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

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

A High Resolution Land use/cover Modelling Framework for Europe: introducing the EU-ClueScanner100 model
Carlo Lavalle, Claudia Baranzelli, Filipe Batista e Silva, Sarah Mubareka, Carla Rocha Gomes, - European Commission Joint Research Centre (Ispra, Italy)
Eric Koomen - Faculty of Economics and Business Administration, Vrije Universiteit Amsterdam
Maarten Hilferink - Object Vision, Vrije Universiteit Amsterdam

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  • Schematic representation. We started with simple schematic scheme, trying to include more and more complexity.
  • 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.
  • Schematic presentation of the EUClueScanner model. NB Economy, as to say Economic sectors models
  • Schematic presentation of the EUClueScanner model.
  • 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.
  • The rules depend upon the specific application.
  • Schematic presentation of the EUClueScanner model.
  • ..or emphasizing change through simple spatial statistics such as agricultural abandonment..
  • Indicators are powerful visual and statistical tools, which we like to emphasize can always be refined with the collaboration of experts!
  • 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.
  • 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!
  • 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
  • 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.
  • Transcript

    • 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.
      • Why have one?
      • How does it work?
      • Calibration and validation of model
      • Quiz
    • 3.
      • Why have one?
      • How does it work?
      • Calibration and validation of model
      • Quiz
    • 4.
      • 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)
      • I nterfacing 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
    • 5. Land Use Modelling : Examples of Potential Applications at JRC * (*) Answers to a survey launched by IES in 2009 Everyone needs a LUMP Theme Issue
      • Agriculture
        • Agro-Environment
        • Rural Development
        • Agro-Economy
      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 … …
    • 6.
      • 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)
      Everyone needs a LUMP
    • 7. Future Climate Global / 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 Impact Analysis Cost/Benefit Appraisal
    • 8.
      • Why have one?
      • How does it work?
      • Calibration and validation of model
      • Quiz
    • 9.
      • LUMP is a platform composed by 3 main modules :
        • Interfaces with sector-specific exogenous models
          • Demand for different land uses within different climate and economic contexts
        • 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
        • Impact assessment tools
          • Post-processing tools and indicators
      How does it work?
    • 10. 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
      • Land-use based indicators:
        • Land-use maps
        • Change hotspots
        • Regional changes
      • Thematic indicators:
        • Erosion
        • Carbon sequestration
        • Biodiversity
      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?
    • 11. Projected Land Use Change Policy-related suitabilities Location-specific suitabilities Current land-use Land-use Change Simulation Demand Module
      • Land-use based indicators:
        • Land-use maps
        • Change hotspots
        • Regional changes
      • Thematic indicators:
        • Erosion
        • Carbon sequestration
        • Biodiversity
      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?
    • 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. Land Demands: Industrial and commercial areas Holistic Regional Economic Model RHOMOLO
      • Forecasts 2020
      • GDP
      • Employment
      • Production
      Eurostat economic statistics Regional economic profiles Land demand for industrial and commercial areas Land use efficiency per region and per sector
    • 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. Projected Land Use Change Policy-related suitabilities Location-specific suitabilities Current land-use Land-use Change Simulation Demand Module
      • Land-use based indicators:
        • Land-use maps
        • Change hotspots
        • Regional changes
      • Thematic indicators:
        • Erosion
        • Carbon sequestration
        • Biodiversity
      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?
    • 17. Based on Corine Land Cover 2006 Flexible 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.
    • 18. Refinement of the Corine Land Cover 2006 Current land-use How does it work? Base map. CLC original CLC refined
    • 19. Projected Land Use Change Current land-use Land-use Change Simulation Demand Module
      • Land-use based indicators:
        • Land-use maps
        • Change hotspots
        • Regional changes
      • Thematic indicators:
        • Erosion
        • Carbon sequestration
        • Biodiversity
      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?
    • 20.
      • 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.
    • 21. Source: Verburg and Overmars, 2009 How does it work? Natural succession.
    • 22.
      • 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.
    • 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.
        • Several policies are combined, according to a rule set
      How does it work? Subsidies and taxes.
        • Natura2000
        • Green Infrastructures
        • Locspec for Forest
    • 25.
      • 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.
    • 26.
      • 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.
    • 27.
      • 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.
    • 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. Projected Land Use Change Current land-use Land-use Change Simulation Demand Module
      • Land-use based indicators:
        • Land-use maps
        • Change hotspots
        • Regional changes
      • Thematic indicators:
        • Erosion
        • Carbon sequestration
        • Biodiversity
      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?
    • 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.
      • These sector-specific models can either be integrated through a soft link, or hard-coded into the GeoDMS environment
      Eu-ClueScanner output
    • 33. Hardcoded, quantitative indicator: Agricultural abandonment Agricultural abandonment hot spots:
    • 34. 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
    • 35.
      • Mean Species Abundance
      • Based on GLOBIO3 concept using various data sets + land use map output
      Hardcoded, thematic indicator: Mean species abundance
    • 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.
      • Why have one?
      • How does it work?
      • Calibration and validation of model
      • Quiz
    • 40. 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)
    • 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. Elbe vs Andalucia results
      • 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)
    • 43. Sector external models Projected Land Use Change CAPRI Policy-related suitabilities Location-specific suitabilities Current land-use Land-use Change Simulation Demand Module
      • 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
      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
    • 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.
      • Quiz
    • 46. Impact Analysis module LUMP - Components and Workflow Integration with LISFLOOD for Water Quantity Management