Transcript powerpoint slides

An Internet Tool For Forecasting Land
Use Change And Land Degradation
In The Mediterranean Region
Richard Kingston & Andy Turner
University of Leeds
UK
The presentation
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Some background
The problem
Aims and objectives
Work packages
Building a common spatial framework
Land use predictors
Building the web interface
Conclusions & next stages
Background
• MedAction funded by the EU
– Fifth framework program
– Key Action 2: Energy, Environment and
Sustainable Development
• Specifically looking at:
– Policies for land use to combat
desertification
http://www.icis.unimaas.nl/medaction/
The problem
• Increasing desertification in the
Mediterranean region is having a direct
impact upon land use
• It is largely a society-driven problem
combated by various EC agricultural
subsidies
• A lack of coordinated action across the
Mediterranean has led to a patchwork of
policy actions
Overall aims and objectives
• The EC have decided that we need to:
– Develop land use change scenarios at various
scales
– Analyse effects of past policies in four target areas
– Analyse the costs of land degradation and benefits
of mitigation measures
– Develop options for land use policies, mitigation
strategies, and incentives to combat desertification
Specific aims and objectives
• Develop a scenario based integrated land
use and land degradation prediction model
• Develop an interactive internet interface to
the modelling system and associated data
• Encourage experts, policy makers and the
public to use the on-line modelling system
and develop the way it operates, its
functionality and its capabilities based on
feedback from these users
Work Packages
Interconnections between MEDACTION Modules and Work Packages
M1 Development of land use change
scenarios at various scales (pressure)
WP 1.1
European and
Mediterranean
scenarios
our
work
WP 1.2
Regional scenarios
WP 4.5
Focus groups
on land management
and mitigation
M3 Effects of regional land use
scenarios in target areas (state)
M2 Effects of past land use policies
in target areas (impact)
WP 3.1
Decision
Support
System
Alentejo,
Agri
WP 3.2
Policy
Support
System
Lesvos,
Guadalentín
M4 Integrated policy development
to combat desertification (response)
WP 3.3
Internet tool for
(EU) planners
WP 4.1-4.3
Policy analysis at European scale
WP 4.4
Synthesis
Development and communication of a
Desertification Policy Guidance Framework
WP 1.3
Integrated
cost-benefit analysis
at various scales
WP 2.1-2.6
Comparative
analysis
of policy
impacts on
desertification
Work Package 3.3
• Develop an internet interface to an
existing stand-alone modelling system
that
– allows users to select which variables to
include
– enables them to try out different types of
model
– search for and evaluate available data with
respect to the modelling tasks
Previous research
• Developed a means of estimating the likely
impacts of climate change on agricultural land
use and land degradation
• In order to
– gain and raise awareness of the problems
– inform political and public debate
– have a way of contributing to the development of
mitigation strategies
Previous modelling challenge
• To predict contemporary agricultural land use
based on a range of climatic, physical and socioeconomic indicators
• Forecast the various indicators for some time in
the future in order to forecast land use and
provide a land use change scenario
• Translate land use change scenarios into land
degradation indicators
• Combine land degradation indicators to produce
a synoptic forecast of land degradation
What was required
• Highest possible level of spatial resolution
• Complete coverage over the Mediterranean climate region
of the EU
• Produce forecasts for about 50 years hence
• Base the results on global climate change scenarios
• Incorporate socio-economic data
• Produce outputs as maps
• Provide a modelling framework that could be refined as
better data and understanding of the processes is gained
• something we are doing now
Creating the common spatial
framework
• Step 1: Assemble a database of all relevant physical,
socio-economic & environmental data
• Step 2: Model the relationships between land use
and other data assembled
• Step 3: Obtain and make forecasts of the data
• Step 4: Create and analyse maps of changes
• Step 5: Translate the changes into land degradation
risk indicators
• Step 6: Repeat forecasting based on different climate
change scenarios
Assembling the data
• Decided upon a grid at a 1-decimal-minute
resolution with a fixed origin aligned in terms of
latitude and longitude covering the entire
Mediterranean climate region of the EU
• Manipulating available source data into the
framework involved the use of GIS operations
and/or modelling applications
– Most environmental data could be manipulated into it
in a relatively straight forward manner
– BUT... socio-economic data need to be interpolated
The land use predictors
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soil type
soil quality
biomass
temperature
precipitation
height above sea level
population density
Climatic Biomass Potential
Height above Sea level
Predicting future land use
• An example rule
• If a high proportion of land use
estimated/predicted now is arable and a
high proportion of estimated/forecast
future land use is:
arable then land degradation is possible
trees then land degradation is unlikely
barren then land degradation is serious
other land use then land degradation is probable
Building a web interface
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WP 3.3 main aim is to develop a Web
interface to the existing stand-alone
prototype modelling system
– allow the viewing of available input data
and existing model results
– allow users to alter climate change
scenarios and input data and view the
effects on land use change and land
degradation
Work so far
• On-line data viewer
– allows users to view relevant spatial data
– meta data
• Developing web-based GIS
– allows users to decide on input variables
– model type
Step 1: Choose data and view in the on-line map viewer
Step 2: Run model
choose between model types
Step 5: Run another scenario?
Neural Net
Fuzzy Logic
Step 3: Obtain Results
Not Satisfied?
Satisfied?
Step 4: Submit Results to
policy makes
Datasets library
• Split into
– socio-economic land use predictors
• e.g. distance to nearest built-up area
• e.g. frequency of night-time lights observation
– physical land use predictors
• e.g. soil type
• e.g. biomass data
The Data Viewer
• Extracts relevant gif image and
associated meta data
– drop down lists of data types
– data for
• now
• 50 years in the future
Web enabled GIS
• Developing in house GIS
– Java based open source
– vector and raster capabilities
– runs on the Web or stand alone
• http://mapkenzie.sourceforge.net/
The modelling interface
• After using the data library users then
– select which variables to include
– enables them to try out different types of model
• Neural networks for classification
• Fuzzy logic based for subjective interpretation
– view results
– re-run with different data-sets and/or models
• The modelling interface still has to be
developed!
Here’s an example from some previous work
Next stages
• Update the system with new
– socio-economic
– environmental
– physical data
• Develop the Web-based interface
• Develop the modelling system
• Allow users to add their own data
Conclusions
• This work is still in its early stages
• Results will only be good enough to enlighten debate –
not control policy
• It is a first step towards providing wider access to land
degradation data and models
• It has the potential to open up the decision making
process to those who are interested
• It provide an example web-based tool for planners,
decision makers and citizens interested in visualising
the consequences of environmental change
Further details
MedAction
http://www.ccg.leeds.ac.uk/medaction/
[email protected]
[email protected]
Java GIS
http://geotools.sourceforge.net/
http://mapkenzie.sourceforge.net/
Other examples
http:/www.ccg.leeds.ac.uk/atomic/