Towards participatory approaches to a Multiscale European Soil Information System

Nicola Filippi, Panagos Panos, Borut Vrscaj

EUROPEAN COMMISSIONJOINT RESEARCH CENTRE

Institute for Environment and Sustainability

First Workshop on European Reference Grids (EuroGrid-2003)

1. RATIONALE OF THE PROJECT1. RATIONALE OF THE PROJECT

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BGR

INRA

SSLRC

CSIC

NJ OS

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ALTERRA

CSES

A network of Centres of Excellence in Soil Science

Soil data

ESB Network 1:1M Soil Database

1. Rationale of the Project1. Rationale of the Project

Extension of the1:1M Soil Databaseto the Russian Federationand the Mediterranean

Polygon Attribute Table

TEXT...

n, 1

n, n

1, n

1, 1

......

1

1

2

3

4

3

314

10

1314

13

1412

1011

10

10 11

1

1

2

3

3

3

4...AREA... SMU

SMU

STU Attributes

SMU STU STU SOIL

STU.ORG

SMU 4

SMU 3

SMU 2

SMU 1

SMU Attributes

- composed of STU 13 and 14- geometrically defined by 3 polygons

(which also is part of SMU 1)- composed of STU 10- geometrically defined by 1 polygon

- composed of STU 12- geometrically defined by 1 polygon

- composed of STU 10 and 11- geometrically defined by 2 polygons

PEDOLOGICAL LANDSCAPE

SPATIALIZED DATABASE

INFORMATION ORGANIZATION IN THE SOIL GEOGRAPHICAL DATABASE OF EUROPE

AREA

101 11 70

1234

13

3

1233

101214

1013

3010065

10035

11121314

1234

4

oo

Soil1. Rationale of the project1. Rationale of the project

Soil Geographical Database of Europe

World Soil and Terrain Database

Soil Monitoring Sites

Catchment Information System

FAO

EU

Member States

Regions

Communes

Global assessments

Precision farming

1 : 5,000,000

1 : 1,000,000

1 : 250,000

1 : 50,000

1 : 5000

Different scales give answers to different questions

1. Rationale of the project1. Rationale of the project

Georeferenced Soil Database of Europe

Towards a nested European soil information system

1. Rationale of the project1. Rationale of the project

Multiple functions of soil

• Food and other biomass production

• Storage, filtering, and transformation

• Habitat and gene pool

• Physical and cultural environment for mankind

• Source of raw materials

Monitoring Agriculture with Remote Sensing programme enhanced the European 1:1M Soil Database

1. Rationale of the Project1. Rationale of the Project

• Erosion• Decline in organic matter • Soil contamination• Soil sealing• Soil compaction• Decline in soil biodiversity• Salinisation• Floods and landslides

http://europa.eu.int/comm/environment/agriculture/soil_protection.htm

Threats to soil as identified in COM(2002) 179‘Towards a Thematic Strategy for Soil Protection’

1. Rationale for the Project1. Rationale for the Project

Advisory Forum

Chair DG ENV

Stakeholders meetings

Chair DG ENV

TWG 1Monitoring

TWG 2Erosion

TWG 3Organic matter

TWG 4Contamination

ISWG = Interservice Working GroupTWG = Technical Working Group

Commission ISWG Chair DG ENV

Technical co-ordination group and secretariat Chair DG ENV

TWG5Research

Soil Policy Development Organisational Set-up

2. WHY A GRID?2. WHY A GRID?

Soil Geographical Database Soil Monitoring Sampling points

What is a grid?A network of lines that cross over each other:

- to make a set of pixels - to locate points

SPACE TIME The futureEuropean System of Soil Data

Reasons for shifting to grid (pixels)

1. End users are mostly using grid data

2. Copyright issues are simpler

3. Updating and maintenance is simplified

4. Implementing the Nested European Soil Database is facilitated

2. Why a grid?2. Why a grid?

3. MAJOR CARACTERISTICS OF THE GRIDSHow to increase the integration among existing grids?

3. MAJOR CARACTERISTICS OF THE GRIDSHow to increase the integration among existing grids?

National Soil Monitoring

National Soil Surveys

Reporting policy relevant soil data aggregated by administrative units

EU Soil Monitoring(ICP Forest+LUCAS,etc.)

