UCD UII Summer SchoolLand-use modelling for sustainable policy making
Dublin, 18 June 2009
BIOPatricia Benito
1. Background
2. Policy perspective
3. Designing a modelling tool for sustainable policy making
4. Existing modelling tools and comparison
5. Recent application of land use modelling tools in policy making
6. Achievements and drawbacks
7. Current and future work
8. General conclusions
Agenda
2
3
What can science do to support policy?
Advocacy Synthesise information to take a position
Decision-making Provide a specific answer using multi-criteria analysis
Ex-ante analysis
Ex-post analysis
Communication Orderly laying out of arguments for easy understanding
Newsletters
Assessment of the state of the art knowledge
Background (1/6)Science-policy linkage (1/3)
4
How does science support policy?
Provides insights
Cross-sector Impacts of water scarcity on citizens/economy/biodiversity/water quality/etc.
Cross-policy Natura 2000 and its relationship with other initiatives and policies which serve to protect biodiversity
Support for decision-making
The answer is not known: policy assessment EIA of different technical amendments for a possible review of the IPPC– EC DG ENV, 2005-07
EIA of concrete policy response options for the scheduled 'White Paper on adapting to
climate change impacts' – EC DG ENV, 2008
The answer is known: justification The value of biodiversity (economic impacts of biodiversity loss and ecosystem
services loss – EC DG ENV, 2006
Development of tools Comparative analysis of policy options Developing and implementing a land-use modelling framework – European Commission DG ENV, 2009
Background (2/6)Science-policy linkage (2/3)
5
Challenges of linking science and policy
Many differences
Languages
Time spans
Approach to problem solving
Science - best possible solution vs Policy - most feasible solution
Often leads to conflicts
Conflicts
(Science precise vision vs Policy macro vision)
Opaque
Background (3/6)Science-policy linkage (3/3)
6
Land can be considered as a limited resource
Land-use changes alter environmental structures and processes and impact socio-
economic development
Conflict between need for land and the capacity of land to absorb and support this
need
Policy is one of the key drivers leading to land-use change but it is also one of the
responses of society to observed negative land-use patterns
EU Sustainable Development Strategy requires the integration of economic, social
and environmental issues across policy areas
Understanding the links between land-use choices and their potential impacts and
the quantification of these impacts is crucial for the development of sustainable
policies
Background (4/6)Needs for quantitative modelling
7
Key drivers of land use change:
Demography An increase in population results in an increased demand for housing
and other facilities.
Economy A booming economy results in construction of new commercial and
industrial buildings. Further, economic growth can generate new jobs and thus attracts
more workers, leading to population growth, and construction of new houses and
infrastructure.
Society Changes in the attitudes and values of people have considerable impact on
land-use patterns. E.g. Household size .
Politics National, regional, and local planning and policies influence greatly the rate
at which land-use and land-cover changes.
Technology Technological developments influence the intensity of activities, which
can alter the usefulness and demand for different types of lands. E.g. agricultural
mechanisation, improvements in methods of converting biomass into energy, use of
information-processing technologies in crop and pest management.
Background (5/6)Key drivers of land-use change (1/2)
8
Key drivers of land use change over the next 25 years:
Reorientation of the Common Agricultural Policies (CAP)
Changes in the supply and prices of agricultural commodities
EU energy policies, including biofuel policies
Ongoing technological developments in the agriculture and energy sectors
Climate change through direct effects on weather conditions
A global increase in demand for bioenergy feedstocks
An expanding global population (food and space requirements)
Changing consumptions patterns both inside and especially outside Europe with
effects on world food markets
International commitments on biodiversity
Implementation of the Water Framework Directive
Agricultural land abandonment in marginal areas with regeneration of woodland or
degradation
Background (6/6)Key drivers of land-use change (2/2)
9
Policy perspective (1/3)Policy intervention
Most of the policies that directly influence land-use change are drafted and
applied at the local or regional levels
Some international policy and policy dialogues often set the precedent for
national-level policies
Types of policies relevant for land use
Policies that influences the demand for land
CAP on agricultural land and EU Biofuels policies
Policies influencing land-use configurations
Less Favoured Area (LFA) policies that try to stimulate remote or less favored rural
areas
Urbanization and transport policies that can result in either concentration of urban
settlements or sprawled urbanization
Protection of natural areas through designations such as High Nature Value
farmland, Natura 2000 and areas of Outstanding Natural Beauty
10
Policy perspective (2/3)Why land-use modelling?
Interest
Many environmental and ecological problems related to developments in land use
Gain insight in spatial changes in the future
Planners and policy-makers have a decisive influence on future land use
Learning process
Can be applied for:
Environmental and sustainability outlook
Evaluation of policies (e.g. Ex-ante analysis)
According to the EC Guidelines for Impact Assessments (IA), the process
consists of the following steps1. Identify the problem
2. Define the objectives
3. Develop main policy options
4. Analyse their impacts
5. Compare the options
6. Outline policy monitoring and evaluation
Policy question
Modelling framework
Generation of
policy proposals
Policy
implementation
Problem recognition
11
Policy perspective (3/3)What it is a policy-support system?
