOT 2.4.1 WEB-MAPPING SERVICE FOR THE GOVERNMENT DECISION MAKING

.................................................................................................................................................................. 101 FIGURE 42: TIMELINE OF PILOT 2.4.1, WEB-MAPPING SERVICE FOR THE GOVERNMENT DECISION MAKING ............................... 103 FIGURE 43: FORESTRY C2 MOTIVATION VIEW ............................................................................................................... 109 FIGURE 44: FORESTRY C2 STRATEGY VIEW ................................................................................................................... 110 FIGURE 45: BIG DATA COMPONENTS AND ASSETS IN PILOT 2.4.2 SHARED MULTIUSER FOREST DATA ENVIRONMENT ................... 111 FIGURE 46: TIMELINE OF PILOT 2.4.2, SHARED MULTIUSER FOREST DATA ENVIRONMENT ...................................................... 114

List of Tables TABLE 1: THE DATABIO CONSORTIUM PARTNERS ............................................................................................................. 10 TABLE 2: ARCHIMATE MOTIVATION AND STRATEGY VIEWS................................................................................................ 15 TABLE 3: ELEMENTS USED IN THE ARCHIMATE MOTIVATION AND STRATEGY VIEWS ................................................................ 16 TABLE 4. PILOTS IN DATABIO WP2 FORESTRY ................................................................................................................ 19 TABLE 5: THE IDENTIFIED STAKEHOLDERS IN EACH PILOT .................................................................................................... 22 TABLE 6: SUMMARY OF PILOT 2.2.1: EASY DATA SHARING AND NETWORKING (ISO JTC1 WG9 USE CASE TEMPLATE) .................. 30 TABLE 7: STAKEHOLDERS AND USER STORIES OF PILOT 2.2.1: EASY DATA SHARING AND NETWORKING ....................................... 32 TABLE 8: EXPLANATION OF SPECIFIC ELEMENTS IN THE FORESTRY A1 FOREST USER STRATEGY VIEW .......................................... 38 TABLE 9: SUMMARY OF PILOT 2.2.2: MONITORING AND CONTROL TOOLS FOR FOREST OWNERS (ISO JTC1 WG9 USE CASE TEMPLATE)

.................................................................................................................................................................... 43 TABLE 10: STAKEHOLDERS AND USER STORIES OF PILOT 2.2.2: MONITORING AND CONTROL TOOLS FOR FOREST OWNERS.............. 46 TABLE 11: SUMMARY OF PILOT 2.3.1 FOREST DAMAGE REMOTE SENSING (ISO JTC1 WG9 USE CASE TEMPLATE) ...................... 58 TABLE 12: STAKEHOLDERS AND USER STORIES OF PILOT 2.3.1 FOREST DAMAGE REMOTE SENSING ........................................... 61



TABLE 13: EXPLANATION OF SPECIFIC ELEMENTS IN THE FORESTRY B1 MOTIVATION VIEW ....................................................... 65 TABLE 14: LIST OF THE ELEMENTS DEFINED IN THE FORESTRY B1 STRATEGY VIEW ................................................................... 66 TABLE 15: SUMMARY OF PILOT 2.3.2-FH: MONITORING OF FOREST HEALTH (ISO JTC1 WG9 USE CASE TEMPLATE) ................... 73 TABLE 16: STAKEHOLDERS AND USER STORIES OF PILOT 2.3.2-FH: MONITORING OF FOREST HEALTH ........................................ 76 TABLE 17: EXPLANATION OF SPECIFIC ELEMENTS IN THE FORESTRY B1-FH MOTIVATION VIEW ................................................. 78 TABLE 18: EXPLANATION OF SPECIFIC ELEMENTS IN THE FORESTRY B1-FH STRATEGY VIEW ...................................................... 80 TABLE 19: LISTING OF THE COMPONENTS USED OR PRODUCED IN THE PILOT 2.3.2-FH: MONITORING OF FOREST HEALTH.............. 81 TABLE 20: SUMMARY OF PILOT 2.3.2-IAS: INVASIVE ALIEN SPECIES CONTROL AND MONITORING (ISO JTC1 WG9 USE CASE TEMPLATE)

.................................................................................................................................................................... 85 TABLE 21: STAKEHOLDERS AND USER STORIES OF PILOT 2.3.2-IAS: INVASIVE ALIEN SPECIES CONTROL AND MONITORING ............. 88 TABLE 22: LISTING OF THE COMPONENTS USED OR PRODUCED IN THE PILOT 2.3.2-IAS: INVASIVE ALIEN SPECIES CONTROL AND

MONITORING................................................................................................................................................... 92 TABLE 23: SUMMARY OF PILOT 2.4.1 WEB-MAPPING SERVICE FOR THE GOVERNMENT DECISION MAKING (ISO JTC1 WG9 USE CASE

TEMPLATE)...................................................................................................................................................... 95 TABLE 24: STAKEHOLDERS AND USER STORIES OF PILOT 2.4.1 WEB-MAPPING SERVICE FOR THE GOVERNMENT DECISION MAKING ... 97 TABLE 25: LISTING OF THE COMPONENTS USED OR PRODUCED IN THE PILOT 2.4.1 WEB-MAPPING SERVICE FOR THE GOVERNMENT

DECISION MAKING .......................................................................................................................................... 101 TABLE 26: SUMMARY OF PILOT 2.4.2 SHARED MULTIUSER FOREST DATA ENVIRONMENT (ISO JTC1 WG9 USE CASE TEMPLATE) .. 105 TABLE 27: STAKEHOLDERS AND USER STORIES OF PILOT 2.4.2 SHARED MULTIUSER FOREST DATA ENVIRONMENT ....................... 107 TABLE 28: EXPLANATION OF SPECIFIC ELEMENTS IN THE FORESTRY C2 STRATEGY VIEW ......................................................... 110 TABLE 29: LISTING OF THE COMPONENTS USED OR PRODUCED IN THE PILOT 2.4.2 SHARED MULTIUSER FOREST DATA ENVIRONMENT

.................................................................................................................................................................. 112



Definitions, Acronyms and Abbreviations Acronym/

Abbreviation Title

BDVA Big Data Value Association

EO Earth Observation

FMI Forest Management Institute (DataBio partner)

ICT Information and communication technologies

KPI Key Performance Indicator

LIPS Land Parcel Identification System

METSAK Finnish Forest Centre (DataBio partner)

MHGS MHG Systems Oy (DataBio partner)

NIR Near-InfraRed

PPP Public-Private Partnership

RGB Red-Green-Blue

RPAS Remotely Piloted Aerial System

RS Remote Sensing

UAV Unmanned Aerial Vehicle

UI User Interface

VNIR Very Near-InfraRed

VTT VTT Technical Research Centre of Finland Ltd (DataBio partner)

WFS Web Feature Service

WMS Web Map Service

WMTS Web Map Tile Service

WWF World Wildlife Foundation



Introduction 1.1 Project Summary The data intensive target sector on which the

DataBio project focuses is the Data-Driven

Bioeconomy. DataBio focuses on utilizing Big

Data to contribute to the production of the

best possible raw materials from agriculture,

forestry and fishery (aquaculture) for the

bioeconomy industry, as well as their further

processing into food, energy and

biomaterials, while taking into account various accountability and sustainability issues.

DataBio will deploy state-of-the-art big data technologies and existing partners’ infrastructure

and solutions, linked together through the DataBio Platform. These will aggregate Big Data

from the three identified sectors (agriculture, forestry and fishery), intelligently process them

and allow the three sectors to selectively utilize numerous platform components, according

to their requirements. The execution will be through continuous cooperation of end user and

technology provider companies, bioeconomy and technology research institutes, and

stakeholders from the big data value PPP programme.

DataBio is driven by the development, use and evaluation of a large number of pilots in the

three identified sectors, where associated partners and additional stakeholders are also

involved. The selected pilot concepts will be transformed to pilot implementations utilizing

co-innovative methods and tools. The pilots select and utilize the best suitable market-ready

or almost market-ready ICT, Big Data and Earth Observation methods, technologies, tools and

services to be integrated to the common DataBio Platform.

Based on the pilot results and the new DataBio Platform, new solutions and new business

opportunities are expected to emerge. DataBio will organize a series of trainings and

hackathons to support its uptake and to enable developers outside the consortium to design

and develop new tools, services and applications based on and for the DataBio Platform.

The DataBio consortium is listed in Table 1. For more information about the project see [REF-

01].

Table 1: The DataBio consortium partners

Number Name Short name Country

1 (CO) INTRASOFT INTERNATIONAL SA INTRASOFT Belgium

2 LESPROJEKT SLUZBY SRO LESPRO Czech Republic

3 ZAPADOCESKA UNIVERZITA V PLZNI UWB Czech Republic



4 FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER

ANGEWANDTEN FORSCHUNG E.V.

Fraunhofer Germany

5 ATOS SPAIN SA ATOS Spain

6 STIFTELSEN SINTEF SINTEF ICT Norway

7 SPACEBEL SA SPACEBEL Belgium

8 VLAAMSE INSTELLING VOOR TECHNOLOGISCH

ONDERZOEK N.V.

VITO Belgium

9 INSTYTUT CHEMII BIOORGANICZNEJ POLSKIEJ

AKADEMII NAUK

PSNC Poland

10 CIAOTECH Srl CiaoT Italy

11 EMPRESA DE TRANSFORMACION AGRARIA SA TRAGSA Spain

12 INSTITUT FUR ANGEWANDTE INFORMATIK (INFAI) EV INFAI Germany

13 NEUROPUBLIC AE PLIROFORIKIS & EPIKOINONION NP Greece

14 Ústav pro hospodářskou úpravu lesů Brandýs nad

Labem

UHUL FMI Czech Republic

15 INNOVATION ENGINEERING SRL InnoE Italy

16 Teknologian tutkimuskeskus VTT Oy VTT Finland

17 SINTEF FISKERI OG HAVBRUK AS SINTEF

Fishery

Norway

18 SUOMEN METSAKESKUS-FINLANDS SKOGSCENTRAL METSAK Finland

19 IBM ISRAEL - SCIENCE AND TECHNOLOGY LTD IBM Israel

20 MHG SYSTEMS OY - MHGS MHGS Finland

21 NB ADVIES BV NB Advies Netherlands

22 CONSIGLIO PER LA RICERCA IN AGRICOLTURA E

L'ANALISI DELL'ECONOMIA AGRARIA

CREA Italy

23 FUNDACION AZTI - AZTI FUNDAZIOA AZTI Spain

24 KINGS BAY AS KingsBay Norway

25 EROS AS Eros Norway

26 ERVIK & SAEVIK AS ESAS Norway

27 LIEGRUPPEN FISKERI AS LiegFi Norway

28 E-GEOS SPA e-geos Italy



29 DANMARKS TEKNISKE UNIVERSITET DTU Denmark

30 FEDERUNACOMA SRL UNIPERSONALE Federu Italy

31 CSEM CENTRE SUISSE D'ELECTRONIQUE ET DE

MICROTECHNIQUE SA - RECHERCHE ET

DEVELOPPEMENT

CSEM Switzerland

32 UNIVERSITAET ST. GALLEN UStG Switzerland

33 NORGES SILDESALGSLAG SA Sildes Norway

34 EXUS SOFTWARE LTD EXUS United

Kingdom

35 CYBERNETICA AS CYBER Estonia

36 GAIA EPICHEIREIN ANONYMI ETAIREIA PSIFIAKON

YPIRESION

GAIA Greece

37 SOFTEAM Softeam France

38 FUNDACION CITOLIVA, CENTRO DE INNOVACION Y

TECNOLOGIA DEL OLIVAR Y DEL ACEITE

CITOLIVA Spain

39 TERRASIGNA SRL TerraS Romania

40 ETHNIKO KENTRO EREVNAS KAI TECHNOLOGIKIS

ANAPTYXIS

CERTH Greece

41 METEOROLOGICAL AND ENVIRONMENTAL EARTH

OBSERVATION SRL

MEEO Italy

42 ECHEBASTAR FLEET SOCIEDAD LIMITADA ECHEBF Spain

43 NOVAMONT SPA Novam Italy

44 SENOP OY Senop Finland

45 UNIVERSIDAD DEL PAIS VASCO/ EUSKAL HERRIKO

UNIBERTSITATEA

EHU/UPV Spain

46 OPEN GEOSPATIAL CONSORTIUM (EUROPE) LIMITED

LBG

OGCE United

Kingdom

47 ZETOR TRACTORS AS ZETOR Czech Republic

48 COOPERATIVA AGRICOLA CESENATE SOCIETA

COOPERATIVA AGRICOLA

CAC Italy



1.2 Document Scope This deliverable document D2.1 Forestry Pilot Definition (due M06) specifies the pilot case

definitions, requirement specifications, as well as implementation and evaluation plans.

The specification of KPIs and business models is primarily left for inclusion in WP7

deliverables.

Reporting the results of the pilots is out of the scope of this document, and will instead be

included in D2.2 Forestry Pilots Intermediate Report (M24) and D2.3 Forestry Pilots Final

Report (M36).

1.3 Document Structure

This document is comprised of the following chapters:

Chapter 1 presents an introduction to the project and the document.

Chapter 2 presents the chosen pilot modelling framework and gives an overview on all the

pilots and their associated plans and requirements, making note of the commonalities and

differences between them.

Chapters 3 to 9 give a detailed view on each pilot respectively. Provided first for each pilot

are pilot overview and pilot case definition - including stakeholders, user stories, motivation

and strategy, as well as the scope and limitations. This is followed by a number of selected

outputs from pilot modelling, which is an ongoing work that will be continued and extended

in the context of WP4. Here, the focus is to provide Motivation and Strategy views for each

pilot. Finally, big data related components and assets created or used in the project are

described, followed by pilot evaluation plans and initial roadmaps.



Summary 2.1 Overview The objective of WP2 Forestry Pilot is to demonstrate through pilots how Big Data will boost

the forestry sector. The pilots, carried out in four countries, are built around practical cases

from forestry. They will validate the use of Big Data technologies and how well the

expectations of user communities are met. In order to do this, the WP will:

● Specify the requirements for the three pilots based on the DataBio platform

● Implement the pilots giving access to all tools developed

● Gather experiences from the pilots

Detailed reports of the design and experiences from the pilots are provided as deliverables.

Big Data technologies will be tested and validated in three main cases: Multisource

crowdsourcing services (Task 2.2), Forest Health (Task 2.3) and Forest Data Management

Services (Task 2.4).

The forest pilots will aim to:

1. Improve identification of forest damages from biotics - such as pest and diseases - or

abiotics - such as snow, thunderstorms (wind), dryness, rains, fires - using remote

sensors.

2. Optimize the use of tree resources: Detailed characterization of trees through e.g.

airborne laser scanning (knottiness, carvery) for determining the optimal use of trees

for a given output, e.g. pulp, paper, textile, biofuels, etc., in order to guarantee that

supply meets demand.

3. Provide forest health maps to forest owners or public administrators, based on

remote sensing data. Later on, maps of implemented cuttings will be provided for

verification and reforestation control.

Integrated tools are developed and new management plans are implemented that take into

account non-wood products and conservation areas while at the same time maximising

timber production and economic yield.

In most European countries, traditional methods for forest management are based on “static”

management plans, created at the planting stage and reviewed every 10 years. In recent

years, these management plans have become a declaration of intentions, including objectives

for multifunctional forests (non-wood products and services). However, these plans often lack

effective implementation and monitoring methods that allow forest owners, managers and

regulators to validate the progress in achieving the target objectives set out in the

management plan.



2.2 Pilot modelling framework The pilot cases are modelled using the ArchiMate 3.0 modelling framework. Figure 1

summarizes the overall ArchiMate 3.0 framework. The figure also depicts the input provided

by the domain WPs (WP1, WP2, WP3 and their pilots) and that provided by the technology

WPs (WP4, WP5), which will be correlated in the next stages of modelling process.

Figure 1: ArchiMate 3.0 modelling framework.

The modelling presented in this deliverable focuses on the “Motivation” and “Strategy” views.

The “Motivation” view models the reasons that guide the design of the architecture. The

“Strategy” view adds how the course of action is realized. Table 2 provides an extended

description of the two views. After the completion of this deliverable, the plan is to extend

the modelling with other views, while investigating the correlations with the technology WP

input.

Table 2: ArchiMate Motivation and Strategy views.

View name Description

Motivation

view

Motivation elements are used to model the motivations, or reasons, that guide the

design or change of an Enterprise Architecture. It is essential to understand the

factors, often referred to as drivers, which influence other motivation elements.

