a high resolution land use/cover modelling framework for europe: introducing the eu-cluescanner100...

ICCSA June 2011 , MUBAREKA

Land Use Modelling Platform Core :

Eu-ClueScanner 100m

Sarah MUBAREKA

Land modelling team:Carlo Lavalle, Claudia Baranzelli, Carla Rocha Gomes

Land Management and Natural Hazards UnitInstitute for Environment and SustainabilityJoint Research Center


• Why have one?

• How does it work?

• Calibration and validation of model

• Quiz


• LUMP stands for Land use Modeling Platform

• Main objective is to provide land use / land cover simulations for Europe

• The core of LUMP consists in a Land Allocation Model (DynaCLUE algorithm set)

• Interfacing with other sector models is “easy” because of the open source platform

• Includes tools to assess impacts of Land Use/Cover change in various areas of application (areas sensitive to land use change)

WHAT IS LUMP?

Everyone needs a LUMP


Land Use Modelling : Examples of Potential Applications at JRC *

Theme Issue

Agriculture Agro-Environment Rural Development Agro-Economy

Assessment of current and potential agricultural area and cultivation useAssessment of CAP impacts on future land use. CAP, climate change, macro/micro economicEnvironmental and landscape impacts; the assessment of nutrients fate

Ecosystem services Valuation of services (spatially explicit). Mapping of spatial variation of ecosystem services in biophysical terms. Analysis of land use changes for impacts on ecosystem services.

CC Emission / Adaptation

Assessment of GHG fluxes in agriculture and forestExposure and vulnerability AnalysisDefinition and evaluation of spatial measure of adaptation

Economy Evaluation of the impact of cohesion policy on EU regional economies

Hydrology Water quantity: floods, drought, water scarcity, desertification, …

Transport Congestion and traffic indicators, emissions. Feed back with land use

Soil, vegetation Suitability analysis, soil and land degradation, desertification, SOC

… …

(*) Answers to a survey launched by IES in 2009



Land cover/use/function enables the balance between economic, social and environmental considerations.

This concept is gradually being integrated into EU policies:

Environment Biodiversity, Soil, Landscape preservation, Ecosystem Services, …

Transport Integration of transport into land use planning (and vice versa) (Focus Group, 2009)

Agriculture Shift from ‘market driven’ to ‘rural development’ (CAP Health check)

Energy Consumption and land use, bio-fuel production

Climate change Mitigation and Adaptation have a relevant land component

Regional Policies Territorial Cohesion (explicit reference in the Lisbon treaty)



ImpactAnalysis

Cost/BenefitAppraisal

Future ClimateGlobal / Regional

Climate Models

Natural Hazards- Floods (EFAS, LISFLOOD)- Droughts (EDO)- Forest Fires (EFFIS)

Risk Prevention (adaptation)

Current Climate,Soil, Vegetation

Socio-economic Trends & Scenarios

Land Use MOLAND

EuClueScanner

Emission scenarios (IPCC SRES)

LUMP framework


• Why have one?



• Quiz


LUMP is a platform composed by 3 main modules:

1. Interfaces with sector-specific exogenous models• Demand for different land uses within different climate and

economic contexts

2. Endogenous allocation model – EUClueScanner• Land use/cover suitability factors and neighbourhood effects• Policy alternatives modelled as maps • Factor and parameterisation might be defined dynamically by

external models

3. Impact assessment tools• Post-processing tools and indicators

How does it work?


Projected Land Use Change

External drivers for land-use changesExternal drivers for land-use changes

Policy-related suitabilitiesPolicy-related suitabilities Location-specific suitabilitiesLocation-specific suitabilities

Current land-useCurrent land-use Land-use Change SimulationLand-use Change Simulation

Demand ModuleDemand Module

Land-use based indicators:• Land-use maps• Change hotspots• Regional changes• …


Thematic indicators:• Erosion• Carbon sequestration• Biodiversity• …


Definition of

Demands

Definition of

Demands

Definition and

implementation

of EU Policy

Alternatives

Definition and

implementation

of EU Policy

Alternatives

Impact analysisImpact analysis

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Demand settingsDemand settings

demand casedemand case

land-use caseland-use case

Demand scenarioDemand scenario

How does it work?










