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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 Unit Institute for Environment and Sustainability Joint Research Center
[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],WHAT IS LUMP? Everyone needs a LUMP
Land Use Modelling : Examples of Potential Applications at JRC * (*) Answers to a survey launched by IES in 2009  Everyone needs a LUMP Theme Issue ,[object Object],[object Object],[object Object],[object Object],Assessment of current and potential agricultural area and cultivation use Assessment of CAP impacts on future land use.  CAP, climate change, macro/micro economic Environmental 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 forest Exposure and vulnerability Analysis Definition 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 … …
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Everyone needs a LUMP
Future Climate Global / Regional  Climate Models ,[object Object],[object Object],[object Object],[object Object],Risk Prevention  (adaptation) Current Climate, Soil, Vegetation Socio-economic  Trends & Scenarios Land Use   MOLAND EuClueScanner Emission scenarios  (IPCC SRES) LUMP framework Impact Analysis Cost/Benefit Appraisal
[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],How does it work?
Projected Land Use Change External drivers for land-use changes Policy-related suitabilities Location-specific suitabilities Current  land-use Land-use Change Simulation Demand Module ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Definition of Demands Definition and implementation of EU Policy Alternatives Impact analysis Global/Continental scenarios Demand settings demand case land-use case Demand scenario How does it work?
Projected Land Use Change Policy-related suitabilities Location-specific suitabilities Current  land-use Land-use Change Simulation Demand Module ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Definition of Demands Definition and implementation of EU Policy Alternatives Impact analysis Global/Continental scenarios land-use case Demand scenario Demography/Population projections Economic Models Demand settings Demand scenario demand case How does it work?
Historical  Land Use/Cover ,  U t  =  1990;2000;2006 Land Demands:  Urban fabric (residential areas) Historical  Population ,   P  (Eurostat) t  =  1990;2000;2006 NUTS 2 regions  i Historical  population density ,   D
Land Demands:  Industrial and commercial areas Holistic Regional Economic Model  RHOMOLO ,[object Object],[object Object],[object Object],[object Object],Eurostat  economic statistics Regional economic profiles Land demand for industrial and commercial areas Land use efficiency per region and per sector
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) EU-wide agriculture sector modelling system CAPRI  ( forecast 2020 ) 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 crop groups per  NUTS 2 region
Historical statistics on forest related products Land Demands:  Forest areas Trends in historical forest land use from Corine (1990-2006) and Forest Map 2006 Wood/Non-Wood product economic modelling  ( EFSOS, OECD, .. ) Harvest demand -> Minimum and maximum trends in land claims per main forest species/typologies In progress .. (Ref. AA with CLIMA) Land demand for main forest typologies per  Country
Projected Land Use Change Policy-related suitabilities Location-specific suitabilities Current  land-use Land-use Change Simulation Demand Module ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Definition of Demands Definition and implementation of EU Policy Alternatives Impact analysis Global/Continental scenarios land-use case Demand scenario demand case Economy Demography/Population projections Demand settings How does it work?
Based on Corine Land Cover 2006 Flexible legend/nomenclature ,[object Object],[object Object],[object Object],[object Object],Current land-use How does it work?  Base map.
Refinement of the Corine Land Cover 2006 Current land-use How does it work? Base map. CLC original CLC refined
Projected Land Use Change Current  land-use Land-use Change Simulation Demand Module ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Definition of Demands Definition and implementation of EU Policy Alternatives Impact analysis WORKFLOW OF LUMP Global/Continental scenarios demand case Location spec. pref. add. Conversion settings Factor Data Neighbourhood effect Demand scenario land-use case Economy Demography/Population projections Demand settings How does it work?
[object Object],[object Object],How does it work? Conversion allowances.
Source: Verburg and Overmars, 2009 How does it work? Natural succession.
[object Object],[object Object],[object Object],[object Object],How does it work? Subsidies and taxes.
Erosion sensitive areas How does it work? Subsidies and taxes. Natura 2000 areas High Nature Value areas Soil/Crop/Vegetation properties Ecological corridors Flood prone areas Mean annual/seasonal temp. / precipit. Upstream parts of catchments
[object Object],How does it work? Subsidies and taxes. ,[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],How does it work? Biophysical suitability.