They can originate from either inside or outside the enterprise. Internal drivers, also

called concerns, are associated with stakeholders, which can be some individual



human being or some group of human beings, such as a project team, enterprise, or

society. Examples of such internal drivers are customer satisfaction, compliance to

legislation, or profitability.

Strategy

view

The immediate decision support system is built on top of a data collection and

distribution system. The data collection and distribution system is used to collect

sensor data from the on-board systems and makes them available in a single system.

The data distribution system ensures that the decision support system only interface

with a single system, instead of multiple sensors. The decision support system

presents the data from the data distribution system and collect them in an internal

storage system for presentation of current performance vs. historic performance.

The main elements used in the above views are explained in Table 3. Their relationships are

shown in Figure 2 and Figure 3. For further information see [REF-02].

Table 3: Elements used in the ArchiMate Motivation and Strategy views

Element Definition Notation

Stakeholder The role of an individual, team,

or organization (or classes

thereof) that represents their

interests in the outcome of the

architecture.

Driver An external or internal condition

that motivates an organization

to define its goals and

implement the changes

necessary to achieve them.

Assessment The result of an analysis of the

state of affairs of the enterprise

with respect to some driver.

Goal A high-level statement of intent,

direction, or desired end state

for an organization and its

stakeholders.



Outcome An end result that has been

achieved.

Principle A qualitative statement of intent

that should be met by the

architecture.

Requirement A statement of need that must

be met by the architecture.

Constraint A factor that prevents or

obstructs the realization of

goals.

Meaning The knowledge or expertise

present in, or the interpretation

given to, a core element in a

particular context.

Value The relative worth, utility, or

importance of a core element or

an outcome.

Resource An asset owned or controlled by

an individual or organization.

Capability An ability that an active

structure element, such as an

organization, person, or system,

possesses.

Course of

action

An approach or plan for

configuring some capabilities

and resources of the enterprise,

undertaken to achieve a goal.



Figure 2: Relationships of the Motivation elements

Figure 3: Relationships of the Strategy elements

2.3 Pilot introductions Within the three overall cases outlined above - Multisource crowdsourcing services, Forest

Health and Forest Data Management Services - the work is arranged into seven pilots. The full

pilot descriptions and plans are given in chapters 3 to 9 of this document. Below is a summary

table, giving also linking between the pilot IDs and the chapters in this document. The table

is followed by a brief introduction of each pilot.



Table 4. Pilots in DataBio WP2 Forestry

Pilot ID Pilot title Pilot leader Project partners D2.1 chapter

2.2.1 Easy data sharing and networking MHGS VTT, SPACEBEL, METSAK

3

2.2.2 Monitoring and control tools for forest owners

MHGS FMI, TRAGSA, METSAK

4

2.3.1

Forest damage remote sensing MHGS VTT, SENOP, METSAK, SPACEBEL

5

2.3.2-FH

Monitoring of forest health TRAGSA SENOP, CSEM, CiaoT, FMI, VTT

6

2.3.2-IAS Invasive alien species control and monitoring

TRAGSA SENOP, CSEM, CiaoT, FMI, VTT

7

2.4.1 Web-mapping service for the government decision making

FMI VTT, SPACEBEL 8

2.4.2 Shared multiuser forest data environment

METSAK VTT 9

Pilot 2.2.1 - Easy data sharing and networking - aims to develop and pilot standardized

procedures for collecting and transferring data utilizing the Wuudis Service and DataBio

platform from silvicultural activities executed in the forest. Wuudis, developed by MHGS, is a

commercial service for forest owners, timber buyers and forestry service companies for

management of forestry activities and forest resource management. The goal is to develop

and validate Wuudis’ collaboration features, quality monitoring and social forest platform

features in selected pilot areas. In addition, one important goal is also to integrate the Wuudis

Service to external services such as map services and authority systems. In Finland, there are

two estates selected for this pilot, called Rangunkorven yhteismetsä and Taipale.

Pilot 2.2.2 - Monitoring and control tools for forest owners - aims to develop standardized

procedures and apps for collecting, monitoring and transferring data utilizing the Wuudis

Service and the DataBio platform, to be exported to 3rd party IT systems through standard

interfaces. In this pilot, an end-to-end data transfer solution will be developed between the

Wuudis Service and METSAK´s metsaan.fi eService. Forest damage (like storms, snow, pests,

insects, fungi) monitoring through standardized procedures will be developed together with

METSAK as well as easy-to-use mobile tools for these damage monitoring needs and non-

wood product monitoring needs.

Pilot 2.3.1 - Forest damage remote sensing - aims to develop a Forest Inventory system on

the Wuudis Service based on remote sensing (satellite, aerial, UAV) and field surveys. Selected

Big Data partners will integrate their existing market-ready or almost market-ready



technologies onto the Wuudis Service, and the resulted solutions are piloted with Wuudis

users, forestry sector partners, associated partners and other stakeholders. The pilot will

develop a comprehensive and near real-time quantitative assessment of forest cover, forest

aboveground carbon stock and carbon stock change over the project pilot area (Rangunkorpi

cooperative forestry). This allows detecting and measuring damages, deforestation and forest

degradation, which is a major cause of loss of biomass and carbon stores.

Pilot 2.3.2-FH - Monitoring of forest health - aims to set up a methodology based on remote

sensing images (satellite + aerial + UAV) and field data for the monitoring of the health status

of forests in large areas of the Iberian Peninsula. The work will focus, particularly, in the

monitoring of the health of Quercus sp. forests affected by the fungus Phytophthora

cinnamomi Rands and of the damage in eucalyptus plantations affected by the coleoptera

Gonipterus scutellatus Gyllenhal. EO-based solutions will provide Public Bodies with valuable

information and tools to help decision making. An EO-based system for monitoring the health

of big forest areas will be set up (mapping + assessment tools), so Authorities will be able to

optimise forest management resources. A mapping and assessment tool will be developed

for monitoring the damages caused by Gonipterus in eucalyptus plantations, as well as for

damage assessment, in order to adapt management and minimise economic losses.

Pilot 2.3.2-IAS - Invasive alien species control and monitoring - aims to develop a simple

model for assessing invasion risk in Spain based on a set of factors that strongly influence the

geographic pattern and level of invasion: 1) Environmental similarity, calculated from

bioclimatic variables; 2) Biodiversity similarity, approached through biogeographic

information; 3) Propagule pressure, estimated from data on trade, tourism, immigration,

population and terrestrial transport network; and 4) Ecosystem disturbance, measured from

land use and fire frequency. The pilot case is linked to prevention, which is both an effective

and efficient way of dealing with the problem of biological invasions. Indeed, the pilot will

identify the areas in Spain at greatest risk of invasion and the most likely source regions of

IAS, thus providing crucial information for resource prioritization and for a much better

management of these species.

Pilot 2.4.1 - Web-mapping service for the government decision making - aims to develop a

new methodology for forest health assessment based on Copernicus satellite data. This allows

assessing the forest health of the entire area of Czech Republic and other temperate forest

regions in Europe, while reducing costs for field surveys and highly effective identification of

forest owners eligible for subsidies / tax relief. This pilot focuses on technological

development of the processing of Sentinel-2 optical data. Utilizing the great potential of high-

spatial and temporal resolution satellite data for forestry, with special focus on forest health

trends is the main goal of the pilot. In addition, the forest owners will benefit from publicly

available map server and implementation of the layers on the Wuudis platform, where all

forest health status maps will be published to allow pro-active management of their forest

properties.

Pilot 2.4.2 - Shared multiuser forest data environment - aims to pilot presenting

crowdsourced forest data and possible new functionalities related to it in Metsään.fi eService



and therefore enhance the use of Metsään.fi and METSAK’s forest resource data. Metsään.fi

is an eService provided by the governmental body, the Finnish Forest Centre (METSAK), to

make forest resource information available for citizens free of charge. Metsään.fi eService is

constantly developed by METSAK. The collecting methods are also aimed to increase the

amount of METSAK’s forest resource data. The plan is to pilot presenting crowdsourced forest

data and possible new functionalities related to it in Metsään.fi eService and therefore

enhance the use of Metsään.fi and METSAK’s forest resource data.

2.3.1 Wuudis

Several of the pilots are linked with the Wuudis platform and services by MHGS. The Wuudis

Service developed by MHGS is a unique commercial service on the market for forest owners,

timber buyers and forestry service companies. It enables the management of forestry

activities and forest resource management through a single tool. The cloud-based platform,

with a mobile interface and data in XML and JSON formats, connects forest owners directly

with local contractors and timber buyers. With it, forest owners and other stakeholders can

effectively manage their forest resources remotely in real-time. It can be used to obtain real-

time information about the forest and its timber resource, track executed silvicultural and

harvest activities, plan the needed forest management activities, and bid for care works and

timber sales online.

The Wuudis Networking feature allows users to create a group inside the Wuudis Service and

share forestry information flawlessly with the people of choice. The user can define a different

level of access for each user, for example a view-only access or an access to do both viewing

and editing. Access to the information increases the transparency and effect of mutual

decision-making, for example in timberland investment companies.

The Wuudis Monitoring feature allows users to collect various data including non-wood

products and to monitor any changes in the forest on the Wuudis Service and share this

information flawlessly with the people of choice. The user can define a different level of

access for each user, for example the view-only access or the access to do both. Access to the

realtime information - situation view - improves real time guidance, for example for

harvesting operations in high biodiversity sites, while decreasing risks for operational

damages due to miscommunication. It also improves bidding through marketplaces, for

example for care works or harvesting operations, in particular after storm damage occurred,

enabling faster and more organized exploitation operations than at present.

2.4 Pilot case definitions The pilot case definitions in the respective chapters of this deliverable include identification

of stakeholders, their goals and expected benefits (sections X.2.1), as well as explanation of

pilot motivation and strategy (sections X.2.2). These form the requirement specifications for

the pilot and are used in subsequent sections in pilot modelling. Finally, the scope and

limitations of each pilot are given (sections X.2.3). The identified stakeholders in each pilot

are listed in the below table.



Table 5: The identified stakeholders in each pilot

Pilot ID Pilot title Stakeholders

2.2.1 Easy data sharing and networking Forest owner Forestry contractor Timber buyer Forest authority expert

2.2.2 Monitoring and control tools for forest owners

Forest owner Forestry contractor Timber buyer Forest authority expert Forest insurance company MHGS service provider

2.3.1

Forest damage remote sensing Forest owner Forestry contractor Timber buyer Forest authority expert Forest insurance company MHGS service provider

2.3.2-FH

Monitoring of forest health End user (Junta de Extremadura) End user (Xunta de Galicia) End user (Public Administrations) TRAGSA Technician Generic user

2.3.2-IAS Invasive alien species control and monitoring

End user (MAPAMA-Policy Makers)

End user (Public Administrations)

TRAGSA Technician Generic user

2.4.1 Web-mapping service for the government decision making

Ministry of Agriculture of the Czech Republic Local forest owners, including Forests of the Czech Republic and Wallonia

2.4.2 Shared multiuser forest data environment

Forest owner Forestry operator METSAK user

2.5 Big data assets For each pilot described in chapters 3 to 9, section X.4 introduces the usage and development

of Big Data assets and components, via a supporting figure that is based on a reference

classification developed by the Big Data Value Association (BDVA). For most pilots, it has been

possible at this stage to take the presentation to the level of identifying the type of assets

used or developed in various layers. On a number of the pilots it has been possible already to



uniquely name each component. In all cases, the presentation gives the best estimate at this

point in pilot preparation.

2.6 Evaluation plans The evaluation plans for each pilot are given in sections X.5 in chapters 3 to 9. These are

presented as lists of identified Key Performance Indicators (KPIs) that will be used in

evaluation of the results of each pilot. Depending on how advanced the discussions are with

the external stakeholders, the KPIs are presented either with target values or with more

general descriptions.

2.7 Implementation plans The implementation plans with the actions and schedule for each pilot are given in sections

X.6 (Initial roadmap) in Chapters 3 to 9. The schedules are designed to align with both the

project overall schedule and the development plans of external associated partners and

stakeholders in each pilot.

Timeline figures regarding each pilot are presented jointly below.

Figure 4: Timeline of pilot 2.2.1, Easy data sharing and networking



Figure 5: Timeline of pilot 2.2.2, Monitoring and control tools for forest owners

Figure 6: Timeline of pilot 2.3.1, Forest damage remote sensing



Figure 7: Timeline of pilot 2.3.2-FH, Monitoring of forest health

Figure 8: Timeline of pilot 2.3.2-IAS, Invasive alien species control and monitoring



Figure 9: Timeline of pilot 2.4.1, Web-mapping service for the government decision making

Figure 10: Timeline of pilot 2.4.2, Shared multiuser forest data environment



Pilot 2.2.1: Easy data sharing and networking 3.1 Pilot overview

3.1.1 Pilot introduction

This pilot aims to develop and pilot standardized procedures for collecting and transferring

data utilizing the Wuudis Service and DataBio platform from silvicultural activities executed

in the forest. The Wuudis Service and the Wuudis Networking features are applied in the pilot;

see section 2.3.1 for explanation on these.

Data sharing and a collaborative environment enables improved tools for sustainable forest

management decisions and operations. Data becomes accessible to forest owners and other

end users interfacing with market place, e-contracting, online purchase and sales of timber

and biomass. Higher data volumes and better data accessibility increase the probability that

the data will be updated and maintained.

In the DataBio project, selected Big Data partners will integrate their existing market-ready

or almost market-ready technologies onto the Wuudis Service, and the resulted solutions will

be piloted with the Wuudis users, forestry sector partners, as well as associated partners and

other stakeholders, e.g. NGOs related to nature conservation. This integration also applies to

the pilot 2.4.2 Shared multiuser forest data environment in WP2.

This pilot is developed in Task 2.2.1 Easy data sharing and networking and the task 2.4.2

Shared multiuser forest data environment, in the context of the WP2 Forestry pilot. The

involved partners are: MHGS, VTT, SPACEBEL and METSAK.

3.1.2 Pilot overview

All current real estate data is integrated from METSAK´s metsaan.fi eService to the Wuudis

platform for DataBio pilots. Data is transferred via the Finnish forestry standard XML format.

This initial forestry data is very crucial for the pilot because every update will affect the initial

data directly. Modified and updated data should also go back to the authorities via integration

interfaces. In this pilot, the Wuudis Service will work as a data sharing platform between

authorities and end users providing mobility and data modification tools for the users.

We develop and use a work quality monitoring app (available for Microsoft, iOS and Android

mobile platforms) in order to feed the forest inventory master data in real time operations

into the METSAK´s databases, metsaan.fi and METSAK’s forest resource data. High quality

updates are provided for strategic planning through the Wuudis platform and for paying

subsidies for cleaning and treating young seedling and young forest stands in a controlled way

by METSAK. The collecting methods are aimed to improve work quality and customer

satisfaction, and increase competition between contractors resulting in decreasing care work

costs paid by forest owners.

The goal is to develop and validate Wuudis’ collaboration features, quality monitoring and

social forest platform features in selected pilot areas. In addition, one important goal is also



to integrate the Wuudis Service to external services such as map services and authority

systems. In Finland, there are two estates selected for this pilot, called “Rangunkorven

yhteismetsä” and “Taipale”, both located in Central Finland.

Figure 11: Pilot estate forestry data transferred into Wuudis from the forestry authority system (metsaan.fi)

This pilot specifies the requirements for refining and showing the crowdsourced forest data

to metsaan.fi users. The implementation of the new functionalities will be carried out in

collaboration with the Metsään.fi development team and other METSAK's projects. This pilot

gives specifications to other projects and follows up the implementation according to these

specifications in Czech Republic and Belgium by WP2 partners (FMI and SPACEBEL

respectively), which will be specified at a later stage.

To summarize, the following improvements will be developed for the Wuudis Service:

1. Development of data sharing features for more flexible data sharing

2. Development of more flexible collaboration features

3. Development of the Wuudis mobile app to enable work quality monitoring in a

standardized way (sample plots “kemera”)

The work quality monitoring data consists of the following information: forest estate,

geometry of compartments, type of the forest work, sample plot locations, measured data

per sample plot, measurement averages per compartment, measurement date and user



information. The quality control data will be added to the existing forest data standard during

2017.

4. Development of a feature that allows the user to decide what data he/she wants to

send back to the authority.

5. Development of an interface to the authority system (for example metsaan.fi), which

requires a strong user identification. Other requirements need to be defined during

the pilot.

6. Send quality data back to the authority system.

7. Development of sharing features to the existent market places if needed.

8. Specify all data sources and formats that are needed to accomplish all user

requirements (maps, reports, tables, etc.).