Definition of

Demands

Definition of

Demands

Definition and

implementation

of EU Policy

Alternatives

Definition and

implementation

of EU Policy

Alternatives


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Demography/Population projections

Demography/Population projectionsEconomic ModelsEconomic Models




How does it work?


Historical Land Use/Cover, U

t = 1990;2000;2006

Historical Land Use/Cover, U

t = 1990;2000;2006

Land Demands: Urban fabric (residential areas)

Historical Population, P (Eurostat)

t = 1990;2000;2006

Historical Population, P (Eurostat)

t = 1990;2000;2006NUTS 2 regions iNUTS 2 regions i

Historical population density, DHistorical population density, D


Land Demands: Industrial and commercial areas

Holistic Regional Economic Model

RHOMOLO

Holistic Regional Economic Model

RHOMOLO

Forecasts 2020GDPEmploymentProduction

Forecasts 2020GDPEmploymentProduction

Eurostat economic statistics

Eurostat economic statistics

Regional economic profiles

Regional economic profiles

Land demand for industrial

and commercial areas

Land use efficiency per

region and per sector

Land use efficiency per

region and per sector


Land demand for main crop groups per NUTS 2 region

Historical statistics on agricultural commodity

production from CoCo/CAPRI(1990-2005)

Historical statistics on agricultural commodity

production from CoCo/CAPRI(1990-2005)

Land Demands: Agricultural areas

Trends in historical agricultural land use from Corine (1990-2006)

Trends in historical agricultural land use from Corine (1990-2006)

EU-wide agriculture sector modelling

system CAPRI (forecast 2020)

EU-wide agriculture sector modelling

system CAPRI (forecast 2020)

Minimum and maximum trends in agricultural land claims per crop

group

Minimum and maximum trends in agricultural land claims per crop

group

Currently being employed for the assessment of the new CAP


Land demand for main forest typologies per

Country

Historical statistics on forest related products

Historical statistics on forest related products

Land Demands: Forest areas

Trends in historical forest land use from Corine (1990-2006) and

Forest Map 2006

Trends in historical forest land use from Corine (1990-2006) and

Forest Map 2006

Wood/Non-Wood product economic

modelling (EFSOS, OECD, ..)

Wood/Non-Wood product economic

modelling (EFSOS, OECD, ..)

Harvest demand -> Minimum and maximum trends in land claims

per main forest species/typologies

Harvest demand -> Minimum and maximum trends in land claims

per main forest species/typologies

In progress ..(Ref. AA with CLIMA)










Definition of

Demands

Definition of

Demands

Definition and

implementation

of EU Policy

Alternatives

Definition and

implementation

of EU Policy

Alternatives


Glo

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EconomyEconomy Demography/Population projections



How does it work?


Based on Corine Land Cover 2006Flexible legend/nomenclature

• Refined version of the CLC is being validated with the use of reference data;

• Main objectives:

• Feed EUCS with more detailed original Land Use Map;

• Better spatial definition of local land-use change dynamics.

Current land-use

How does it work? Base map.


Refinement of the Corine Land Cover 2006

CLC originalCLC refined

Current land-use

How does it work? Base map.









Definition of

Demands

Definition of

Demands

Definition and

implementation

of EU Policy

Alternatives

Definition and

implementation

of EU Policy

Alternatives


WORKFLOW OF LUMP

Glo

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Location spec. pref. add.

Location spec. pref. add.

Conversion settings

Conversion settings Factor DataFactor Data Neighbourhood

effectNeighbourhood

effectDemand scenarioDemand scenario





How does it work?


Conversion Settings:

It is possible to define which kind of transitions are allowed, given a certain land-use legend these transitions may be either natural (natural succession for vegetation growth, depending on CC parameters) or human-driven.

How does it work? Conversion allowances.


Source: Verburg and Overmars, 2009

How does it work? Natural succession.


