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desertification

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De Survey De Survey Presentation Transcript

  • European Commission A Surveillance System for 6th Framework Programme: Assessing and Monitoring Desertification Global Change & Ecosystems. www.desurvey.net Integrated Project Contract No. 003950 DeSurvey: A Surveillance System for Assessing, DeSurvey: A Surveillance System for Assessing, Monitoring and Forecasting of Desertification Monitoring and Forecasting of Desertification •• Interdisciplinary research 2005-2010 Interdisciplinary research 2005-2010 •• 39 partners (>90 scientists), 39 partners (>90 scientists), •• EU contribution: 7.8 M€ EU contribution: 7.8 M€ •• Belgium, France, Germany, Greece, Holland, Italy, Belgium, France, Germany, Greece, Holland, Italy, Portugal, Spain, Sweden, UK, Algeria, Morocco, Portugal, Spain, Sweden, UK, Algeria, Morocco, Senegal,Tunisia, Chile, China, Senegal,Tunisia, Chile, China, DeSurvey is considering the interaction and importance of socio-economy, climate and DeSurvey is considering the interaction and importance of socio-economy, climate and landssystem vulnerability to land degradation landssystem vulnerability to land degradation
  • DeSurvey objectives DeSurvey objectives •• Understanding of desertification in aasystemic and dynamic Understanding of desertification in systemic and dynamic manner; manner; •• Monitoring and assessment of desertification and land Monitoring and assessment of desertification and land degradation status over large areas using objective and degradation status over large areas using objective and reproducible methods, including diagnosis of driving forces; reproducible methods, including diagnosis of driving forces; •• Discriminating between current and inherited desertification, and Discriminating between current and inherited desertification, and the identifying of desertification hot spots; the identifying of desertification hot spots; •• Forecasting of desertification under selected climatic and socio- Forecasting of desertification under selected climatic and socio- economic scenarios; economic scenarios; •• Bridging the gap between scientific knowledge generated by the Bridging the gap between scientific knowledge generated by the project on the processes underlying desertification and the project on the processes underlying desertification and the practice of formulating policy and management action to detect, practice of formulating policy and management action to detect, prevent and resolve desertification risks. prevent and resolve desertification risks.
  • DeSurvey modelling approach DeSurvey modelling approach •• Spatially explicit cellular modelling of climate and socio-economic forcing Spatially explicit cellular modelling of climate and socio-economic forcing impacts on land condition and land claims in land use systems. A feedback impacts on land condition and land claims in land use systems. A feedback loop between land condition and land use spatial allocation will enable loop between land condition and land use spatial allocation will enable dynamic time projections. dynamic time projections. •• Predator-prey based systems modelling of Land Use Systems Vulnerability. Predator-prey based systems modelling of Land Use Systems Vulnerability.
  • Operating modules •• Climate forcing. Climate forcing. •• Water resources condition Water resources condition assessment. assessment. •• Socio-economic forcing. Socio-economic forcing. •• Data and information systems. Data and information systems. •• Land-use systems vulnerability. Land-use systems vulnerability. •• Integration and validation. Integration and validation. •• Ground-based land condition Ground-based land condition assessment and forecasting. assessment and forecasting. •• Innovation related activities. Innovation related activities. •• Integrated remote sensing and Integrated remote sensing and •• Project monitoring, evaluation, Project monitoring, evaluation, geomatics approaches for the geomatics approaches for the contingency planning and contingency planning and assessment and monitoring of assessment and monitoring of management management land surface conditions. land surface conditions. •• Training, demonstrations Training, demonstrations
  • DeSurvey spatial resolutions DeSurvey spatial resolutions The DeSurvey System will be designed to run at The DeSurvey System will be designed to run at three spatial resolution levels: three spatial resolution levels: •• (i) Coarse resolutions (~ 8 km or province-NUT (i) Coarse resolutions (~ 8 km or province-NUT equivalents) for preliminary surveys at the global- equivalents) for preliminary surveys at the global- multi national regional scale; multi national regional scale; •• (ii) Standard resolutions (~ 1 km) for national-sub (ii) Standard resolutions (~ 1 km) for national-sub national regional applications; national regional applications; •• (iii) Fine resolutions (~ 30 m) for local applications. (iii) Fine resolutions (~ 30 m) for local applications.