9. Execution of all integrations that are specified.

Figure 12: Data sharing in Wuudis



Table 6: Summary of pilot 2.2.1: Easy data sharing and networking (ISO JTC1 WG9 use case

template)

Use case title Easy data sharing and networking

Vertical (area) Forestry

Author/company/email Seppo Huurinainen & Veli-Matti Plosila / MHGS [email protected] [email protected]

Actors/stakeholders and their roles and

responsibilities

Forest owners and forestry operators as Wuudis Service users. The Wuudis (MHGS) admin users who use and refine the forest resource data and make it available for Wuudis users.

Goals To increase the use of Wuudis freemium and commercial Services and in parallel use METSAK’s forest resource data.

Use case description Specifying the requirements for new information and functionalities of Metsään.fi’s eService and implementing them in collaboration with the Metsään.fi development team and other METSAK projects. Developing a work quality monitoring app (MS, IoS, Android), further developing networking features for the Wuudis service to facilitate easy and real-time communication.

Current solutions

Compute(System) MHGS´s internal systems related to forest resource data.

Storage Databases for MHGS’s internal forest resource data and map systems, for publishing forest resource data for Wuudis and Metsään.fi.

Networking Web based and mobile solution for Wuudis and Metsään.fi users

Software Wuudis service

Big data characteristics

Data source (distributed/centralized)

Mobile data service, modern smartphone/tablet, web browser, open API to the authority and 3rd party systems

Volume (size) Scalable through international service provider

Velocity (e.g. real time)

Real time updates from field measurements, quality control, forest owners’ forest management plans and other notifications from forest owners, forestry operators and other stakeholders

Variety (multiple datasets,

mashup)

Multiple datasets: tree stand basic data, tree stand strata, growth place (site quality)



Variability (rate of change) Same as above (velocity).

Big data science (collection, curation,

analysis, action)

Veracity (Robustness Issues, semantics)

The data source must be saved within the forest resource data (e.g. data from forest owner vs. measured and analyzed data)

Visualization The user interface is the existing Wuudis Service and its map views. For MHGS admin users there are also existing internal systems with which the data is browsed and handled.

Data quality (syntax) Collected forest operative and quality data must be consistent with the specific standards.

Data types Tree stand basic data, tree stand strata data, growth place data (site quality), location data, time and user stamps.

Data analytics National averages of work quality.

Big data specific challenges (Gaps)

To balance between data publicity and privacy; To adapt to the new Finnish Forest Act being revised at the moment; To take into account the users of the Wuudis service, public authorities’ and Metsään.fi eService user needs.

Big data specific challenges in bio-

economy

To maintain the consistency of data and the usability of new data, functionalities and services from the Wuudis service users’ point of view to better support clients´ forests and their related business development and decision-making, and therefore bio-economy.

Security and privacy technical considerations

There are both public and private data in the Wuudis Service. Personal and forest estate specific information are private. National Forest Acts set demands on data publicity and privacy issues.

Highlight issues for generalizing this Use case (e.g. for ref. architecture)

Using data standards in the interfaces. Visualizing complex data in a logical and understandable way.

More information (URLs) https://www.databio.eu/en/

Notes: - Spacebel: The Wuudis service will be integrated in the EO Regions! multi-thematic EO

services platform in Wallonia.The forestry services developed in the framework of the EUGENIUS projects will reciprocally be integrated in the Wuudis service for the Finnish market.

- MHGS: Development of features for strategic planning in order to promote forest property management and timber sales (automated alarms, request for automated bidding, group sales etc.)

https://www.databio.eu/en/



3.2 Pilot case definition

3.2.1 Stakeholders and user stories

Table 7: Stakeholders and user stories of pilot 2.2.1: Easy data sharing and networking

Who I want to Why

Forest

owner

I want to report care works (with pictures,

video & positioning) easily with mobile

application

I want to get quality reports from my

contractor

I want that work quality reports and work

integrate with the authority central

database

I want to get real time information from

the contractor

I want to share my forest estate data to

contractors easily

I want the service to offer me guidance

To prove to METSAK, who is paying the

subsidies, that the job was done

according to guidelines and

recommendations

To see and control what happens in my

forest

To be sure that information from my

forest is accurate for growth

simulations

To maintain my forest data updated,

and to follow and evaluate the quality

of work of the contractor I have made

contract with

For the contractor to easily find the site

and understands what to do there

To follow harvesting and care works

time frame to maximize my incomes,

minimize costs and control significant

vegetation changes, such as clear-cuts

and forest damage areas to act in time



Forestry

contractor

I want to easily share and report forest

estate data with the forest owner

I want to receive forest data

I want to get more deals doing business

directly with forest owners

I want to make winning offers for group

offer requests

I want to network with my subcontractors

I want to know if, where and when

significant vegetation changes, such as

damages, occur in the forests I’m working

on

I want to know what are the major tree

species in the forests I’m working on and

where they are

To provide a superior customer service

to my clients

To receive conveniently the forest data

to my standard interface, smart phone

or tablet

For better profit and less work

without principals and middle men

To win deals thanks to precise data

available for cost analysis

To outsource part of my deals by

networking smoothly with my

subcontractors

To be ready to act as soon as possible to

win deals in any business environment

To focus on the most profitable sites



Timber

buyer

Forest

authority

expert

I want to receive forest data easily to my

smart phone or tablet

I want that my contractors do work quality

controls

I want to get more matching deals for my

purchase targets

I want that work quality reports are

reliable and integrate automatically with

the central authority database

I want to report work quality inspections

easily and in a reliable manner through

mobile application

I want to know when and where significant

vegetation changes, such as clear-cuts,

occur

To receive conveniently the forest data


or tablet

For customer satisfaction, it is

important to report to forest owners

and my supervisors. In addition, the

reporting method must interface with

our IT system

To close deals with fewer expenses by

understanding better in

site/compartment level available tree

species and assortments etc.

To develop and implement new

business practices with minimum

paperwork to become more cost

efficient

For simple and compatible solutions

everyone is ready to learn and use

To use my standard interface, smart

phone, as a reporting tool because I

take care of daily routines like banking

through apps

It is of utmost importance to act as soon

as possible if something unusual

happens in the forest in order to

prevent additional damages while

ensuring e.g. harvesting operations

3.2.2 Motivation and strategy

New features will be delivered/deployed continuously. All new bigger features are split into

small parts to enable fast deployment and testing cycles. The most important thing is to

prioritize and understand these development requirements correctly first.

After the developed features are tested by the development team and deployed to the

production environment, these features are ready for the DataBio pilot case to be tested in

practical operations by committed Wuudis users, associate partners and other possible



Wuudis users (Kemera work quality documentation service). In Wallonia, Belgium, the

integration of the Wuudis service with EO Regions! will be planned and executed together

with SPACEBEL and its network.

The key advantage is that forest contractors can better respond to forest owners and

authority expectations about work quality concerning subsidy payments by METSAK. Forest

owners are able to follow the quality of care work in their forests and in the meantime get

real time updates for their forest management plan. METSAK will save tax payers´ money

because field inspections will not be needed any more thanks to reliable e-reporting by

contractors and forest owners.

Wuudis users are able to update the forest resource data not only to the Wuudis Service but

to the Metsään.fi eService too, thus providing better customer service and satisfaction than

competitor solutions. This should bring more paying customers to MHGS, being the first

service provider with such a complete service package from forest to authority database.

3.2.3 Scope and limitations

This pilot operates in an existing service environment of MHGS producing new data and

functionalities related to the Wuudis Service. The pilot scope is to:

- develop a work quality monitoring app seamlessly interfacing with METSAK´s

metsään.fi eService

- test the app in the field operations with associate partners and other stakeholders

The limitations in this pilot may be caused by:

- Operating in METSAK’s system environment and its development: this sets both

content and schedule limitations when specifying and testing changes in Metsään.fi.

- The forest data standard: all the forest data interfaces must be consistent with the

forest data standard.

3.3 Pilot modelling with ArchiMate In this pilot, there is an existing technical environment of the Wuudis Service. Any data

modelling or architecture design is done by MHGS´s internal Wuudis development team. Pilot

modelling in this section is therefore applicable to a limited extent only.

This section presents the "Forestry A1 Easy data sharing and networking modelling with

ArchiMate" view point described using the ArchiMate standard.

3.3.1 DataBio forestry pilot 2.2.1 motivation view

Figure 13 describes the "Forestry A1 Motivation view" defined in the "Forestry A1 Easy data

sharing and networking modelling with ArchiMate" view point.



Figure 13: Forestry A1 Motivation view

Figure 14 below is the "Forestry A1 Forest User Motivation view" defined in the "Forestry A1

Easy data sharing and networking modelling with ArchiMate" view point.

Figure 14: Forestry A1 Forest User Motivation view

The goal “Prove conformance to recommendation and guidelines” is further explained with

this description: “Prove to myself and to METSAK who is paying subsidies that the job was

done according to guidelines and recommendations.”

3.3.2 DataBio forestry pilot 2.2.1 strategy view

Figure 15 describes the "Forestry A1 Strategy view" defined in the "Forestry A1 Easy data

sharing and networking modelling with ArchiMate" view point.



Figure 15: Forestry A1 Strategy view

Figure 16 below is the "Forestry A1 Forest User Strategy view" defined in the "Forestry A1

Easy data sharing and networking modelling with ArchiMate" view point. Table 8 provides

further explanations to a number of the view's elements.

Figure 16: Forestry A1 Forest User Strategy view



Table 8: Explanation of specific elements in the Forestry A1 Forest User Strategy view

Name Description

Action: Integrate work and its quality

reports with authority central database

Get quality reports from my contractor

Action: Report care works Report care works (with pictures, video & positioning)

easily with mobile application

Goal: Prove conformance to

recommendations and guidelines

Prove to myself and to METSAK who is paying subsidies

that the job was done according to guidelines and

recommendations



3.4 Big Data infrastructure: Components and BDVA classification The existing technical environment of the Wuudis Service concerning big data components

and assets is described in Figure 17 below. This pilot is about further development of the

Wuudis Service features in order to better serve all its customers and partner groups: forest

owners, contractors, timber buyers and authorities.

Figure 17: Big data components and assets in pilot 2.2.1: Easy data sharing and networking



3.5 Pilot evaluation plan

3.5.1 High level goals and KPIs

There are several KPIs for this pilot to evaluate the results yearly and in the end of the project.

Perhaps the most logical approach to evaluate these innovations is through real customer use

cases in forestry operations. These will be identified, specified and agreed with piloting clients

in business practicalities during the project.

The KPIs identified for this pilot include:

● %Increase in contract work productivity following the e-tools available/developed

vs. what would be the time spent following standard contracting practices based on

paper documents and paper maps

○ Quantify %increase in productivity for example for young seedling stand

cleaning (contractor and authority).

● %Decrease in operational costs for performing the same contracting activities

(through accurate site information and better management of resources) following

the e-tools available/developed vs. what would be the revenue (per hour) following

standard practices based on data on paper form

○ Quantify %Decrease in operational costs for example for young seedling

stand cleaning (contractor and authority).

● %Increase customer satisfaction following the networking e-tools

available/developed vs. what would be the satisfaction following standard

communication practices based on contractor's present practicalities (phone, SMS,

work quality report if any)

○ Quantify %increase in satisfaction for example for young seedling stand

cleaning work quality reporting (contractor and forest owner).

The amount of forest owners and other users as Wuudis Service users is now around 2 700.

The amount is expected to increase as follows: 5 000 in the end of 2017, 10 000 in the end of

2018 and 50 000 in the end of 2019.

The final KPIs will be specified with associate partners and other stakeholders based on

selected study cases.

3.6 Initial roadmap The Wuudis Service roadmap and implementation plan for this pilot is as follows:

1. Wuudis mobile app development: Work quality monitoring

2. Development of data sharing and collaboration features to become more flexible

3. Export work quality data in standard XML format

4. Interface/integration development with the metsaan.fi service

5. Evaluate developed features with real end users (like associate partners and other

Wuudis users)



All forest resource data from the Wuudis Service is saved in a centralized forest resource data

system. The Wuudis Service uses that data through a publishing database and other existing

interfaces.

The app will be developed, implemented and integrated with Metsään.fi eService in Q4/2017.

The implementation and further development schedule described in Figure 18 is partially

dependent on the schedule of Metsään.fi’s development plans.

Figure 18: Timeline of pilot 2.2.1, Easy data sharing and networking



Pilot 2.2.2: Monitoring and control tools for

forest owners 4.1 Pilot overview


This pilot aims to develop standardized procedures and apps for forest owners for collecting,

monitoring and transferring data utilizing the Wuudis Service and the DataBio platform. The

Wuudis Monitoring feature is applied in the pilot; see section 2.3.1 for introduction on

Wuudis. This data can be exported to third party IT systems through standard interfaces. In

this pilot, an end-to-end data transfer solution will be developed between the Wuudis Service

and METSAK´s metsaan.fi eService.

In the DataBio project, selected Big Data partners will integrate their existing market-ready

or almost market-ready technologies onto the Wuudis Service and the resulted solutions will

be piloted with the Wuudis users, forestry sector partners, associated partners and other

stakeholders such as NGOs and authorities related to nature conservation. This integration

also applies to the pilot 2.4.2: Shared multiuser forest data environment in WP2.

This pilot is developed in Task 2.2.2 Monitoring and control tools for forest owners, under

WP2 Forestry pilot and Task 2.2 Multisource and data crowdsourcing /e-services. The involved

partners are MHGS, FMI, METSAK and TRAGSA.


Forest damage (such as storms, snow, pests and diseases) monitoring through standardized

procedures will be developed together with METSAK, as well as easy-to-use mobile tools for

these damage monitoring needs and non-wood product monitoring needs. Finally, the data

will be integrated with METSAK´s metsaan.fi eService. This allows forest owners and forest

specialists willing to monitor and report forest damage information to authorities a direct

access to metsaan.fi’s master database.

The Finnish Forest Centre will launch a campaign in 2017 targeted at private forest owners

and forest specialists to collect and report observations from forest damages through the

Wuudis app seamlessly interfacing with metsaan.fi’s eService. Similar monitoring service will

be implemented and tested in Czech Republic in the third year of the DataBio project with

FMI.

WWF Finland and numerous private forest owners strive to manage their forests favouring

multiple use and high biodiversity values. WWF Finland has an ongoing campaign targeted at

private forest owners to collect data from high nature value sites and other important flora

and fauna that forest owners want to preserve in coming care work activities and harvesting

operations. This campaign, called “Forest Challenge”, aims to secure biodiversity of forest

nature. WWF has launched a guidebook to illustrate measures to preserve biodiversity. All

contracting and timber buying committed to the challenge promise to respect the measures



described in the guidebook of WWF Finland. In this pilot, a database and communication

procedure will be further developed on the Wuudis Service for supporting Forest Challenge´s

objectives together with WWF Finland pilot users.

Table 9: Summary of pilot 2.2.2: Monitoring and control tools for forest owners (ISO JTC1 WG9 use case template)

Use case title Monitoring and control tools for forest owners




responsibilities

Forest owners and forestry operators as Wuudis Service users. The Wuudis (MHGS) admin users who use and refine the forest resource data and make it available for Wuudis users.

Goals To increase the use of Wuudis freemium and commercial Services and in parallel the use of METSAK’s forest resource data.

Use case description Specifying the requirements for forest damage data and non-wood data collection through Wuudis apps to Metsään.fi’s eService and implementing them in collaboration with Metsään.fi’s development team and other METSAK projects. Developing forest damage and non-wood monitoring app (Microsoft, iOS, Android mobile platforms), further developing networking features for the Wuudis service in order to interface with marketplaces.

Current solutions



Networking Web based and mobile solution for Wuudis and Metsään.fi users




Mobile data service, modern smart phone/tablet, web browser, open API to the authority and 3rd party systems



Real time updates from field measurements, quality control, forest owner’s forest management plans and other notifications from forest owners



and forestry operators and other stakeholders


mashup)




analysis, action)




Data quality (syntax) Collected forest damage and non-wood product data must be consistent with the specific standards.

Data types Tree stand basic data and strata data, growth place data (site quality), location data, time and user stamps.

Data analytics


To balance between data publicity and privacy, to adapt to the new Finnish Forest Act being revised at the moment and to take into account Wuudis service users, public authorities’ and Metsään.fi’s eService user needs.


economy

To maintain the consistency of data and the usability of new data, functionalities and services from the Wuudis service user point of view to support better clients´ forest related business development and decision making, and therefore bio-economy.


There are both public and private data in the Wuudis Service. Personal and forest estate specific information are private. National Forest Acts set demands on data publicity and privacy issues.









This pilot aims to solve the following needs/problems as a Wuudis user:

1. Share data/information and communicate easily between different stakeholders

with mobile and web application.