Location specific preference addition:

• Scenario and policies settings (e.g. subsidies and taxes) influence these suitabilities;

• Each cell may be assigned a modification (location specific) of the suitability for a certain land use

• The change in suitability is different depending on the type of spatial policy and on the possible overlap of different policies.

How does it work? Subsidies and taxes.


Natura 2000 areas

High Nature Value areas Soil/Crop/Vegetation properties

Erosion sensitive areas Ecological corridors

Flood prone areas

Mean annual/seasonal temp. / precipit.

Upstream parts of catchments



Several policies are combined, according to a rule set

Natura2000

Green Infrastructures

Locspec for Forest



Factor Data

• EU-ClueScanner contains a wide range of spatial data sets that describe specific themes such as accessibility, geomorphology (elevation, slope, south slope), crop suitability (AGRI4CAST), forest species distribution (FOREST), climate, etc.;

• Depending on the source, the factor data are stored as tif files at both 1km and 100 m resolution.

How does it work? Biophysical suitability.


Neighbourhood effect

Land-use conversion can be partially explained by the occurrence of certain land-uses in the neighbourhood:

• Neighbourhood characteristics (size and shape) are assigned for each modelled land-use class;

• A weight of the neighbourhood function is also assigned, depending on the considered land-use class.

The neighbourhood function is active/non-active, depending on the consider neighbour land-use class.

How does it work? Neighborhood effects.


Conservation premium:

Any land-use change implies a certain cost: the latter can be interpreted as the ‘resistance’ that can be put up against that specific transition (conversion elasticities)

How does it work? Resistance to conversion.


OVERALL SUITABILITY

OVERALL SUITABILITY

Location Specific Preference Addition (LOCSPEC)

Location Specific Preference Addition (LOCSPEC)

Factor DataFactor Data Neighbourhood effectNeighbourhood effect

Conservation PremiumConservation Premium++ ++ ++

For each spatial (modelling) unit, the overall suitability is computed

Where:

i is the simulated land-use class in is the total number of simulated land-use classes

How does it work? Overall suitability.









Definition of

Demands

Definition of

Demands

Definition and

implementation

of EU Policy

Alternatives

Definition and

implementation

of EU Policy

Alternatives


Glo

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ontin

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Conversion settings

Conversion settings

Location specific drivers

Location specific drivers

Demand scenarioDemand scenario Factor DataFactor Data Neighbourhood

effectNeighbourhood

effect


Projected Land Use ChangeProjected Land Use Change

How does it work?


DIRECT OUTPUT OF EUCS:200520102015202020252030

Land use / land cover changeRASTERS

200520102015202020252030200520102015202020252030200520102015202020252030

Eu-ClueScanner output


Impact analysis:

Indicator models use information both derived from external models and the land allocation module to provide a balanced set of indicators focusing on the land-use and environmental domains.



These sector-specific models can either be integrated through a soft link, or hard-coded into the GeoDMS environment



Hardcoded, quantitative indicator: Agricultural abandonment

Agricultural abandonment hot spots:


Hardcoded, thematic indicator: Carbon sequestration

• Estimated carbon sequestration in ton C/km2

• Can be positive (sink) or negative (source) Based on EURURALIS approach using:

• Land use (modelling result) • Soil organic carbon (ESDB)• Age of land use (modelling result)• Emission factors (country and land-use specific)• Forest biomass content (based on model forest age)

Differentiated per:• observation year (e.g. 2010, 2020)• accumulation over preceding period

0

20

40

60

80

100

120

2000 2005 2010 2015 2020 2025 2030

Car

bo

n s

equ

estr

atio

n (

Tg

C/y

ear)

Reference

Biofuels no EU

Biofuels with EU


Mean Species AbundanceBased on GLOBIO3 concept using various data sets +

land use map output

Hardcoded, thematic indicator: Mean species abundance


Links and nodes are classified according to their level of importance

The best placement for new links to associate two different components can be proposed based on a series of criteria

Soft link between GUIDOS and EUCS:Habitat connectivity


Wh

at

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an

deri

ve f

rom

lan

d

use

Composite indicator for urban compactness, calculated for 305 large urban zones for the year 2000 with inset for northern Italy. (The urban morphological classes are overlain.)