  • EU DeSurvey research target areas EU DeSurvey research target areas Target areas of moderate size (~ 1000 – Target areas of moderate size (~ 1000 – 5000 km22)are selected and used for three 5000 km ) are selected and used for three purposes: purposes: •• (i) development and parameterisation of (i) development and parameterisation of models that evaluate land use and land models that evaluate land use and land degradation changes as well as vulnerability degradation changes as well as vulnerability of land use systems to desertification; of land use systems to desertification; •• (ii) validation of the DESURVEY (ii) validation of the DESURVEY surveillance and assessment procedures, surveillance and assessment procedures, and; and; •• (iii) demonstration of the DESURVEY (iii) demonstration of the DESURVEY System’s performance. System’s performance.
  • Desertification Indicator(s) ? Desertification Indicator(s) ? Dear members of DeSurvey, Dear members of DeSurvey, Desertification is defined by the UN as land N=65*2 degradation in arid, semi arid the UN as land Desertification is defined by and sub-humid lands. Degradation impliesarid and sub-humid degradation in arid, semi the reduction of the resource potential ofimplies the reduction of the lands. Degradation the landscape through different processes.of the landscape through resource potential different processes. Assume desertification can be described Assume desertification can be described numerically through system dynamics modelling in terms of aathrough systemstock" withmodelling numerically key "resource stock" with inflows dynamics in terms of key "resource inflows (growth/production/ reproduction) and outflows (growth/production/ reproduction) and outflows (consumption of resources). (consumption of resources). A higher consumption (outflow) than production A) Soil water storage A) Soil water storage (inflow) may lead to some kind of than production A higher consumption (outflow) system crash B) Ground water storage or at least to alead to someresource reproduction (inflow) may decreasing kind of system crash B) Ground water storage andataleast to a decreasing resource reproduction or a reduced potential, possibly involving C) Soil (erosion modelling, e.g. soil depth &/or C) Soil (erosion modelling, e.g. soil depth &/or and reduced potential, possibly involving accelerated land degradation. nutrient status ) ) accelerated land degradation. nutrient status D) Green & woody biomass (natural & crops This may take place through the development of D) Green & woody biomass (natural & crops productivity) one or several feed back loops reinforcing the of This may take place through the development productivity) degradation/desertification to aareinforcing itit will one or several feed back loops level where the degradation/desertification to level where will be difficult to stop. E) Vegetation fractional cover (canopy and field E) Vegetation fractional cover (canopy and field be difficult to stop. cover) cover) Assume YOU have to do the modelling and that F) Human population F) Human population YOU haveYOUpick THEdo the modelling andthat Assume to pick THE key variable (stock) that have to that G) Household income YOU have toa surrogate forvariable (stock) key desertification! would act as a surrogate for desertification! G) Household income would act as H) Rural/urban standard of living H) Rural/urban standard of living Which variable would you choose? Which variable would you choose? I)I) Livestock density Livestock density J) I I have no idea what you are talking about J) have no idea what you are talking about K) Suggested alternatives...(desertification is aa K) Suggested alternatives...(desertification is syndrome… syndrome…
  • System Dynamic System Dynamic Conceptual Model of Conceptual Model of Desertification (LU) Desertification (LU) Predator-Prey based approach Predator-Prey based approach
  • RIKS’ Cellular Automata Land Use Change Model to allocate growth to the individual 1 km plot Land use change is modelled; EU-Region consists of a grid with +/- 4 million 1 km2 cells; Overall growth and land claim of each land use function is determined at NUTS 3 level Neighbourhood 8 cell-radius, 196 cells; Identical and coupled CA models, 1 per NUTS 3 region; Max. 32 land-use classes, some dynamic, some static; Indikatoren CA develops in a space defined by Suitability, Zoning and Infrastructure. Zeitliche Veränderungen Spezielle Forschungs- RIKS aspekte research institute for knowledge systems 1989 2030 Social & economic macro- and micro- processes drive land condition models Social & economic macro- and micro- processes drive land condition models