2. Different kinds of forest damages will be monitored in real time operations through

a mobile application to be defined and built up.

3. Forest owners are able to monitor different kinds of damage and share the data with

authorities/forest experts for consultation and reporting through a mobile app.

4. Service providers/contractors/timber buyers are able to monitor different kind of

damages and share the data with authorities/forest experts for consultation and

reporting through a web service.

5. All monitoring data has to be integrated with the authority databases through

standardized procedures. A specific standard for forest damage monitoring will be

developed in the pilot.

6. Forest authority experts are able to use a specific app for biodiversity monitoring

(instead of paper sheets or user-unfriendly solutions).



Table 10: Stakeholders and user stories of pilot 2.2.2: Monitoring and control tools for forest

owners

Who I want to Why

Forest

owner

I want to report damage (with pictures,

video & positioning) easily with a mobile

application to authorities

I want to share damage (with pictures,

video & positioning) easily with a mobile

application to my contracting

company/timber buyer

I want to get a situation view through an

easy-to-use and cost-effective web service

I want damage monitoring reports to

integrate with the authority’s central

database

I want damage monitoring reports to

integrate with the 3rd party’s database

I want the service to offer me

guidance/advice about what should be

done in my forest

I want to receive an alert on my mobile or

tablet

To get consultancy about the damage

and how to treat it to avoid further risks

To get injured trees harvested as soon

as possible

It´s important for me to know that my

forest property is doing well

To maintain my forest data updated in

the authority service

It´s important for me to electronically

share information with my contractor

and timber buyer

It´s important for me to know and be

prepared for further harvesting needs in

order to prevent further damages

(fungi, insects).

To be aware of the probability of a

damage occurring in my forest and I

want to receive an indication of the

level of probability



Forestry

contractor

I want to easily share forest estate data

with the forest owner

I want to easily receive forest data to my


I want to report my work in details and

easily

I want to get detailed information about

damaged sites/compartments

I want to network with my subcontractors

I want to receive on my mobile or tablet an

alert if a probability that a damage occurs

in the forest I’m working on exists

To provide a superior customer service

to my clients

To conveniently receive the forest data


or tablet

To provide a superior, real-time

customer service to my clients

To win deals thanks to the availability of

precise data and to better manage

available machine and operator

resources

To outsource part of my deals by having

tools for smooth networking with my

subcontractors

To be ready to act as soon as possible

and I want to receive an indication of

the level of probability

Timber

buyer

I want to receive forest data easily

I want my contractors to do top quality

harvesting operations and report to forest

owners and my supervisors


purchase targets with less expenses

To conveniently receive the forest data


or tablet

For customer satisfaction, it is

important to report to forest owners

and my supervisors. In addition, the

reporting method must interface with

our IT system

To close deals with less expenses by

understanding better in-site /

compartment level available tree

species, timber quality, assortments etc.



Forest

authority

expert

I want damage monitoring reports to be



I want to report work damage inspections

easily and in a reliable manner through a

mobile application

I want to report biodiversity features easily

and in a reliable manner through mobile

application

I want to better define the places for field

visits

I want to be able to detect infections in

early stages so that I can apply control

measures before they spread



To use my standard interface or

smartphone as a reporting tool because

I take care of daily routines like banking

through apps

To use my standard interface or

smartphone as a reporting tool because

I take care of daily routines like banking

through apps

To be efficient and focus on most risky

sites in the field inspections, to

concentrate efforts and save costs [KPI]


as possible if something unusual

happens in the forest, in order to

prevent additional damages while

ensuring e.g. harvesting operations

Forest

insurance

company

I want to access damages produced by e.g.

storm, insects, fungi

To quantify economic losses for

compensation payment in a cost-

efficient way

MHG

service

provider

I want to provide real time monitoring

services

To provide a superior, real-time

customer service to my clients

interfacing with the authority service,

unlike my competitors


New features will be delivered and deployed continuously. All new bigger features are split

into small parts to enable fast deployment and testing cycles. The most important thing is to



production environment, the features are ready for the DataBio pilot case to be tested in

practical operations by committed Wuudis users, WWF Finland users, associate partners and

other possible Wuudis users.



The key advantage is that forest contractors can better respond to forest owners and

authority expectations about work quality in regards with biodiversity and nature

conservation, and plan and execute harvesting operations as soon as possible after significant

forest damage occurred. Forest owners and timber buyers are able to guide and give

instructions to contractors remotely through the Wuudis Service and follow the quality of

harvesting operations performed in the forests and, in the meantime, get real time updates

for forest management plans.

Wuudis users are able to update the forest resource data not only on the Wuudis Service but

on Metsään.fi’s eService too, providing better customer service and satisfaction than


service provider with such a complete service package in the market interfacing with the

authority database.


This pilot operates in an existing service environment of MHGS producing new data and

functionalities related to the Wuudis Service. The pilot scope is to:

- develop forest damage monitoring app seamlessly interfacing with METSAK´s

metsään.fi eService

- test the app in the field operations with associate partners and other stakeholders

The limitations in this pilot may be caused by:

- Ongoing standardization process regarding forest damages

- Operating in METSAK’s system environment and its development: this sets both

content and schedule limitations when specifying and testing changes in Metsään.fi.

- The forest data standard: all the forest data interfaces must be consistent with the

forest data standard.

4.3 Pilot modelling with ArchiMate In this pilot, there is an existing technical environment of the Wuudis Service. Any data

modelling or architecture design is done by MHGS´s internal Wuudis development team. Pilot

modelling in this section is therefore applicable to this pilot to limited extent only.

This section presents the "Forestry A2 Monitoring and control tools for forest owners

modelling with ArchiMate" viewpoints described using the ArchiMate standard.


Figure 19 describes the "Forestry A2 Motivation view" defined in the "Forestry A2 Monitoring

and control tools for forest owners modelling with ArchiMate" view point.



Figure 19: Forestry A2 Motivation view

The goal “Real-time monitoring of different forest damages” is further explained by this

description: “Different kinds of forest damages will be monitored in near real-time operations

through the RS service to be defined and interfaced with Wuudis.”

Figure 20 describes the "Forestry A2 Forest owner Motivation view" defined in the "Forestry

A2 Monitoring and control tools for forest owners modelling with ArchiMate" view point.

Figure 20: Forestry A2 Forest owner Motivation view




Figure 21 describes the "Forestry A2 Strategy view" defined in the "Forestry A2 Monitoring

and control tools for forest owners modelling with ArchiMate" view points.

Figure 21: Forestry A2 Strategy view

The goal “Real-time monitoring of different forest damages” is further explained by this

description: “Different kinds of forest damages will be monitored in near real-time operations

through the RS service to be defined and interfacing with Wuudis.”

Figure 22 describes the "Forestry A2 Forest owner Strategy view" defined in the "Forestry

A2 Monitoring and control tools for forest owners modelling with ArchiMate" view points.



Figure 22: Forestry A2 Forest owner Strategy view



4.4 Big Data infrastructure: Components and BDVA classification The existing technical environment of the Wuudis Service concerning big data is described in

Figure 23. This pilot is about further development of the Wuudis Service features in order to

better serve all its customers and partner groups: forest owners, contractors, timber buyers

and authorities.

Figure 23: Big data components and assets in pilot 2.2.2: Monitoring and control tools for forest owners







cases in forestry operations. These will be identified, specified and agreed with piloting clients

in business practicalities during the project.

Some of the KPIs in this pilot are as follows:

● %decrease in damages in high biodiversity site following the networking e-tools

available/developed for communication and monitoring vs. what would be damage

level based on working instructions on paper documents and paper maps

○ Quantify %decrease in damages.

● %Increase customer satisfaction following the networking e-tools

available/developed vs. what would be the satisfaction following standard

communication practices based on contractor's present practicalities (phone, SMS,

work quality report if any)

○ Quantify %increase in satisfaction for example for high biodiversity stand

harvesting work quality reporting (contractor and forest owner).

● %decrease in costs following the monitoring tools available/developed for

monitoring and reporting vs. what would be costs based on monitoring and

reporting practices currently

○ Quantify %decrease in costs.

● The amount of forest owners and other users as Wuudis Service users is now around

2 700. The amount is expected to increase as follows: 5 000 in the end of 2017, 10

000 in the end of 2018 and 50 000 in the end of 2019.

The final KPIs will be specified and selected later on based on study cases agreed with

associate partners and other stakeholders.

4.6 Initial roadmap The goal of this pilot is to develop and test the forest damage monitoring service to Wuudis

and integrate reported forest damage data to the authority service, Metsaan.fi’s eService.

The Wuudis mobile app will be used as a reporting tool of various forest damages (Figure 24).

The Wuudis mobile app includes all important forest data, maps and geolocation. The Wuudis

mobile app runs on Windows 10 Mobile, Apple iOS, as well as Android smartphones and

tablets.

The implementation process for the app will go on in sprint cycles:

1. Specify

2. Develop

3. Test

4. Deploy






Figure 24: Wuudis mobile app for observation reporting


production environment, the features are ready for the DataBio pilot.

The Wuudis implementation plan for this pilot is presented in the following:

1. Wuudis mobile app development: Extend the observation feature to support all kind

of damage reporting

2. Specify and implement a visibility model for the damage reports

3. Export damage report data in a standardized format supported by and compatible

with authority systems

4. Data interface/integration development

5. Evaluate implementation with real end users



All Wuudis Service forest resource data are saved in a centralized forest resource data system.

The Wuudis Service uses that data through a publishing database and other existing

interfaces.

The Wuudis app expansion with damage reporting features will be developed and

implemented (Q1/2018), piloted and feedback collected (Q2-Q3/2018) for further

development of the platform (Q3/2018). The complete implementation schedule is described

in Figure 25 below. It is partially dependent on the schedule of Metsään.fi’s standardization

progress regarding forest damage monitoring and the development plan timeframe.

Figure 25: Timeline of pilot 2.2.2, Monitoring and control tools for forest owners



Pilot 2.3.1: Forest Damage Remote Sensing 5.1 Pilot overview


The goal of this pilot is to develop a Forest Inventory system for damage identification on the

Wuudis Service based on remote sensing (satellite, aerial, UAV) and field surveys. The Wuudis

Monitoring feature is applied in the pilot; see section 2.3.1 for introduction on Wuudis. In the

DataBio project, selected Big Data partners will integrate their existing market-ready or

almost market-ready technologies onto the Wuudis Service and the resulted solutions will be

piloted with the Wuudis users, forestry sector partners, associated partners and other

stakeholders. This integration also applies to the pilot 2.4.2 Shared multiuser forest data

environment in WP2.

This pilot is developed in Task 2.3.1 “Forest damage remote sensing”, under WP2 Forestry.

The involved partners are MHGS, VTT, SENOP, METSAK and SPACEBEL.


Earth Observation (EO) data from multispectral optical aerial, unmanned aerial vehicles (UAV)

and satellite sensors present the optimal way to timely collect information on land cover over

areas of various sizes. Particularly the availability of the Copernicus Sentinel-2 data and the

applicable data policy present a great opportunity for developing low cost commercial

applications of EO downstream services in monitoring of the environment.

In parallel, FMI is developing a new methodology for forest health assessment based on

Copernicus satellite data focusing on technological development of the processing of

Sentinel-2 optical and Sentinel-1 radar data. This allows us to assess the forest health of the

entire area of Czech Republic. In addition, the forest owners will benefit from publicly

available map servers and implementation of the layers on the Wuudis platform, where all

forest health status maps will be published to allow proactive management of their forest

properties.

Forest damage (from e.g. storms, snow, pests and diseases) monitoring standardized

procedures will be developed together with METSAK as well as easy-to-use RS-based tools

and services for the damage monitoring needs of various stakeholders, and finally the data

will be integrated with METSAK´s metsaan.fi eService. However, these activities are partially

dependent on further funding through a “Spearhead project” with national funding support,

managed by METSAK.

The pilot aims to develop a comprehensive and near real-time quantitative assessment of

forest cover, forest aboveground carbon stock and carbon stock change over the project pilot

area (Rangunkorpi cooperative forestry). This allows detecting and measuring damages,

deforestation and forest degradation, which is a major cause of loss of biomass and carbon

stores. The data collected will provide a comprehensive and near real-time quantitative

assessment of forest vegetation indexes and monitoring spatial changes related to forest



degradation and deforestation over the project pilot areas. A challenging aspect is the

integration of numerous heterogeneous data sources into distributed systems. This is a

prerequisite for genuinely exhaustive information systems for strategic management.

Figure 26: Pilot foresty, Rangunkorpi cooperative foresty, on the Wuudis service

For easy integration of satellite maps and analysed (highlighted) theme maps, standard WMS

or WMTS interfaces will be used. The Wuudis Service is using OpenLayers 3/4 as the mapping

client library. For the phase I development Wuudis needs all the data provided in a ready to

use format (for the end users), so no calculations need to be done in the Wuudis platform.

Wuudis will just serve as a user interface for the end users and display specific important

information provided by the Remote Sensing (RS) services. All the developed RS map layers

should be available in the Wuudis web UI and in the Wuudis mobile app.

Table 11: Summary of pilot 2.3.1 Forest Damage Remote Sensing (ISO JTC1 WG9 use case

template)

Use case title Forest Damage Remote Sensing






responsibilities

Forest owners and forestry operators as Wuudis Service users. The Wuudis (MHGS) admin users who use and refine the RS- and forest resource data and make it available for Wuudis users.

Goals To increase the use of Wuudis freemium and commercial Services in Finland and piloting countries, Belgium and Czech Republic.

Use case description Specifying the requirements for forest damage collection through the Wuudis Service to Metsään.fi eService and implementing them in collaboration with the Metsään.fi development team and other METSAK projects. Developing forest damage monitoring services for the Wuudis service in order to interface with marketplaces.

Current solutions



Networking Web-based and mobile solution for Wuudis and Metsään.fi users




Mobile data service, modern smartphone/tablet, web browser, open API to the authority and 3rd party systems



Near real time updates from remote sensing services and other notifications for forest owners and other stakeholders


mashup)




analysis, action)






Data quality (syntax) Collected forest damage and other inventory data should be consistent with the specific standards.

Data types Tree stand basic data, tree stand strata data, growth place data (site quality), location data, time stamps.

Data analytics


To take into account Wuudis service users, public authorities’, marketplaces´, and Metsään.fi eService users’ needs.


economy

To maintain the consistency of data and the usability of new data, functionalities and services from the Wuudis service user point of view to support better clients´ forest related business development and decision making, and therefore bio-economy.


There are both public and private data in the Wuudis Service. Personal and forest estate specific information through authority sources like metsaan.fi eService are private.




NOTEs - Spacebel: The Wuudis service will be integrated in the EO Regions! multi-thematic EO services platform in Wallonia. The forestry services developed in the framework of the EUGENIUS projects will reciprocally be integrated in the Wuudis service for the Finnish market.

- Development of features for strategic planning in order to promote forest property management and timber sales (automated alarms, request for automated bidding, group sales etc.)



This pilot aims to solve the following needs/problems as a Wuudis user:

1. Share data/information and communicate easily between different stakeholders

with a mobile and web application.

2. Different kinds of forest damage will be monitored in near real-time operations

through RS-services to be defined and interfacing with Wuudis.

3. Forest owners, service providers/contractors, timber buyers, authorities and other

end-users are able to monitor different kinds of damages and share the data for

consultation and reporting through a web service.

4. Near real-time situation view from forest estate (RS-service integrated with Wuudis)

guides forest owners to make decisions for harvesting of damaged/contaminated




timber in time thus preventing further expansion of insect damages, for example.

Also harvesting operations after storm damage should take place immediately to

avoid fungi attack (saw logs) and a couple of months later (coniferous biomass) to

prevent insect invasion and damages.

5. The service is grouping forest owners having damages in their forest, asking

permission for timber sales tendering, and enabling efficient group sales of timber in

damage areas to prevent further insect/fungi spoilage.

Table 12: Stakeholders and user stories of pilot 2.3.1 Forest Damage Remote Sensing

Who I want to Why

Forest

owner

I want to get a situation view on my

forestry through an easy to use and cost

effective web service

I want to share damage observations

easily to my contracting company/timber

buyer


integrated with the authority central

database


integrated with the 3rd party database

I want the service to offer me guidance

about what should be done in my forest

regarding harvesting needs in order to

prevent further damages (fungi, insects).

I want to receive on my mobile or tablet

an alert if a probability that a damage

occurs in my forest exists and I want to

receive an indication of the level of that

probability

To know that my forest property is doing

well

To act as soon as possible after any

damage to prevent further injuries

To maintain my forest data updated

It´s important to me to electronically

share information with my contractor and

timber buyer

It´s important to me to know and be

prepared for further harvesting needs in

order to prevent further damages (fungi,

insects).