Soft link between GUIDOS, R and EUCS: Urban morphology


0

1000

2000

3000

4000

5000

6000

8/1/2002 8/6/2002 8/11/2002 8/16/2002 8/21/2002 8/26/2002 8/31/2002

Dresden CLC2006

Dresden mxd2past

Dresden mxd2DUF

Summer

0

1000

2000

3000

4000

5000

6000

3/20/2006 3/25/2006 3/30/2006 4/4/2006 4/9/2006 4/14/2006 4/19/2006

Dresden CLC2006

Dresden mxd2past

Dresden mxd2DUF

Spring

Water quantity

Soft link between IDL, Lisflood and EUCS: Water quantity


• Why have one?



• Quiz


Model Calibration

• Regional calibration (NUTS 0, NUTS 1, NUTS 2 or any aggregation thereof)

• Calibration for biophysical suitability of terrain to host land use

• Calibration of neighborhood effects

• Both are based on multinomial logistic regression (automated in R)

• Model is re-calibrated for each application (changes in land use typology; regionalisation; input maps etc)


Proportion correct based on a pixel:pixel comparison of ref map : simulated map

The other 4 expressions give proportion correct if the simulated map is adjusted for quantity and/or location (for better or for worse)

From Pontius, Huffaker and Denman, 2004

Model Validation


Elbe vs Andalucia results

20 20 20 20 20 20

12 12 14 16 16 13

5646

5257 57 64

8

8

9

7 7 1414

60 0 2

0

10

20

30

40

50

60

70

80

90

100

CLC Elbe CLCAndalucia

CLC & CoCoElbe

CLC & CoCoAndalucia

CLC & CoCominmax

Andalucia

null

Pe

rce

nt o

f La

nd

sca

pe

chance agreement quantity agreement allocation agreement allocation disagreement quantity disagreement

•CoCo data greatly improves agreement in Andalucia•Results are same whether min/max are the same or min=MIN(CLC,CoCo) and max=MAX(CLC,CoCo)


Sector external models


CAPRICAPRI




Land-use based indicators:• Land-use maps• Change hotspots• Regional changes• Exposure to CC driven events

Land-use based indicators:• Land-use maps• Change hotspots• Regional changes• Exposure to CC driven events

Thematic indicators:• Water Quantity - Availability• Water Demand - Use• Adaptation Measures• …

Thematic indicators:• Water Quantity - Availability• Water Demand - Use• Adaptation Measures• …

Definition

of Land

Demands

Definition

of Land

Demands

Definition

and

implementation

of EU Policy

Alternatives

Definition

and

implementation

of EU Policy

Alternatives


Glo

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Conti

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Glo

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RHOMOLORHOMOLO GLIMPGLIMPLEITAP/IMAGELEITAP/IMAGE TRANSTOOLSTRANSTOOLS POLESPOLES GEM-E3

GEM-E3


Summary

RCMRCM

Adaptation Measures

Adaptation Measures


JRC models within Unit

Dynamic Land Allocation

Forestry Soil

JRC modelsoutside of Unit:

Water

Global Economicmodels

Demographic models

Demand for products and services

La

nd

allo

catio

n

Woo

d/no

n-woo

d pr

oduc

ts

dem

and

Water dem

and & managem

ent

Hydrological parameters

Agriculture

Transport

Energy

*Policy and the relevant indicators are sector-specific

…So

il pa

ram

ete

rsFores

t land

ava

ilabil

ity

Indicators*

Assessment of policy alternatives

Stakeholders

Land availability

Land demand


Quiz


Impact Analysis moduleLUMP - Components and Workflow

Integration with LISFLOOD for Water Quantity Management

a high resolution land use/cover modelling framework for europe: introducing the eu-cluescanner100...

Technology

land use changewhat

future land use

land use planning

land degradation

land usesoil

analysis of land use

historical land usecover

different land uses