  • PESERA/RDI (1 km) & PATTERN-LEIS (30-100 m) Land Condition Modelling PESERA/RDI (1 km) & PATTERN-LEIS (30-100 m) Land Condition Modelling
  • Current climate: January Expected changes in erosion due to global climate changes: More erosion, especially in Winter if land use is unchanged Hadley Centre 2080 scenario: January
  • MEDOKADS, NASA/GIMMS, MEDOKADS, NASA/GIMMS, TERRA/MODIS (250, 500,1k), TERRA/MODIS (250, 500,1k), Pathfinder, Landsat, NDVI time Pathfinder, Landsat, NDVI time series for biomass anomaly trend series for biomass anomaly trend studies with climate analysis studies with climate analysis NDVI (AVHRR) and rainfall NDVI (AVHRR) and rainfall (GPCP, 2.50, ,~275 km) anomalies (GPCP, 2.50 ~275 km) anomalies for 55random years during the for random years during the 1982 to 2002 period. 1982 to 2002 period. Lund university-07
  • Linear trends in vegetation Linear trends in vegetation productivity for the period 1982 to productivity for the period 1982 to 2002 based on annual integrated NDVI 2002 based on annual integrated NDVI values. The trend is expressed as values. The trend is expressed as percentages i.e. the relative difference percentages i.e. the relative difference between the start and the end value of between the start and the end value of the linear trend. the linear trend. Map of the correlation coefficients of Map of the correlation coefficients of NDVI anomalies with Rainfall NDVI anomalies with Rainfall anomalies for the period 1982 to 2002. anomalies for the period 1982 to 2002. Lund university-07
  • Spatio-temporal Indicators, High resolution data, Univ of Trier Veg. [%] 1997 y = a + b*x year 1994 1993 1991 Satellite- Estimated 1989 Vegetation Abundance 1972 uh-07
  • DeSurvey outputs DeSurvey outputs The main outputs of the project will be: The main outputs of the project will be: •• DeSurvey Desertification Surveillance system tailored to end- DeSurvey Desertification Surveillance system tailored to end- user information needs. user information needs. •• Application examples of desertification assessment and its Application examples of desertification assessment and its performance at national scales in Portugal, Spain, Italy and Greece. performance at national scales in Portugal, Spain, Italy and Greece. •• Application examples of desertification assessment and its Application examples of desertification assessment and its performance at the sub-national scales in 5 European areas and in performance at the sub-national scales in 5 European areas and in Morocco, Algeria, Tunisia, Senegal, China and Chile. Morocco, Algeria, Tunisia, Senegal, China and Chile. •• Algorithms for deriving system-based indicators of discontinuities Algorithms for deriving system-based indicators of discontinuities and breakpoints in the expected trajectories of threatened areas. and breakpoints in the expected trajectories of threatened areas. •• Databases and information systems to run DESURVEY in the afore- Databases and information systems to run DESURVEY in the afore- mentioned areas. mentioned areas. •• Two courses for increasing capacity of postgraduate specialists in Two courses for increasing capacity of postgraduate specialists in desertification surveillance and training them in DESURVEY desertification surveillance and training them in DESURVEY implementation and use. implementation and use.
  • DeSurvey core products; end of 2007 DeSurvey core products; end of 2007 •• A monitoring system based on spatially A monitoring system based on spatially distributed one-a- time land condition distributed one-a- time land condition assessment repeated through time (remote assessment repeated through time (remote sensing & field surveys; socio-economy/land use sensing & field surveys; socio-economy/land use and biomass) and biomass) •• A forecasting system delivering time A forecasting system delivering time projections of spatially distributed land condition projections of spatially distributed land condition (i.e. economy driven land condition modelling; (i.e. economy driven land condition modelling; land use & erosion) land use & erosion) •• An assessment of stability conditions of the An assessment of stability conditions of the desertification syndromes occurring in the areas desertification syndromes occurring in the areas of interest (i.e. ”predator-prey” based system of interest (i.e. ”predator-prey” based system dynamic modelling of vulnerability, stress, dynamic modelling of vulnerability, stress, equilibrium conditions & desertification) equilibrium conditions & desertification)
  • DeSurvey complementary needs: Additional partners to represent and validate all syndromes; additional focus on bio-diversity and socio-economy Prepared plans & partners: Sudan, Argentina, Niger, Uzbekistan, South Africa, China