1. 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
2. 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.
3. 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.
4. 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
5. 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.
6. 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.
7. 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…
8. System Dynamic
System Dynamic
Conceptual Model of
Conceptual Model of
Desertification (LU)
Desertification (LU)
Predator-Prey based approach
Predator-Prey based approach
9. 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
10. PESERA/RDI (1 km) & PATTERN-LEIS (30-100 m) Land Condition Modelling
PESERA/RDI (1 km) & PATTERN-LEIS (30-100 m) Land Condition Modelling
11. 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
12. 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
13. 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
14. 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
15. 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.
16. 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)
17. 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