[object Object],[object Object],[object Object],[object Object],[object Object],How does it work? Neighborhood effects.
[object Object],[object Object],How does it work? Resistance to conversion.
OVERALL SUITABILITY Location Specific Preference Addition (LOCSPEC) Factor Data Neighbourhood effect Conservation Premium + + + For each spatial (modelling) unit, the overall suitability is computed Where: i  is the simulated land-use class  i n  is the total number of simulated land-use classes How does it work? Overall suitability.
Projected Land Use Change Current  land-use Land-use Change Simulation Demand Module ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Definition of Demands Definition and implementation of EU Policy Alternatives Impact analysis Global/Continental scenarios demand case Economy Demography/Population projections Demand settings Conversion settings Location specific drivers Demand scenario Factor Data Neighbourhood effect land-use case Projected Land Use Change How does it work?
DIRECT OUTPUT OF EUCS: Land use / land cover change RASTERS Eu-ClueScanner output 2005 2010 2015 2020 2025 2030 2005 2010 2015 2020 2025 2030 2005 2010 2015 2020 2025 2030 2005 2010 2015 2020 2025 2030
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. Eu-ClueScanner output
[object Object],Eu-ClueScanner output
Hardcoded, quantitative indicator:  Agricultural abandonment Agricultural abandonment hot spots:
Hardcoded, thematic indicator:  Carbon sequestration ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],Hardcoded, thematic indicator:  Mean species abundance
Soft link between GUIDOS and EUCS: Habitat connectivity 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, R and EUCS: Urban morphology What we can derive from land 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 IDL, Lisflood and EUCS: Water quantity Water quantity Summer Spring
[object Object],[object Object],[object Object],[object Object]
Model Calibration ,[object Object],[object Object],[object Object],[object Object],[object Object]
From Pontius, Huffaker and Denman, 2004 Model Validation 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)
Elbe vs Andalucia results ,[object Object],[object Object]
Sector external models Projected Land Use Change CAPRI Policy-related suitabilities Location-specific suitabilities Current  land-use Land-use Change Simulation Demand Module ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Definition of Land Demands Definition and implementation of EU Policy Alternatives Impact analysis Global/Continental scenarios Demand scenario RHOMOLO GLIMP LEITAP/IMAGE TRANSTOOLS POLES GEM-E3 Demand settings Summary RCM Adaptation Measures
JRC models within Unit Dynamic Land Allocation Forestry Soil JRC models outside of Unit: Water Global  Economic models Demographic  models Demand for products  and services Land allocation Wood/non-wood products demand Water demand & management Hydrological parameters Agriculture Transport Energy Regional Policy Alternatives* *Policy and the relevant indicators are sector-specific  … Soil parameters Forest land availability Indicators* Assessment of  policy alternatives Stakeholders Land availability Land demand
[object Object]
Impact Analysis module LUMP - Components and Workflow Integration with LISFLOOD for Water Quantity Management

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A High Resolution Land use/cover Modelling Framework for Europe: introducing the EU-ClueScanner100 model

  • 1. 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 Unit Institute for Environment and Sustainability Joint Research Center
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11.
  • 12. Historical Land Use/Cover , U t = 1990;2000;2006 Land Demands: Urban fabric (residential areas) Historical Population , P (Eurostat) t = 1990;2000;2006 NUTS 2 regions i Historical population density , D
  • 13.
  • 14. 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) EU-wide agriculture sector modelling system CAPRI ( forecast 2020 ) 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 crop groups per NUTS 2 region
  • 15. Historical statistics on forest related products Land Demands: Forest areas Trends in historical forest land use from Corine (1990-2006) and Forest Map 2006 Wood/Non-Wood product economic modelling ( EFSOS, OECD, .. ) Harvest demand -> Minimum and maximum trends in land claims per main forest species/typologies In progress .. (Ref. AA with CLIMA) Land demand for main forest typologies per Country
  • 16.
  • 17.
  • 18. Refinement of the Corine Land Cover 2006 Current land-use How does it work? Base map. CLC original CLC refined
  • 19.