Georeferenced Soil Database for Europe

Soil Mapping Unit

(Soilscape)

Normalised Statistical Unit

Towards future flow of soil information in Europe

0

0,5

1

1,5

2

2,5

3

3,5

4

4,5

5

EUROPE

SQMN

Soil2 x CLC2 combinations

Rel

ativ

e F

requ

ency

ComparisonStatistics for all EuropeStatistics for grid points

Soil

Land cover

Grid

4. Does the grid meet our needs?4. Does the grid meet our needs?

Organic Carbon (%) No Data 0 - 1 1 - 2 2 - 5 5 - 10 10 - 25 25 - 35 > 35

Organic Carbon Content Data sourcesSoil typeLand coverTemperature

Rasterization Spatial layers derived by rasterization of a Triangulated Irregular Network (TIN) model with weighted distance interpolation

Soil typeTemperature

5. LINK YOUR PROJECT WITH OTHER DATA(raster layers of 1km grid size)

5. LINK YOUR PROJECT WITH OTHER DATA(raster layers of 1km grid size)

Temperature

SOIL DATASOIL DATA

POLYGON : IN RASTER FORM / GRIDS vector

PONT : SAMPLING IN REGULAR or RANDOM LOCATIONS

Temperature

TYPES OF SOIL DATATYPES OF SOIL DATA

Soil MapsVECTOR THEMATIC MAP – RASTER DATA;

GRIDED DATA

Soil Profiles POINT - RANDOM

Soil Pollution… various monitoring prj.POINT - REGULAR GRID

datasets

1 – RANDOM - REPRESENTATIVE SAMPLING Soil profiles

chemical & physical soil properties(CONTINUOUS PROCESS)

Temperature

SAMPLING SOILS – SOIL MONITORINGSAMPLING SOILS – SOIL MONITORING

2 – REGULAR GRID SAMPLING

MANY? national soil monitoring projects •Pollution (heavy metals, pesticides…)

SAMPLING SOILS – REGULAR GRID SAMPLING SOILS – REGULAR GRID

EXAMPLE:Monitoring soil pollution in Slovenia: •4x4km predefined sampling points,regular grid•National projection: Gaus-Krueger, 5th zone, Bessel…

Standard report - 1st page Location data

Interpreted location data - heavy metals in soil

SAMPLING SOILS – REGULAR GRID SAMPLING SOILS – REGULAR GRID

Sampling pattern Sampling depths

Example:

Temperature

SAMPLING SOILS IN REGULAR GRIDSAMPLING SOILS IN REGULAR GRID

Raster processing of data SAMPLED IN REGULAR GRID

geostatistics ……merging with vector derived data – properties… …evaluation…

state of the environment…

Zn in soil (0-5cm)

Areas of warning concentrations

Areas of critical concentrations

Temperature

RASTER PROCESSING OF VECTOR DATARASTER PROCESSING OF VECTOR DATA

RASTER PROCESSING

GRIDS!Many advantages

MODELLINGPollution, Soil SealingErosion, Land Use, Flood risk…

Soil data and: -EO / RS data; -DEM & DEM derived; -Weather; -Lithology-Land-use;-….

Temperature

GRID PROCESSING OF VECTOR DATA IGRID PROCESSING OF VECTOR DATA I

EXAMPLE:

RASTERISED SOIL MAP: 3D RASTER MODELLING

Temperature

GRID PROCESSING OF VECTOR DATA IGRID PROCESSING OF VECTOR DATA I

MODELLING:

IMPROVING SOIL DATA:

GEOGRAPHIC

SEMANTIC ?!?

Temperature

WHERE TO MEETWHERE TO MEET

VARIOUS SOIL DATA: •DATA OF VECTOR ORIGIN•POINT - SAMPLING IN REGULAR GRID•POINT - SAMPLING IN RANDOM GRID

RECOMMENDATION?:

TO PROCESS SOIL DATA AND

NON-SOIL REGULAR GRID BASED DATA

IN A RASTER FORMAT

?

Temperature

WHERE TO MEETWHERE TO MEET

Thank You

Soil inventories Soil monitoring

SPACE TIMENational soil surveys

MAJOR CARACTERISTICS OF THE GRIDSHow to increase the integration among existing grids?

3. How to increase the integration among existing grids?3. How to increase the integration among existing grids?

Soil x Land-Cover Europe Grid-points Bd x 31 4.9% 5.2% Lo x 21 3.8% 4.0% Be x 21 3.0% 3.2% Bk x 23 2.6% 2.8% … …

0

0,5

1

1,5

2

2,5

3

3,5

4

4,5

5

5,5

Europe

S.Q.M.N.

Soil2 x CLC2 Combinations

Rel

ativ

e fr

eque

ncy

Comparison of the frequencies of distributions

Soil x Corine Land Cover

Rela

tive f

requ

enci

es

All EuropeGrid-points

4. Does the grid meet our needs?4. Does the grid meet our needs?