To be aware of probability that a damage

occurs in my forest and I want to receive

an indication of the level of that

probability



Forestry

contractor

I want to share forest estate data with

the forest owner easily



I want to report my work in details and

easily

I want to get detailed information about

damaged sites/compartments in order to

better manage available machine and

operator resources

I want to network with my

subcontractors

I want to receive on my mobile or tablet

an alert if a probability that a damage

occurs in the forest I’m working on exists

and I want to receive an indication of the

level of that probability

To provide a superior customer service to

my clients

To receive conveniently the forest data to

my standard interface, smart phone or

tablet

For better profit and less work

without principals and middle men

To win deals thanks to precise data

available for cost analysis

To outsource part of my deals by

networking smoothly with my

subcontractors

I want to be ready to act as soon as

possible to win deals in any business

environment

Timber

buyer



I want my contractors to do top quality

harvesting operations and report to

forest owners and my supervisors

interfacing with our IT system


purchase targets with less expenses

To receive conveniently the forest data to

my standard interface, smart phone or

tablet

For customer satisfaction, it is important

to report to forest owners and my

supervisors. In addition, the reporting

method must interface with our IT system

To close deals with fewer expenses,

understanding better in site /

compartment level the available tree

species, assortments, etc.

To develop and implement new business

practices with minimum paperwork to

become more cost efficient



Forest

authority

expert




I want to report work damage

inspections easily and in a reliable

manner through mobile applications

I want to better define the places for

field visits so that I can concentrate

efforts and save costs [KPI]

I want to be able to detect infections in

early stages so that I can apply control

measures before they spread



To use my standard interface or my

smartphone as a reporting tool because I

take care of daily routines like banking

through apps

To be efficient and focus on most risky

sites in the field inspections, to

concentrate efforts and save costs [KPI]


as possible if something unusual happens

in the forest in order to prevent

additional damages while ensuring e.g.

harvesting operations

Forest

insurance

company

As an end user, I want to access damages

produced by e.g. storm or insects so that

I can cost efficiently quantify economic

losses for compensation payment

To quantify economic losses for

compensation payment in a cost-efficient

way

MHG

service

provider

I want to provide real-time monitoring

services

To provide a superior, real-time customer

service to my clients interfacing with the

authority service unlike my competitors



small parts to enable fast deployment and testing cycle. The most important thing is to



production environment, these features are ready for the DataBio pilot case to be tested in

practical operations by committed Wuudis users, associate partners and other possible

Wuudis users. In Wallonia, FMI, with the support of Spacebel, aims to develop a remote

sensing service to provide a spatial distribution of the vulnerability and risk exposure to

diseases and other potential hazards and Sentinel-2 or S1+S2 identification of most vulnerable

areas, identification of dominant risk factors in forest. In addition, an integration of the

Wuudis service with EO Regions! is planned to expand the market of Wuudis to Wallonia.



As underlined by FMI, the forest owners will benefit from publicly available map servers and

implementation of the layers in the Wuudis Service, where all forest health status maps will

be published to allow pro-active management of their forest properties.

The key advantage is that timber buyers and forest contractors can better respond to

harvesting needs of vastly damaged forest sites through smooth monitoring, networking,

communication and the bidding system of the Wuudis Service and its market place.

Wuudis users are able to update the forest resource data not only on the Wuudis Service but

also to the Metsään.fi eService, thus providing better customer service and satisfaction than


service provider with such a complete service package in the market.


The scope of the pilot extends to provide a useful tool on the Wuudis Service for accurate

monitoring forest cover and forest damages caused by storms and insects for example.

Limitations that could be encountered are:

● Technical difficulties for accessing different data sources

● Technical difficulties derived from managing big volumes of data

● Technical difficulties derived from managing many different data sources and

formats, with different spatial resolution and precision

5.3 Pilot modelling with ArchiMate Any data modelling or architecture design is done by MHGS´s internal Wuudis development

team. Pilot modelling in this section is applicable to this pilot to limited extent only.

This section presents the "Forestry B1 Forest damage remote sensing modelling with



Figure 27 describes the "Forestry B1 Motivation view" defined in the "Forestry B1 Forest

damage remote sensing modelling with ArchiMate" view point. The three assessments in the

view are explained via the KPIs in section 5.5.1. A number of other elements in the view are

further explained in Table 13.



Figure 27: Forestry B1 Motivation view

Table 13: Explanation of specific elements in the Forestry B1 Motivation view

Name Description

Goal: Easy data

sharing between

stakeholders

Share data/information and communicate easily between different

stakeholders with mobile and web application.

Goal: Near real

time situation view

from forest estate

Near real time situation view from a forest estate (RS service integrated

with Wuudis) guides forest owners to make decisions for harvesting of

damaged/contaminated timber in time preventing further expansion of for

example insect damages. Also harvesting operations after storm damage

should take place immediately to avoid fungi attack (saw logs) and a couple

of months later (coniferous biomass) to prevent insect invasion and

damages.

Goal: Real-time

monitoring of

different forest

damages

Different kind of forest damages will be monitored in near real time

operations through RS-services to be defined and interfacing with Wuudis.

Stakeholder:

Wuudis user

The amount of forest owners and other users as Wuudis Service users is

now around 2 700. The amount is expected to increase as follows: 5 000 in

the end of 2017, 10 000 in the end of 2018 and 50 000 in the end of 2019.




Figure 28 describes the "Forestry B1 Strategy view" defined in the "Forestry B1 Forest damage

remote sensing modelling with ArchiMate" view point. A number of elements in the view are

further explained in Table 14.

Figure 28: Forestry B1 Strategy view

Table 14: List of the elements defined in the Forestry B1 Strategy view

Name Description

Action: Provide real

time situation view

from forest estate

Near real-time situation view from a forest estate (RS service integrated

with Wuudis) guides forest owners to make decisions for harvesting of

damaged/contaminated timber in time preventing further expansion of for

example insect damages. Also harvesting operations after storm damage

should take place immediately to avoid fungi attack (saw logs) and a couple

of months later (coniferous biomass) to prevent insect invasion and

damages.

Forest damage

monitoring

Forest damage (like storms, snow, pests, diseases) monitoring standardized

procedures will be developed together with METSAK as well as easy-to-use

remote sensing based tools and services for the damage monitoring needs

of various stakeholders



Forest health

assessment

FMI is developing a new methodology for forest health assessment based

on Copernicus satellite data focusing on technological development of the

processing of Sentinel-2 optical and Sentinel-1 radar data.

Goal: Easy data

sharing between

stakeholders

Share data/information and communicate easily between different

stakeholders with mobile and web applications.

Integrated user

interface for map

layers

For the easy integration of satellite maps and analysed (highlighted) theme

maps, standard WMS or WMTS interfaces will be used. The Wuudis Service

is using OpenLayers 3/4 as mapping client library.

Invasion danger

index

TRAGSA is developing an “invasion danger index” (ecology + transit +

ecosystem disturbance) for mapping and setting up of an alert system for

early warning of risk presence.

Quantitative

assessment of forest

cover

The pilot will develop a comprehensive and near real-time quantitative

assessment of forest cover, forest aboveground carbon stock and carbon

stock change over the project pilot area.

Spatial risk

distribution

In Wallonia, FMI, with the support of Spacebel, aims to develop a remote

sensing service to provide a spatial distribution of the vulnerability and risk

exposure to diseases and other potential hazards based on Sentinel-2 or

S1+S2



5.4 Big Data infrastructure: Components and BDVA classification The existing technical environment of the Wuudis Service concerning big data is described in

Figure 29 below. This pilot is about further development of the Wuudis Service Set in order

to better serve all its customers and partner groups: forest owners, contractors, timber

buyers, authorities and other end-user like market places and insurance companies.

Figure 29: Big data components and assets in pilot 2.3.1 Forest Damage Remote Sensing







cases in forestry business operations. These will be identified, specified and agreed with

piloting clients in business practicalities during the project.

Some of the KPIs in this pilot are as follows:

● %Decrease in operational costs for performing the same contracting activities

(through accurate site information and better management of resources) following

the e-tools available/developed vs. what would be the revenue (per hour) following

current practices based

○ Quantify %Decrease in operational costs for example for harvesting

(contractor)

● %Increase customer satisfaction following the monitoring e-tools and services

available/developed vs. what would be the satisfaction following forest asset

monitoring practices based on forest owners present practicalities (forest

management plan (10 years interval) on paper or in electronic form in own/authority

IT systems)

○ Quantify %increase in satisfaction for example for forestry level reporting

(forest owner)

● %decrease in costs following the monitoring tools available/developed for

monitoring and reporting vs. what would be costs based on monitoring and

reporting practices currently

○ Quantify %decrease in costs (authority and/or insurance company?)

● The amount of forest owners and other users as Wuudis Service users is now around

2700. The amount is expected to increase as follows: 5 000 in the end of 2017, 10

000 in the end of 2018 and 50 000 in the end of 2019.

The final KPIs will be specified together with relevant stakeholders based on study cases to

be selected later on.

Big Data methods bring the possibility to both increase the value of the forests as well as to

decrease the costs within sustainability limits set by natural growth and ecological aspects.

The key technology is to gather more and more accurate information about the trees from a

range of sensors including new generation of satellites, UAV images, laser scanning, mobile

devices through crowdsourcing and machines operating in the forests. This enables a

characterization of even single trees, not to mention accurate monetary value of the forestry.

5.6 Initial roadmap The goal of this pilot is to develop, visualize and test forest damage monitoring services made

available through the Wuudis Service.



Wuudis implementation plan for this pilot proceeds as follows:

1. Specify and develop needed map layers with partners (SPACEBEL, FMI)

2. Integrate those map layers with Wuudis web UI and Wuudis mobile app

3. Gather all data available and show it on the user interface

4. Evaluate usability in the pilot



prioritize and understand these development requirements correctly first. After the

developed features are tested by the development team and deployed to the production

environment, the features are ready for the DataBio pilot case.

The first components of the forest damage RS service will be implemented and integrated in

Q1/2018. Feedback will be collected from field users, analyzed and used for development of

the second version of the platform in Q2-Q3/2018. A more detail roadmap is given below in

Figure 30.

Figure 30: Timeline of pilot 2.3.1, Forest damage remote sensing



Pilot 2.3.2-FH: Monitoring of forest health 6.1 Pilot overview


Spain has to face alarming situations due to several pests which are big threats affecting the

health of very important species in the Iberian Peninsula, among others: Quercus ilex, Quercus

suber and Eucaliptus sp.

Spanish Public Bodies and forest owners need updated information about the health status

of forests to be able to perform sustainable forest management. The optimal combination of

different EO data, together with field data, will provide new products for monitoring, and

effective tools for decision-making, with a good balance between success and cost of

detection. Tools need to be very adapted to user requirements and needs. All this will result

in improved forest management.

In the DataBio project, Big Data partners will integrate their existing market-ready or almost

market-ready technologies to the forest databases and new datasets obtained by processing

state of the art Remote Sensing products. The resulted solutions will be piloted with the

forestry sector partners, with associated partners and other stakeholders. Final users affected

(policy makers, public administration, forest owners) will be involved in the pilot. The main

aim of this pilot is fully aligned with pilots 2.2.2 and 2.3.1. Therefore, this integration applies

to the pilot 2.2.2: Monitoring and control tools for forest owners and pilot 2.3.1: Forest

damage remote sensing in WP2.


The goal of this pilot is to set up a methodology based on remote sensing images (satellite +

aerial + UAV) and field data for the monitoring of the health status of forests in large areas of

the Iberian Peninsula. The work will focus, particularly, in the monitoring of the health of

Quercus sp. forests affected by the fungus Phytophthora cinnamomi Rands and of the damage

in eucalyptus plantations affected by the coleoptera Gonipterus scutellatus Gyllenhal.

6.1.2.1 Monitoring of the health of Quercus sp. forests affected by the fungus Phytophthora

cinnamomi Rands

Main user: JUNTA DE EXTREMADURA – CICYTEX

Current situation: Phytophthora cinnamomi affects very severely several tree species, among

them Quercus ilex and Q. suber, in different areas in Spain (Extremadura, Andalucia, Castilla

y León, Castilla La Mancha, Madrid), causing a great ecological and economic problem.

Detection is currently performed through direct observations or through data sampling and

analysis in the laboratory.



Pilot solution: The pilot aims at developing EO-based monitoring tools at different scales:

• Orthophotos (RGB + NIR) will be used to identify dead trees from different dates and locate possible affected areas of Quercus forests, as well as their evolution. Sampling plots will be selected in those areas.

• Detailed RPAS (RGB + multispectral + thermal sensors) and field data will be collected in the selected sampling plots and analysed (in-situ or in the lab); RPAS will be employed for intensive monitoring of affected and control areas, to establish the relationships between satellite-derived indexes (from multispectral images) and biophysical parameters from field data, and select the most adequate parameters to be measured, as well as the optimal spatial resolutions and sensors for an effective monitoring.

• A more general health status monitoring for big areas of Quercus forests could be developed based on satellite-derived Vegetation indices using freely distributed Sentinel 2/Landsat 8 data. Ancillary information about environmental conditions and management would be combined with EO data to detect areas under stress and, consequently, more prone to be affected by Phytophtora and/or other plagues and diseases.

All the information will be combined and analysed to:

• define an optimal methodology for data acquisition and analysis

• develop efficient tools for health status monitoring at different spatial, temporal and economic levels.

• optimize efforts by focusing resources (intensive monitoring and field work) on the most affected / vulnerable areas and on those that show anomalies in their evolution.

Key problem-solving capacity: EO-based solutions will provide Public Bodies with valuable

information and tools to help decision-making. An EO-based system for monitoring the health

of big forest areas will be set up (mapping + assessment tools), so authorities will be able to

optimise forest management resources.

6.1.2.2 Monitoring of the damage in eucalyptus plantations caused by the coleoptera

Gonipterus scutellatus Gyllenhal

Main users: XUNTA DE GALICIA & ENCE

Current situation: Gonipterus scutellatus defoliates eucalyptus plantations very severely.

Eucaliptus is one of the main commercial species in the North of Spain (Galicia, Asturias and

Cantabria), where Gonipterus produces huge economic losses by impeding the development

and growth of trees. Authorities (Xunta de Galicia), industrial companies from the paper

sector (ENCE) and forest owners need an economic, systematic and objective tool for affected

areas identification and damage assessment.

Pilot solution: Sentinel 2-derived vegetation indices will be used for a systematic monitoring

(weekly) of the health status in the selected study areas; anomalies will show areas where



Gonipteurs can be defoliating, which will be checked on the field, either visually or using RPAS.

This information will be combined to define an optimal methodology for data acquisition and

analysis. The rate of defoliation that can be detected must be analysed and established for

different EO data.

Key problem-solving capacity: A mapping and assessment tool will be developed for

monitoring the damages caused by Gonipterus in eucalyptus plantations, as well as for

damage assessment, in order to adapt management and minimise economic losses.

Table 15: Summary of pilot 2.3.2-FH: Monitoring of forest health (ISO JTC1 WG9 use case template)

Use case title Pilot 2.3.2-FH: Monitoring of forest health


Author/company/email

Asunción Roldán & Jesús Estrada / TRAGSA Group [email protected] & [email protected]


responsibilities

Actors / roles:

- Final Users (public administrations, policy makers, forest

companies, forest owners) / define users’ needs and requirements;

validate the new products and services.

- Forestry Technicians and developers from Tragsa Group / develop

EO-based tools and methodologies

Goals Set up a methodology (satellite + aerial + UAV + field data) for the monitoring of pests affecting forests (Phytophthora cinnamomi Rands affecting Quercus ilex and Q. suber) and Gonipterus scutellatus Gyllenhal affecting Eucaliptus plantations.