  • 20.
  • 21. Source: Verburg and Overmars, 2009 How does it work? Natural succession.
  • 22.
  • 23. Erosion sensitive areas How does it work? Subsidies and taxes. Natura 2000 areas High Nature Value areas Soil/Crop/Vegetation properties Ecological corridors Flood prone areas Mean annual/seasonal temp. / precipit. Upstream parts of catchments
  • 24.
  • 25.
  • 26.
  • 27.
  • 28. OVERALL SUITABILITY Location Specific Preference Addition (LOCSPEC) Factor Data Neighbourhood effect Conservation Premium + + + For each spatial (modelling) unit, the overall suitability is computed Where: i is the simulated land-use class i n is the total number of simulated land-use classes How does it work? Overall suitability.
  • 29.
  • 30. DIRECT OUTPUT OF EUCS: Land use / land cover change RASTERS Eu-ClueScanner output 2005 2010 2015 2020 2025 2030 2005 2010 2015 2020 2025 2030 2005 2010 2015 2020 2025 2030 2005 2010 2015 2020 2025 2030
  • 31. 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. Eu-ClueScanner output
  • 32.
  • 33. Hardcoded, quantitative indicator: Agricultural abandonment Agricultural abandonment hot spots:
  • 34.
  • 35.
  • 36. Soft link between GUIDOS and EUCS: Habitat connectivity 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
  • 37. Soft link between GUIDOS, R and EUCS: Urban morphology What we can derive from land 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.)
  • 38. Soft link between IDL, Lisflood and EUCS: Water quantity Water quantity Summer Spring
  • 39.
  • 40.
  • 41. From Pontius, Huffaker and Denman, 2004 Model Validation 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)
  • 42.
  • 43.
  • 44. JRC models within Unit Dynamic Land Allocation Forestry Soil JRC models outside of Unit: Water Global Economic models Demographic models Demand for products and services Land allocation Wood/non-wood products demand Water demand & management Hydrological parameters Agriculture Transport Energy Regional Policy Alternatives* *Policy and the relevant indicators are sector-specific … Soil parameters Forest land availability Indicators* Assessment of policy alternatives Stakeholders Land availability Land demand
  • 45.
  • 46. Impact Analysis module LUMP - Components and Workflow Integration with LISFLOOD for Water Quantity Management

Notas do Editor

  1. Schematic representation. We started with simple schematic scheme, trying to include more and more complexity.
  2. Schematic presentation of the EUClueScanner model. I leave the definition of scenarios turned on because is something to be ware of all along the modelling process. Its exact configuration is case study specific while the overall modelling approach is generic and similar in various applications.
  3. Schematic presentation of the EUClueScanner model. NB Economy, as to say Economic sectors models
  4. Schematic presentation of the EUClueScanner model.
  5. The CLUE model is based on the dynamic simulation of competition between land uses. Its spatial allocation rules are based on a combination of empirical analysis of current land use patterns, neighbourhood characteristics and scenario-specific decision rules. It combines the top-down allocation of land use change at national/regional level for all EU Member States to regular either 1km×1 km or 100mx100m grid cells with a bottom-up determination of conversions for specific land use transitions.
  6. The rules depend upon the specific application.
  7. Schematic presentation of the EUClueScanner model.
  8. ..or emphasizing change through simple spatial statistics such as agricultural abandonment..
  9. Indicators are powerful visual and statistical tools, which we like to emphasize can always be refined with the collaboration of experts!
  10. Using proxies, we are testing indicators that may seemingly not be calculable from land use model output such as biodiversity, carbon sequestration, soil erodability, river discharge (flood risk) etc.
  11. Again with GUIDOS, we are able to create composite indicators and derive output very quickly for all questions related to morphology, even built up area spatial metrics can be incorporated!
  12. Throughout the various phases of the Lisflood model modifications, the river discharge was used as a parameter to measure sensitivity We look at different events (floods, water stress) and different seasons
  13. Schematic presentation of the EUClueScanner model. I leave the definition of scenarios turned on because is something to be ware of all along the modelling process. Its exact configuration is case study specific while the overall modelling approach is generic and similar in various applications.