Use case description

Refer to the pilot case definition section and diagrams in the pilot modelling sections

Current solutions

Compute(System) Dedicated server 2 processors Intel(R) Xeon(R) CPU E5606 @ 2.13GHz, 8 cores, with 96 GB ECC of Memory

Storage Dedicated server Hard Disks: 2 disks - 2 TB (RAID). Total: 2 TB

Networking 250 MBps

Software OS: Debian 8.8 Apache web server 2.4.10 Tomcat: 7.0.56 and 8.0.14 R: 3.3.3. PostGres: 9.4 MySQL: 5.5.55 Python: 2.7.9 Virtuoso: 07.20.3212




Data source (distributed/centraliz

ed)

Combination of both types: Centralized: Remote sensing data such as Sentinel 2A and 2B data provided by ESA at Sentinel Data Hub (https://cophub.copernicus.eu/) Orthophotos (Spanish Coverage). RGB and NIR bands provided by Spanish National Geographic Institute at http://centrodedescargas.cnig.es/CentroDescargas/catalogo.do Surveys and field data: Direct observations and lab measurements as Chlorophyll content, morphology, green and dry weight, hydric potential, leaf area index, visual classification of damages or other features according to pilot needs Spanish Forestry Map (MFE50) on forest types and forest status (scale 1:50.000) available at http://www.mapama.gob.es/es/biodiversidad/servicios/banco-datos-naturaleza/informacion-disponible/mfe50_descargas_comunidad_madrid.aspx Likely, GEOSS open sources available at GEOSS portal (http://www.geoportal.org) will be used as testing and validation data Distributed/local: LPIS system is provided in a distributed way by NUTS2-Level Administration. TRAGSA Drones produce JPEG and LAS files using thermal and multispectral sensors. More information is available in the DataBio deliverable D6.2 – Data Management Plan

Volume (size) Remote sensing data such as Sentinel 2A and 2B have an average size of tens of TB per year over pilot zone. The Spanish LPIS system has a size of hundreds of Gigabytes, likewise for the Spanish Orthophoto project (PNOA). MFE50 weighs several megabytes in the ESRI Shapefile format. TRAGSA Drones produce information (TB per year) on demand. Field data information has a size of MB per year.


Sentinel 2A and 2B have the highest revisit within the Pilot’s data sources (5 days). All external sources have several-years updating ratio.


mashup)

The formats to be used will be imagery, digital terrain models and ESRI Shapefiles for vector information.

Variability (rate of change)

Forestry information, typically, depends on seasons. Highest variability rate is some months (4-6)

Big data science (collection,

curation,


All data sources are official and trusted ones: European Space Agency (ESA) and Spanish Public Administration.

https://cophub.copernicus.eu/

http://centrodedescargas.cnig.es/CentroDescargas/catalogo.do




http://www.mapama.gob.es/es/biodiversidad/servicios/banco-datos-naturaleza/informacion-disponible/mfe50_descargas_comunidad_madrid.aspx




http://www.geoportal.org/



analysis, action)

Visualization Standard imagery visualization services. Spanish Public Administration usually provides WMS services for information visualization.

Data quality (syntax) Even though the data providers are supposed to produce good quality information, all datasets are processed by TRAGSA to produce improved images. Specifically, orthophotos will be transformed by an orthorectification method developed under WP5.

Data types TIFF or JPEG for images, .LAS for terrain models. Text document for surveys and field data.

Data analytics EO-based solutions will provide Public Bodies with valuable information and tools to help decision-making. This EO-based system for monitoring the health of big forest areas will be set up to optimize forest management resources concerning specific diseases and plagues.


TRAGSA Group is currently able to process, manage and submit results about a high number of forestry parcels. Processes will be scaled to provincial, regional and national levels.


economy

TRAGSA Group is currently able to process, manage and submit results about a high number of forestry parcels. With regard to forestry surfaces, the initial aim is to process two study sites (one for each pest - variable surface depending on the affection of trees) in which field + RPAS data will be collected. Processes will be scaled to provincial/regional levels, taking into account a multi-temporal approach.

Security and privacy technical

considerations

None of the datasets of this pilot are considered sensitive or related to personal data.

Highlight issues for generalizing this

Use case (e.g. for ref. architecture)

Main technical problems are related to data storage and resulting maps transmission.

More information (URLs)

ESA: https://sentinel.esa.int/web/sentinel/sentinel-data-access PNOA: http://www.ign.es/web/ign/portal/obs-portal-pnoa As auxiliary source of information, Possibly GEOSS platform could be used GEOSS: https://www.earthobservations.org/index.phphttps://www.earthobservations.org/index.php



The users involved in the pilot are:

- JUNTA DE EXTREMADURA – CICYTEX (Main user)

- XUNTA DE GALICIA (Main user)

https://sentinel.esa.int/web/sentinel/sentinel-data-access

https://sentinel.esa.int/web/sentinel/sentinel-data-access

http://www.ign.es/web/ign/portal/obs-portal-pnoa

http://www.ign.es/web/ign/portal/obs-portal-pnoa

https://www.earthobservations.org/index.php







- ENCE (Empresa Nacional de Celulosas) (Main user)

- MAPAMA - Ministry of Agriculture (Subdirección General de Sanidad e Higiene

Vegetal y Forestal de la Dirección General de Sanidad de la Producción Agraria)

- Other public administrations (Junta de Andalucía, Junta de Castilla y León, Junta

de Castilla La Mancha, Comunidad de Madrid, Principado de Asturias, Gobierno

de Cantabria).

- Forestry and environmental Technicians

Table 16: Stakeholders and user stories of pilot 2.3.2-FH: Monitoring of forest health

Who (type of user) I want to (perform some task) Why (to achieve some goals)

As an end user

(Junta de Extremadura)

I want to know the current status

of P. Cinnamomi distribution

To visualize updated maps

As an end user

(Xunta de Galicia)

I want to know the current status

of G. Scutellatus distribution


As an end user

(Xunta de Galicia)

I want to assess damages produced

by G. Scutellatus

To quantify economic losses

As an end user

(Public Administrations)

I want to accurately assess the

temporal evolution of forest health

To concentrate efforts and

avoid unnecessary field visits

As an end user


I want to better define the places

for RPAS visits


save costs

As an end user


I want to be able to detect

infections in early stages

To apply control measures

before they spread

As a TRAGSA Technician I want to produce and provide

updated Forest Health maps

To send them to customers

[Period to be defined]

As a generic user I want to use all standard GIS

features

To pan, change scales, go to

specific coordinates and places

and so on


The main motivations for this pilot are:

● to set up an optimised EO-based system for monitoring the health of Quercus ilex

and Q. suber forest areas (mapping + assessment tools), so authorities and forest

owners will be able to optimise forest management resources and decision making.



● to develop an efficient mapping + assessment tool for monitoring the damages

caused by Gonipterus in eucalyptus plantations, as well as for damage assessment, in

order to adapt management and minimise economic losses.

The pilot motivation and strategy is summarized using ArchiMate diagrams in the next

section, while goals and KPIs are addressed in the succeeding evaluation plan.


The scope of the pilot extends to providing final users with useful tools for the monitoring of

health of forests affected by Phytophthora or damages caused by Gonipterus, within a local

or regional geographical range.


● Difficulties for finding suitable filled sites (adequate conditions for RPAS + field

operations, representativeness, range of affection by pests etc.)

● Difficulties in performing RPAS + field operations (complex terrain, permissions etc.)

● Meteorological issues that can affect the acquisition of RPAS/satellite images and

field data

● Lack of correlation between EO-derived spectral information and biophysical

parameters measured on the ground.

● Possible interaction in the study area of other pests and diseases, as well as of

abiotic factors, in the study area that may interfere with the results obtained.

● The monitoring of damage caused by living organisms, especially in the case of

insects, is limited to a specific period of the year, more or less concrete depending

on its biological cycle and the climate conditions.

6.3 Pilot modelling with ArchiMate This section presents the "Forestry B1-FH Monitoring of forest health modelling with


6.3.1 DataBio forestry pilot 2.3.2-FH motivation view

Figure 31 describes the "Forestry B1-FH Motivation view" defined in the "Forestry B1-FH

Monitoring of forest health modelling with ArchiMate" view point. A number of elements in

the view are further explained in Table 17.



Figure 31: Forestry B1-FH Motivation view

Table 17: Explanation of specific elements in the Forestry B1-FH Motivation view

Name Description

Health of important species are

threatened

In the Iberian Peninsula, quercus ilex, quercus suber and

eucaliptus sp.

Monitor health of Quercus forests Monitor the health of Quercus forests affected by the

fungus Phytophtora cinnamoni Rands.

Monitor the damage of eucalyptus

plantations

Monitor the damage in eucalyptus plantations affected

by the coleoptera Gonipterus scutellatus Gyllenhal



Monitor the health status of forest Monitor the health status of forests in large areas of the

Iberian Peninsula.

6.3.2 DataBio forestry pilot 2.3.2-FH strategy view

Figure 32 describes the "Forestry B1-FH Strategy view" that is defined in the "Forestry B1-FH

Monitoring of forest health modelling with ArchiMate" view point. A number of elements in

the view are further explained in Table 18.

Figure 32: Forestry B1-FH Strategy view



Table 18: Explanation of specific elements in the Forestry B1-FH Strategy view

Name Description

Monitor health of Quercus forests Monitor the health of Quercus forests affected by the

fungus Phytophtora cinnamoni Rands.

Monitor the damage of eucalyptus

plantations

Monitor the damage in eucalyptus plantations affected by

the coleoptera Gonipterus scutellatus Gyllenhal

Monitor the health status of forest Monitor the health status of forests in large areas of the

Iberian Peninsula.



6.4 Big Data infrastructure: Components and BDVA classification Figure 33 presents the big data components and assets used or developed in the pilot, using

the BDVA classification. The components are explained in Table 19.

Figure 33: Big data components and assets in pilot 2.3.2-FH: Monitoring of forest health

Table 19: Listing of the components used or produced in the pilot 2.3.2-FH: Monitoring of

forest health

Used in this pilot: Produced in this pilot:

1. Centralized Datasources: 1. Imagery classification system



a. Sentinel 2A, 2B

b. PNOA

c. Field Data

d. MFE50

2. Distributed Datasources:

a. LPIS

b. NUTS2

c. TRAGSA Drones

2. Machine learning classification to

produce a “Changes Layer”

3. Imagery Optimization. Maps Evolution.

Temporal changes

4. Remote Sensing imageries download

system: Synchronous and Asynchronous

connection system. Real time data

access and batch

processes

5. Visualization and Querying system:

viewer and data access



The following technical KPIs (Key Performance Indicators) have been identified so far:

● Surface processed: number of hectares of forest land monitored using different

EO data sources (satellite/aircraft/RPAS) for the two assessed pests (Phytophtora

& Gonipterus).

● Field visits saved: an assessment of how much fieldwork (number of hours) can

be saved by using an adequate EO-based methodology will be performed.

● Economic improvements: an economic ratio will be obtained to assess the

performance of the new methodologies (€/ha) and compare it with traditional

methods.

● Accuracy of cartography obtained from different EO-data sources (% )

● Generation of new protocols for detection and monitoring of Gonipterus &

Phytophtora using EO & field data (yes/no).

● Generation of new products & services available for final users (yes/no).

● Estimation of potential users (number)

Target figures for each KPI will be established later in the project, as they need to be

established in collaboration with the end users.

6.6 Initial roadmap Pilot implementation starts on M5 with the first campaign of RPAS flights and field work. RPAS

flights + field work will take place in spring-summer-autumn periods during 2017, 2018 and

2019 (M5-M10, M17-M22, M25-M34). Gonipterus will be monitored in 2017 and 2018 and

Phytophtora in 2018 and 2019. In parallel, the necessary satellite images will be acquired.



A data processing period will take place after each field campaign (M6-M16, M18-M28, M29-

M34). In parallel, the implementation of services in Databio platform will be performed in two

periods: M18-M28 (first implementation), M30-M34 (final implementation + trial with end

users). EO services will be ready on M35.

KPIs will be measured in two moments: M12 (baseline measurement) and M35 (final

measurement). Deliverables will be produced on M6, M24 and M36, according to the general

planning.

Figure 34: Timeline of pilot 2.3.2-FH, Monitoring of forest health



Pilot 2.3.2-IAS: Invasive Alien Species control

and monitoring 7.1 Pilot overview


Invasive alien species (IAS) are a big threat for biodiversity in the Iberian Peninsula, the Canary

Islands and the Balearic Islands, and cause significant economic losses. Resources are limited

and eradication measures are complex and very expensive, so early warning and monitoring

are key points for Spanish Public Bodies to be more efficient. The model developed is

expected to identify the geographic origin of the biological invasions that will likely affect

terrestrial Spain in the next future, to provide a detailed generic spatial assessment of

invasion risk within Spain and, eventually, to serve for a better management of IAS by

increasing the efficiency of preventive measures.


market-ready technologies to the forest databases and, in this specific case, with datasets

related to trade movements and migratory flows. The target of this pilot is directly related to

pilot 2.2.2, although the technical tools to be used will be slightly different. Therefore, this

integration applies to the pilot 2.2.2: Monitoring and control tools for forest owners and, due

to it will be developed by similar teams, pilot 2.3.2: Forest monitoring health status.


The pilot aims at developing a simple model for assessing invasion risk in Spain based on a set

of factors that strongly influence the geographic pattern and level of invasion:

1) Environmental similarity, calculated from bioclimatic variables

2) Biodiversity similarity, approached through biogeographic information

3) Propagule pressure, estimated from data on trade, tourism, immigration,

population and terrestrial transport network

4) Ecosystem disturbance, measured from land use and fire frequency.

The model is expected to identify the geographic origin of the biological invasions that will

likely affect terrestrial Spain in the next future, to provide a detailed generic spatial

assessment of invasion risk within Spain and, eventually, to serve for a better management

of IAS by increasing the efficiency of preventive measures.

Pilot solution

It has been demonstrated that prevention is the most effective way to face the problem of

biological invasions. Consequently, it is important to know the invasion risk in different areas

and ecosystems for a better management of this problem. Moreover, targeting areas and

ecosystems at highest risk makes preventive measures most efficient. The pilot case, by

providing a detailed spatial assessment of invasion risk and by identifying the geographic

origin of the biological invasions that will likely affect Spain in the next future, is expected to



serve for increasing the efficiency of preventive measures and so to contribute to a better

management of IAS. Sensitive areas, i.e. those with the highest risk of invasion, will be

identified and mapped.

Invasion risk is assessed by quantifying climatic similarity (based on climatic distances) and

‘propagule pressure’ (addressed by information on tourism, immigration and trade) between

Spain and the rest of the world. Finally, the degree of disturbance of the arrival ecosystems

will also be incorporated, as well as the biogeographic regions of the territories that act as

sources of IAS.

Key problem-solving capacity

The pilot case is linked to prevention, which is both an effective and efficient way of dealing

with the problem of biological invasions. Indeed, the pilot will identify the areas in Spain at

greatest risk of invasion and the most likely source regions of IAS, thus providing crucial

information for resource prioritization and for a much better management of these species.

For instance, more resources and sensible measures could be addressed to the survey of areas

at highest risk and products coming from specific countries or regions.

In addition, because of the use of public and periodically updated databases, a dynamic tool

will be provided, with which future invasion risk assessments will be possible.

Table 20: Summary of pilot 2.3.2-IAS: Invasive Alien Species control and monitoring (ISO

JTC1 WG9 use case template)

Use case title Pilot 2.3.2-IAS: Invasive Alien Species control and monitoring



Laura Luquero & Jesús Estrada / TRAGSA Group [email protected] & [email protected]


responsibilities

Actors / roles:

- Final Users (public administrations, policy makers, forest companies, forest owners) / define users’ needs and requirements; validate the new products and services.

- Forestry Technicians and developers from Tragsa Group / develop EO-based tools and methodologies

Goals Set up a methodology for modelling IAS invasion risk in Spain.

Use case description Refer to the pilot case definition section and diagrams in the pilot modelling sections.

Current solutions

Compute(System) Dedicated server 2 processors Intel(R) Xeon(R) CPU E5606 @ 2.13GHz, 8 cores with 96 GB ECC of Memory

Storage Dedicated server Hard Disks: 2 disks - 2 TB (RAID). Total: 2 TB



Networking 250 MBps

Software OS: Debian 8.8 Apache web server 2.4.10 Tomcat: 7.0.56 and 8.0.14 R: 3.3.3. PostGres: 9.4 MySQL: 5.5.55 Python: 2.7.9 Virtuoso: 07.20.3212



All 2.3.2-IAS sources will be Centralized: WORLDCLIM provided by the International Journal of Climatology. 19 bioclimatic raster layers with a resolution of 1km. Foreign trade database from Spanish Finance Ministry. Foreign trade disaggregated by months, products, origin and destination. Available at http://www.icex.es/icex/es/navegacion-principal/que-es-icex/index.html Immigration Database by Spanish Statistical Institute. Migration to/from Spain disaggregated by year, province, country, sex and age. Available at http://www.ine.es/dynt3/inebase/index.htm?type=pcaxis&path=/t20/p277/prov/e01/&file=pcaxis Tourism dataset from Ministry of Energy, Tourism and Digital Agenda. Tourism to Spain disaggregated by month, country, destination and type of transport. Available at http://estadisticas.tourspain.es/es-es/estadisticas/frontur/paginas/default.aspx GHS – population Grid developed by JRC. Population density raster based on population census and human settlements. Available at http://ghsl.jrc.ec.europa.eu/datasets.php Spanish terrestrial transport network. ESRI Shapefile provided by the National Geographic Institute. NUTS-2, NUTS-3 and Municipalities maps from

Global Administrative Areas

(http://www.gadm.org/)

Volume (size) WORLDCLIM .TIFF images and the results obtained from them have a typical size of hundreds of Gigabytes. All the statistical information (CSV) provided by Spanish Public Administrations have an average size of several Megabytes. GHS population grid (versions 1975, 1990, 2000 and 2015) size is likely to be in the order of Terabytes.

http://www.icex.es/icex/es/navegacion-principal/que-es-icex/index.html


http://www.ine.es/dynt3/inebase/index.htm?type=pcaxis&path=/t20/p277/prov/e01/&file=pcaxis



http://estadisticas.tourspain.es/es-es/estadisticas/frontur/paginas/default.aspx


http://ghsl.jrc.ec.europa.eu/datasets.php

http://www.gadm.org/




All external sources have several years updating ratio, but touristic information datasets are updated monthly.


mashup)

The formats to be used will be imagery, ESRI Shapefiles for vector information and CSV for text information.


Highest variability rate is monthly.


analysis, action)


All data sources are official and trusted ones: Spanish Public Administration and Global and European Institutions.

Visualization Standard imagery visualization services. Spanish Public Administration usually provides WMS services for information visualization. Tabular and text information is usually provided as HTML pages.

Data quality (syntax) Even though data providers are supposed to produce good quality information, this pilot will develop R-Statistics process to improve and transform them.

Data types TIFF or JPEG for images. Text document for statistics.

Data analytics The pilot aims at developing a simple model for assessing invasion risk in Spain based on the set of factors that strongly influence the geographic pattern and level of invasion: Environmental similarity, Biodiversity similarity, Propagule pressure and Ecosystems disturbance.


Processes will be scaled to provincial, regional and national levels.


economy

The number of zones to be processed will be defined later. The aim is to process ecological variables (bioclimatic and biogeographic variables), data on flows (trade, tourism and immigration), and the degree of ecosystem disturbance (from land use, fire frequency or terrestrial transport network) from global scale to developing a model for assessing invasion risk in the Iberian Peninsula, Canary Islands and Balearic islands (approximate surface: 596.270 km2). The model will serve to improve management of IAS of Spanish Public Bodies (NUTS 2 level, Ministry, national parks...) in order to prioritize activities and increase the efficiency of preventive measures established.


considerations

None of the datasets of this pilot are considered sensitive or related to personal data.



Highlight issues for generalizing this Use

case (e.g. for ref. architecture)

Main technical problems are related to data storage and resulting maps transmission.


Spanish administration: http://www.icex.es/icex/es/navegacion-principal/que-es-icex/index.html http://www.ine.es/dynt3/inebase/index.htm?type=pcaxis&path=/t20/p277/prov/e01/&file=pcaxis http://estadisticas.tourspain.es/es-es/estadisticas/frontur/paginas/default.aspx European administration: http://ghsl.jrc.ec.europa.eu/datasets.php Global Institutions: http://www.gadm.org/



The users in the pilot are:

- MAPAMA - Ministry of Agriculture

- OAPN - National Parks Authority

- Public Administrations - NUTS2 Level

Table 21: Stakeholders and user stories of pilot 2.3.2-IAS: Invasive Alien Species control and

monitoring

Who (type of user) I want to (perform some task) Why (achieve some goals)

As an end user

(MAPAMA-Policy Makers)

I want to know current status of

the distribution of specific AIS


As an end user


I want to have accurate

information about the temporal

evolution of AIS


save field visits

As an end user


I want to know the invasion risk of

new AIS in Spain every 1-2 years

For strategic planning

As an end user


I want to establish priority areas

based on an invasion risk index

For a better management of

IAS by increasing the efficiency

of preventive measures

As an end user


I want to better know in advance

the most suitable places for AIS


save costs






http://ghsl.jrc.ec.europa.eu/datasets.php

http://www.gadm.org/



As an end user


I want to set up an alert system for

early warning of AIS presence

To allow to act as quickly as

possible

As a TRAGSA Technician I want to develop, manage and

update an early warning system

every 1-2 years

To provide my customers with

a timely service

As a generic user I want to use all standard GIS

features

To pan, change scales, go to

specific coordinates and places

and so on


The main motivations for this pilot are:

● to develop a model capable to identify the geographic origin of the biological

invasions that will likely affect terrestrial ecosystems in Spain in the next future

● to provide a detailed generic spatial assessment of invasion risk within Spain

● to provide a dynamic tool based on public and periodically updated databases with

which future invasion risk assessments will be possible

● to serve for a better management of IAS by increasing the efficiency of preventive

measures

The pilot motivation and strategy are summarized using ArchiMate diagrams in the next

section, while goals and KPIs are addressed in the succeeding evaluation plan.


The scope of the pilot extends to providing final users with a useful tool for the monitoring

and prevention of IAS presence in the Iberian Peninsula within a regional/national

geographical range.


● Lack of detail/updating in the information contained in the databases which will be

employed for the development of the “danger of invasion index”

● Complexity in combining “static” (climate) & “dynamic” (flows: commercial,

tourism) variables

● Need for capacity of adapting to changes in laws affecting IAS

● Lack of updating of the risk maps

● Technical difficulties for accessing different data sources

● Technical difficulties derived from managing big volumes of data (world from all

around the world, at a 1x1 km spatial resolution)

● Technical difficulties derived from managing many different data sources and

formats, with different spatial resolution and precision



7.3 Pilot modelling with ArchiMate This section presents the "Forestry B2-IAS Invasive alien species control and monitoring

modelling with ArchiMate" view point described using the ArchiMate standard.

7.3.1 DataBio forestry pilot 2.3.2-IAS motivation view

Figure 35 describes the "Forestry B2-IAS Motivation view" defined in the "Forestry B2-IAS

Invasive alien species control and monitoring modelling with ArchiMate" view point.

Figure 35: Forestry B2-IAS Motivation view

7.3.2 DataBio forestry pilot 2.3.2-IAS strategy view

Figure 36 describes the "Forestry B2-IAS Strategy view" defined in the "Forestry B2-IAS

Invasive alien species control and monitoring modelling with ArchiMate" view point.



Figure 36: Forestry B2-IAS Strategy view





Figure 37: Big data components and assets in pilot 2.3.2-IAS: Invasive Alien Species control and monitoring

Table 22: Listing of the components used or produced in the pilot 2.3.2-IAS: Invasive Alien Species control and monitoring


1. Centralized data sources:

a. WorldClim

b. Immigration database

1. R-based Data classification system

2. Data Optimization. Temporal changes

3. Interactive data access and process



c. Tourism dataset

d. Others

4. Visualization and Querying system:

viewer and data access



The following technical KPIs (Key Performance Indicators) have been identified so far:

• Surface processed: has of land monitored (related to the whole of Iberian Peninsula, Canary Islands and Balearic islands, approximate surface: 596.270 km2) using the methodology developed within the pilot.

• Invasion risk maps generation: Risk assessment at a geographical level with cells of 1 km per 1 km for the surface processed.

• Reports of risk level: at least NUTS2 level

• Field visits saved: an assessment of how much fieldwork can be saved by using the methodology developed within the pilot will be performed. The goal is to save at least 10 % of field visits.

• Economic improvements: an assessment of how much money can be saved by using the methodology developed within the pilot will be performed. The goal is to save at least 10 %.

More precise target figures for each KPI will be established later in the project, as they need to be established in collaboration with the end users.

7.6 Initial roadmap Pilot implementation starts on M4 with data sources selection and acquisition and will last

until M12. On M12 all data will be acquired and data processing period will start. Data

processing and information analysis will be ready on M19 and start the generation of Risk

maps. Invasion Risk Maps will be finished on M24.

After having completed the analysis phase of the data and having the information collected

and with the risk maps generated, status reports will be elaborated at NUTS2 level (M27).

Deliverables will be produced on M6, M24 and M27, according to the general planning. KPIs

will be measured at two points in time: M12 (baseline measurement) and M35 (final

measurement).



Figure 38: Timeline of pilot 2.3.2-IAS, Invasive alien species control and monitoring



Pilot 2.4.1: Web-mapping service for

government decision making 8.1 Pilot overview


A central database (FMI) of forestry and hunting provides a range of services regarding the

information on forests for various governmental bodies and forest owners. For the

development of the service, it is necessary to develop and validate the processing chain based

on the DataBio platform and big data environment. The outputs of the service (e.g. the map

server) should serve both to streamline the implementation of forestry-related measures, and

for redistribution of subsidies and tax relief for forest owners, and ultimately for forest

monitoring activities.


In the recent years, there's significant forest health decrease in Czech Republic. It is caused

by various factors, both biotic and abiotic. These are independent on the forest owner and

his management practices, resulting in loss of forest value compared to unaffected forests.

The government compensates this loss to forest owner by the means of subsidies and tax

reliefs. In order to correctly identify the affected forest owners and their eligibility for

subsidies/tax relief, the Ministry of Agriculture of Czech Republic must precisely spatially

locate the affected areas. For this purpose, the field surveys are used. These are however

local, costly and subjective.

Table 23: Summary of pilot 2.4.1 Web-mapping service for the government decision making

(ISO JTC1 WG9 use case template)

Use case title 2.4.1 Web-mapping service for the government decision making


Author/company/email Petr Lukeš / FMI [email protected]


responsibilities

Primary end-user of the pilot is the Ministry of Agriculture of Czech Republic, secondary users include forest owners in Czech Republic and Wallonia, Belgium

Goals To provide forest health service based on Sentinel-2 data

Use case description 1. Ministry of Agriculture needs relevant and timely information about current forest health status and its trends. Forest owners are looking for plot-level information about the condition of his/her property.

2. Ministry/forest owner access dedicated map servers, where forest health status and its trends are visualized in an easily accessible form.



3. The ministry will use the information for better distribution of financial aid for worst affected forest owners, and forest owners will better allocate his/her resources

Current solutions

Compute(System) FMI’s computer hardware, single PC with 8 cores and 64 GB RAM, multi-platform (Windows and Unix)

Storage Local storage

Networking Map server of FMI and Ministry of Agriculture of the Czech Republic (eAGRI)

Software Opensource technologies (GDAL, Python), in-house development



Sentinel-2 satellite data, distributed by European Space Agency. Local storage for the area of Czech Republic established at FMI, and local storage for Wallonia established at Spacebel

Volume (size) 1-2 TB annually for Czech Republic 800 GB annually for Wallonia


New satellite data being acquired every 5 days, cloud-free mosaics generated annually for vegetation growing season from all-available Sentinel-2 acquisitions


mashup)

Surface reflectance in 9 spectral channels covering visible and infrared wavelengths Set of vegetation indices generated from a combination of the surface reflectance spectral channels of S-2



analysis, action)


Derived forest health products must be sensitive to observed ground truth

Visualization FMI’s internal map server. Visualization of raster layers together with other vector and raster products (e.g. forest management plans); WMS/WFS service for third-party applications

Data quality (syntax) Surface reflectances used as an input for forest health interpretation (atmospheric corrections), sensitivity of derived products on forest health



Data types Forest reflectances and its derived products

Data analytics Forest health trends based on reflectance data, vegetation indices and forest quantitative products


To generate seamless cloud-free mosaics of Czech Republic and Wallonia, consistent and comparable in time. Increased performance of atmospheric corrections of L2A product (sen2cor vs MAJA-MACCS)


economy

To establish a robust methodology for forest health trends assessment based on the interpretation of Sentinel-2 satellite data. Feedback from end-users is needed in order to set the decision rules on forest health trends


All Sentinel-2 satellite data are provided free of charge, several internal products will be used (e.g. forest mask, forest management plan) which won’t be shared publicly


Automated production of cloud-free synthetic mosaics for Czech Republic and Wallonia; Retrieval of forest parameters from satellite data; Interpretation of forest health trends




Table 24: Stakeholders and user stories of pilot 2.4.1 Web-mapping service for the government decision making

Who I want to Why

Ministry of

Agriculture

of the

Czech

Republic

The ministry of Agriculture of the Czech

Republic wants to have objective and

timely tool for the assessment of forest

health status, systematically for the

entire area of the country. Based on the

analysis of the outputs, subsidies shall

be distributed to target the most

affected forest owners. Local forest

owner want to know current extend,

spatial and temporal trends of forest

health status decay in order to plan the

forest activities.

Outdated forest health monitoring

programme using static forest damage

zones established 20 years ago, strong

focus on abiotic sulphur dioxide emissions,

which are no longer prevailing damage

factor of Czech forests. Forest health

monitoring using Landsat data with

limited spectral and temporal

performance. Subsidies for forest owners

affected by the reduction in forest value

doesn’t correspond to actual salvage

felling volumes on municipality levels.




Local forest

owners,

including

Forests of

the Czech

Republic

and

Wallonia

Web-based service for both the

Ministry of Agriculture and local forest

owners. The service will provide both

municipality-level information on forest

health (each municipality will be

assigned to one of four classes) for the

purpose of subsidies re-distribution and

several thematic layers describing the

actual forest health and its trends on

forest compartment level (i.e. pixel size

of 20m x 20m). Local forest owners in

Czech Republic and pilot sites in Finland

and Wallonia will also benefit from the

availability of thematic layers on forest

health on the Wuudis platform, where

both forest management plan and the

forest health layers can be used in a

mobile environment.

Limited knowledge on timely forest

health information for pro-active forest

management – e.g. current extent of

decaying forests and their spatial

trajectory


Our main motivation for this pilot is to develop a new methodology for forest health

assessment based on Copernicus satellite data. This allows us to assess the forest health of

the entire area of Czech Republic and other temperate forest regions in Europe, while

reducing costs for field surveys and highly effective identification of forest owners eligible for

subsidies / tax relief. This pilot focuses on technological development of the processing of

Sentinel-2 optical data. Although the first pair of Sentinel-2 satellites has been launched

already in 2015 and 2017, there is no settled methodology for satellite data processing and

interpretation available for the Ministry of Agriculture and its associated organizations.

Utilizing the great potential of high-spatial and temporal resolution satellite data for forestry,

with special focus on forest health trends is thus the main goal of the pilot. In addition, the

forest owners will benefit from publicly available map server and implementation of the

layers on the Wuudis platform, where all forest health status maps will be published to allow

pro-active management of their forest properties.


The scope of this pilot is to provide timely and accurate information on forest health status

and its trends. By utilizing advanced methods of spatio-temporal data analysis of big satellite

data, the pilot will generate wall-to-wall cloud-free maps of forest health.



The following limitations has been identified:

● satellite products retrieved from Sentinel-2 satellite data may not be sensitive to

describe forest health of heterogeneous, highly mixed forest plots (e.g. mixture of

broadleaved and coniferous forests, multi-layered forest canopies).

● spatial resolution of 20 m is too coarse to observe tree-level change in forest health.

Change in forest health of individual tree will result in sub-pixel change of observed

forest reflectance which may not be detectable. The minimum spatial unit of forest

health attribution is forest stand.

● it is challenging to separate different forest management activities (e.g. logging of old-

growth forest in its felling age vs. sanitation felling due to forest health decay). In the

pilot, we will use rich database of forest structural information to interpret the

intermediate satellite-based forest health maps.

● interpretation of forest health trends will be based on observed satellite reflectances.

Since the forest is an extremely heterogeneous environment where reflectances

change both in time (vegetation phenology) and space (vegetation structure), it may

be difficult to obtain cloud-free image of larger areas normalized to single observation

period. Through the use of advanced spatio-temporal analysis of the data, some

periods with high cloud cover (e.g. winter and spring months) may be unavailable for

the analysis due to lack of high quality data.

8.3 Pilot modelling with ArchiMate This section presents the "Forestry C1 Web-mapping service for the government decision

making modelling with ArchiMate" view point described using the ArchiMate standard.


Figure 39 describes the "Forestry C1 Motivation view" defined in the "Forestry C1 Web-

mapping service for the government decision making modelling with ArchiMate" view point.

Figure 39: Forestry C1 Motivation view




Figure 40 describes the “Forestry C1 Strategy view” defined in the “Forestry C1 Web-mapping

service for the government decision making modelling with ArchiMate” view point.

Figure 40: Forestry C1 Strategy view





Figure 41: Big data components and assets in pilot 2.4.1 Web-mapping service for the government decision making

Table 25: Listing of the components used or produced in the pilot 2.4.1 Web-mapping service

for the government decision making


• 1, 2 FMI map server, Wuudis platform

• 3 QGIS, NumPy

• 1 Lookup tables for product retrievals

• 2, 3, 4, 5 Processing chain of S2 data



• 4 Matlab

• 5 Python, GDAL, SNAP

• 6 QGIS, SNAP

• 7 FMI map server

• 8 Sentinel-2 satellite images

• 9 Thematic raster maps

• 10 In-situ validation data

• 6 Cloud-free Sentinel-2 images

• 7 Forest health maps



There are five KPI’s related to the pilot:

• Systematic production of Sentinel-2 L3 product / spatio-temporal analysis using all available Sentinel-2 data to yield cloud-free data for user-defined dates.

• Production of thematic layers of forest health status, and its trajectories between 2015 and 2018. Thematic layers will be based on vegetation indices and forest quantitative products, which will be identified as sensitive to forest health.

• Validation and interpretation of forest health status and its trends based on extensive in-situ data collection and feedback from users

• Publication of forest health maps on dedicated map server

• Distribution to third parties via WMS/WFS service (e.g. Wuudis)

8.6 Initial roadmap Pilot implementation will start with the establishment of wall-to-wall data archive of

atmospherically corrected Sentinel-2 observations for the Czech Republic and Wallonia

(Q1/2018) and systematic production of cloud-free country mosaics using advanced spatio-

temporal analysis (Q2/2018).

In the next phase, interpretation of cloud-free surface reflectances will be performed via

vegetation indices and forest quantitative products (Q4/2018) and its validation against both

in-situ data collection and feedback from users (Q1/2019).

Finally, the thematic products of forest health and its trends will be published on a dedicated

map server (Q2/2019) and published to third parties (e.g. Wuudis platform) via WMS/WFS

services (Q4/2019).



Figure 42: Timeline of pilot 2.4.1, Web-mapping service for the government decision making



Pilot 2.4.2: Shared multiuser forest data

environment 9.1 Pilot overview


The Finnish Forest Centre has an important role to activate the different actors of the forestry

sector to utilize Big Data and the third parties to develop new solutions and applications for

forest owners and other actors. Currently about 80 percent of private Finnish forestry estates

have laser scanned and analysed forest resource data available online. The coverage will be

100 percent by 2020. To make use of this information, the governmental body Finnish Forest

Centre (METSAK) provides an eService called Metsään.fi to make this forest resource

information available for citizens free of charge. Metsään.fi eService is in constant

development by METSAK.

The plan is to pilot presenting crowdsourced forest data and possible new functionalities

related to it in Metsään.fi eService and therefore enhance the use of Metsään.fi and

METSAK’s forest resource data. The collecting methods are also aimed to increase the amount

of METSAK’s forest resource data.


market-ready technologies to the forest databases with METSAK and the resulted solutions

will be piloted with the forestry sector partners, with associated partners and other

stakeholders e.g. public policies related to nature conservation, infrastructure or landscape

or town plans. This integration applies to the pilot 2.2.1: Easy data sharing and networking.

This pilot is developed in Task 2.4.2 “Shared multiuser forest data environment”, under WP2

Forestry pilot and Task 2.4 “Forest data management services (forecast/predict)”. The

involved partners are METSAK, VTT.


At the moment, there are two recognized areas on crowdsourcing solutions to be piloted:

showing quality control data for young stand improvement and early tending for seedling

stand, and storm damage data. Other possible crowdsourced data, such as other forest

damage than storm damage data, will be evaluated during the project. Another pilotable topic

is the open-data interface to environmental and other public data in Metsään.fi databases.

This topic is highly dependable of development of the Finnish forest legislation and piloting it

will also be evaluated later during this project.

This pilot specifies the requirements for refining and showing the crowdsourced forest data

to Metsään.fi users. The implementation of the new functionalities and data-presenting will

be carried out in collaboration with Metsään.fi’s development team and other METSAK’s

projects. This pilot gives specifications to other projects and follows up the implementation

according to these specifications.



Table 26: Summary of pilot 2.4.2 Shared multiuser forest data environment (ISO JTC1 WG9

use case template)

Use case title 2.4.2 Shared multiuser forest data environment



Anu Kosunen / METSAK [email protected]


responsibilities

Forest owners and forestry operators as Metsään.fi eService users. The Finnish Forest Centre (METSAK) admin users who use and refine the forest resource data and make it available for Metsään.fi users.

Goals To enhance the use of Metsään.fi eService and the use of METSAK’s forest resource data.

Use case description Specifying the requirements for new information and functionalities of Metsään.fi eService and implementing them in collaboration with Metsään.fi development team and other METSAK’s projects. This pilot gives specifications to other projects and follows up the results of implementation.

Current solutions

Compute(System) METSAK’s internal systems related to forest resource data.

Storage Databases for METSAK’s internal forest resource data system, for publishing forest resource data for Metsään.fi and Metsään.fi. File system for map materials.

Networking Web based solution for Metsään.fi users

Software Metsään.fi eService



Centralized forest resource data system as main data source. Original data source for forest resource data can be laser scanning, field measurement, growth modelling or notification from forest owner or forestry operator. Other data sources for Kemera financing data, forest use declarations, access and authorization.

Volume (size) 200 GB of forest resource data in the beginning of 2017


New forest inventory once in a decade per area. Constant other updates from field measurements, quality control, forest owners’ forest management plans and other notifications from forest owners and forestry operators.


mashup)





Same as above (velocity).


analysis, action)



Visualization The user interface is the existing Metsään.fi eService and its map views. For METSAK admin users there are also existing internal systems with which the data is browsed and handled.

Data quality (syntax) Collected forest damage data and quality control data must be consistent with the specific standards.

Data types Tree stand basic data, tree stand strata data, growth place data (site quality), location data, time stamps.

Data analytics Storm damage generalization, national averages of work quality.


To balance between data publicity and privacy, to adapt to the new Finnish Forest Act being revised at the moment and to take into account both public authorities’ and Metsään.fi eService users’ needs.


economy

To maintain the consistency of data and the usability of new data and functionalities from the Metsään.fi user point of view to support better forest management and therefore bio-economy.


considerations

There are both public and private data in Metsään.fi eService. Personal and forest estate specific information are largely private. The Finnish Forest Act sets demands on data publicity and privacy issues.

Highlight issues for generalizing this Use

case (e.g. for ref. architecture)

Using data standards in the interfaces. Visualizing complex data in a logical way for every “straw man”.



Note: The Finnish Forest Act influences significantly this pilot, especially regulations on open and private forest data and demands for METSAK on offering specific forest data to the private forest owners.






Table 27: Stakeholders and user stories of pilot 2.4.2 Shared multiuser forest data environment

Who I want to Why

Forest owner I want to see relevant storm damage

observations and possible forest

damage areas on map, and to see the

quality control data concerning my

forests and the national average of

the quality control data.

To take the action needed to diminish the

damage and prevent further damages in

my forest.

To follow and evaluate the quality of

work of the forest operator I have made a

contract with.

Forestry

operator

I want to see storm damage

observations and possible storm

damage areas on map, to see my

quality control data in one place and

to see the national averages on

quality control data.

To contact the forest owners in the area

to offer silvicultural work to diminish the

damage or prevent future damages.

To follow my quality of work more easily

and compare my quality of work to the

national level.

METSAK user

as data and

system

administrator

I want to refine the crowdsourced

data (storm damage data, quality

control data), have the new storm

damage observations in METSAK's

internal system and increase the

amount of quality control data.

To show Metsään.fi users the possible

storm damage areas, update the forest

resource data according to storm damage

observations, calculate more precise

national averages on quality control and

offer it to Metsään.fi users.


This pilot aims to enhance the use of the Metsään.fi eService and the amount and use of

METSAK’s forest resource data through collaboration between Metsään.fi development team

and other METSAK’s projects. The pilot consists of producing requirement specifications for

showing new data and functionalities in Metsään.fi. A possible new way to collect forest

resource data is crowdsourcing. At the moment, there are two recognized solutions for this:

collecting storm damage data and collecting quality control data for young stand

improvement and early tending for seedling stand. Other solutions might come up later

during the project.

The user interfaces for presenting quality control and storm damage data and possible new

functionalities related to them are defined in this pilot. The interfaces between information



systems or applications are defined in other METSAK’s projects. For example, if some mobile

applications for collecting data are to be developed, the interfaces between the mobile

application and METSAK’s internal services and systems are defined in other projects.

The key problem-solving capacity is that forest owners can better respond to storm damages

according to new information and diminish the damages and prevent further or future

damages in their forests. Forest owners can follow the quality of work being done in their

forests and compare it to the national quality averages. This supports better forest

management and the bio-economy.

Forest operators can offer forest owners silvicultural work in storm damage areas, follow the

quality of their own work and compare it to the national quality averages.

METSAK users are able to update the forest resource data according to storm damages and

to offer Metsään.fi users more information and tools on storm damages and quality control

to support better forest management.


This pilot operates in an existing system environment of METSAK’s producing new data and

functionalities related to that data for Metsään.fi users. The pilot scope is to:

• create requirement specifications for Metsään.fi updates concerning crowdsourced data

• create testing plans for Metsään.fi updates specified in this pilot

• carry out acceptance testing of Metsään.fi update specified in this pilot

• review the requirement and interface specifications of new data collection methods for collecting crowdsourced data

• review forest data standardization updates concerning quality control data

• evaluate other possible crowdsourced data and open data to be piloted

The limitations in this pilot are caused by:

• Operating in METSAK’s system environment and its development: this sets both content and schedule limitations when specifying and testing changes in Metsään.fi.

• The legislation (The Finnish Forest Act) and its changes: data sensitivity and access must be taken into account.

• The forest data standard: all the forest data interfaces must be consistent with the forest data standard.

9.3 Pilot modelling with ArchiMate


Figure 43 describes the "Forestry C2 Motivation view" defined in the "Forestry C2 Shared

multiuser forest data environment modelling with ArchiMate" view point.



Figure 43: Forestry C2 Motivation view

The element “Improve forest management” is further explained by the following description:

“In Finland, there are vast amounts of passively owned forests that could serve both financial

and environmental needs for forest management more effectively. Also, many novel forest

health problems are likely to occur in the future without innovative forest management

solutions that can enable appropriate management activities. A major concern of forest

authorities is how to encourage forest owners to better manage their assets. The Finnish

Forest Centre provides Metsään.fi eService for forest owners and forestry operators to

support the management of privately owned forests and to enhance the use of forest

resource data. Metsään.fi eService is constantly improved by means of increasing the forest

data and functionalities related to it.”


Figure 44 describes the "Forestry C2 Strategy view" defined in the "Forestry C2 Shared

multiuser forest data environment modelling with ArchiMate" view point. Table 28 further

specifies some of the view's elements.



Figure 44: Forestry C2 Strategy view

Table 28: Explanation of specific elements in the Forestry C2 Strategy view

Name Description

Analyse and present data The ability to process acquired data using a set of rules and

algorithms. Present the result to the user in a preferred format on

the preferred devices, e.g. map layer on a chart plotter.

Collect sensor data The ability to collect measurements from a sensor device through a

robust interface



9.4 Big Data infrastructure: Components and BDVA classification The existing technical environment of Metsään.fi eService concerning big data is described in

Figure 45. The components are explained in Table 29. This pilot is about further development

of Metsään.fi eService and adding new forest resource data to METSAK’s forest resource data

system to be utilized.

Figure 45: Big data components and assets in pilot 2.4.2 Shared multiuser forest data environment



Table 29: Listing of the components used or produced in the pilot 2.4.2 Shared multiuser

forest data environment


• 1, 2 Metsään.fi user interface

• 3, 4, 5, 6, 7 Processing chain of forest resource data

• 8, 9 Exchanged data with Metsään.fi users related to

Metsään.fi services and data from other forestry

operators

• 10 Laser scanning, aerial photographing, field

inventories, notifications from Metsään.fi users

• 11 Combining data from different sources

• 12 Integration to METSAK’s other internal systems

• 13 Access control and strong authentication (Vetuma,

KATSO)

• 14 METSAK’s system databases: forest resources,

customer information, publishing, financing and forest

use (Oracle DB, SQL Server)

• 15 METSAK’s map server (ArcGIS) and file server

• 16 Forest resource data, customer information,

financing, forest use

• 17 Laser scanned data

• 18 Geometry: compartments, forest estates, nature

objects, flow models.

• 19 Thematic raster maps, aerial photographs

• 20 Descriptions of forest resource data, suggested

operations, forest estate data, Instructions etc.

• 1 New maps and

functionalities to

Metsään.fi concerning

crowdsourced data

• 2 Prescriptions of

quality control for

Metsään.fi users

• 3 Bringing generalized

storm damage data to

Metsään.fi

• 4 Producing needed

updates on forest data

standard to collect

quality control data

with mobile devices

• 5 Producing new map

materials to Metsään.fi

concerning

crowdsourced data




They were defined in the project proposal phase and updated in the beginning of this project

based on the Finnish Forest Act at the time being. The Forest Act is being revised at the

moment. The pilot evaluation plan will be updated based on the coming Forest Act.

The KPIs in this pilot are as follows:

● The present amount (in the beginning of 2017) of METSAK's forest resource data is

around 200 GB. The amount is expected to increase by approximately 100 GB per

year during this project, amounting to around 500 GB by the end of 2019.



● The coverage of forest resource data in Metsään.fi eService is now around 11 million

hectares. The amount is expected to increase by 800 000 hectares per year,

amounting to around 13.4 million hectares by the end of 2019.

● The amount of data available to be downloaded for forestry operators' own

information systems is now around 1.5 million hectares. The amount is expected to

increase by one million hectares per year, amounting to around 4.5 hectares by the

end of 2019.

● The amount of forest owner as Metsään.fi end users is now around 70 000. The

amount is expected to increase as follows: 85 000 in the end of 2017, 100 000 in the

end of 2018 and 110 000 in the end of 2019.

● The amount of forestry service providers (FSPs) as end user groups is now around

380. The amount is expected to increase as follows: 550 in the end of 217, 650 in the

end of 2018 and 750 in the end of 2019. Note: The forestry operator is the actual

end user level under the FSPs.

9.6 Initial roadmap The technical design and implementation of bringing the new forest data available for

Metsään.fi eService is carried out in other METSAK’s projects and the further development of

Metsään.fi. All METSAK’s forest resource data is saved in a centralized forest resource data

system. Metsään.fi eService uses that data through a publishing database and other existing

interfaces. The data is not saved in Metsään.fi eService itself.

The implementation schedule follows the schedule of Metsään.fi development plans. The

development is constant and the publishing schedule is updated regularly due to a large

amount of dependencies with other system development and technical environment issues

in METSAK.

The implementation plan for this pilot proceeds on as follows. The milestones listed appear

in the following figure.

1. Create initial plans and descriptions for the pilot (Q3/17)

Milestone: Initial plans and descriptions ready. Components identified.

2. Specify and develop the needed data with METSAK’s other parties (Q3/17).

3. Specify the detailed use cases for the pilot system (Q4/17).

4. Assist implementing new data to the pilot environment (Q2/18).

5. Take part into standardizing work (Q3/17-Q3/18).

6. Collect other pilot topics under crowdsourcing and open data issues (Q3/17-Q3/18).

7. Carry out the intermediate KPI follow-up.

Milestone: Detailed use cases ready. Standard changes ready.

8. Follow the implementation of the new features to the pilot system.

9. Assist gathering all data available and show it on the user interface.

10. Carry out the acceptance testing of the pilot implementation.

Milestone: Pilot implementation ready.



11. Evaluate additional pilot topics collected.

Milestone: Additional pilot features planned and scheduled.

12. Iterate the needed steps 2-10 for the additional pilot features and the KPI follow-up.

Milestone: Final implementation completed.

13. Evaluate and report the results in the pilot.

Milestone: Pilot results documented. Final pilot KPI measurement done.

Possible new crowdsourcing or open data features are evaluated continuously in the project

and will be implemented in an iterative way to the pilot if applicable. All new bigger features

are split into small parts to enable fast deployment and testing cycles. After developed

features are tested by the development team and deployed to the production environment,

these features are ready for the DataBio pilot case.

Figure 46: Timeline of pilot 2.4.2, Shared multiuser forest data environment



References

Reference Name of document (include authors, version, date etc. where applicable)

[REF-01] DataBio website. www.databio.eu. Retrieved 2017-06-20.

[REF-02] ArchiMate® 3.0 Specification. http://pubs.opengroup.org/architecture/ArchiMate3-

doc/toc.html. Retrieved 2017-06-29.

http://www.databio.eu/

http://pubs.opengroup.org/architecture/archimate3-doc/toc.html

http://pubs.opengroup.org/architecture/archimate3-doc/toc.html

d2.1 forestry pilot definition - databio · 2017. 7. 5. · d2.1 – forestry pilot definition...

Documents