Characteristics of a PSS in the context on land-use modelling:
Computer-based information system
Supports - not replaces - some phases of the decision-making process
Facilitates analysis, learning and communication
Employs complex and weakly-structured decision contexts
Two types:
Decision/planning support systems (development phase)
Discussion support systems (preparatory phase)
Outcomes of decision support systems :
Prescriptive solutions: Optimal land-use allocation given a set of objectives (van
Ittersum et al., 2004; Loonen et al., 2006)
Descriptive use of models (more common): Land use simulations indicate the
impacts and tradeoffs of alternative policy options
12
Developing a modelling tool (2/10)Elements to consider (2/2)
What are the policy questions to be addressed?
What land-use classes and changes have to be covered by the analysis?
What are the main drivers and pressures to be considered?
What would be the time horizon?
What would be the type of application of the results of the model?
What would be the impacts to be assessed?
Who is going to use the modelling tool (e.g. modellers, scientist, policy-
makers, etc.)
What sector-specific models would be necessary in the modelling
framework?
13
1. Definition of policy themes and questions to be addressed and options
References and policy scenarios
Indicators
Relevant scale and resolution
2. Definition of the modelling framework Specification of the appropriate
structure and components
Selection of important process and variables
Selection of sub-components, interface and language
3. Modelling tool construction
Designing a software architecture for the integrated model
Connecting the individual models or sub-components
Sensitivity analysis
4. Calibration and validation
5. Communication
Developing a modelling tool (3/10)Phases
14
Various options are possible to develop a land-use modelling framework forassessing environmental impacts of land-use changes. Which option is mostsuitable depends on:
The foreseen applications
Preferred modelling architecture
Related operational issues
Developing a modelling tool (4/10)Land use modelling options (1/4)
15
Land use modelling options - application
Application domain
Sector specific (e.g. agriculture, urban sprawl, transport)
Integrated (e.g. cross-cutting issue such as climate change effecting all types of land
use and different sectors)
Type of application
Policy preparation (trend extrapolation or scenarios)
Policy development (ex-ante impact assessment or optimisation)
Evaluation of policy alternatives (ex-post)
Developing a modelling tool (5/10)Land use modelling options (2/4)
16
Land use modelling options - architecture
Model layout
Stand-alone model (replacing existing components/modules)
Integration framework (using existing components)
Usability
User-friendly system
Specialist's tool
Developing a modelling tool (6/10)Land use modelling options (3/4)
Global Economy
Component Possible modelling tools
Regionalsectoralmodels
Land Use model
Indicators
LEITAP
NEMESIS
Agriculture (CAPRI)
Forestry (EFISCEN)
Transport (SCENES-TREMOVE, ASTRA)
Demography(PHOENIX)
CLUE-s
Land Use Scanner
Metronamica
Output
Global Demand and SupplyWorld markets
Accessibility
Regional demands and restrictions on land use
Projected/simulated land-use
•Land-cover characteristics •Carbon sequestration•Accessibility•Land prices•Changes in open spaces•Fragmentation
+Air pollution (RAINS)
Erosion (PESERA)
Hydrology (VIC, SWIM)
GHG and N dynamicsErosionHydrologic balance + water quality
17
Land use modelling options - operation
Model output
Maps and tables
Export to additional impact assessment tools
Specific visualisations (e.g. 3D, Google Earth)
Model characteristics
Spatial and thematic resolution, geographical extent, time horizon, degree of
dynamics, allocation principle, regional divisions, interoperability, performance,
flexibility etc. (follow partly from previous choices)
Developing a modelling tool (7/10)Land use modelling options (4/4)
18
Indicators should:
Relate to specific policy themes (e.g. the results are to be provided at the
appropriate scale)
Be intuitively understandable for policymakers
Discriminate between different simulation outcomes
Capture the essence of simulation results
Types of indicators :
Purely land-use based indicator: used to characterise changes in land use (e.g.
spatial distribution of the available land-use types, extent of urban sprawl, etc)
Enhanced land-use indicator: used to evaluate more complex issues (e.g. flood risk)
and relies on additional data from other external sources.
Indicator-model coupling: that combines land-use simulation results with additional
spatial models (e.g. connectivity of habitats or air pollution).
Developing a modelling tool (8/10)Indicators
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Developing a modelling tool (9/10)User group and end-user tool (1/2)
Different focus
Modellers require flexibility and expressiveness in the specification of models and
chains and their applications in scenario studies.
Policy makes require a quick view on the (comparison of) results. The interface must
be quick and easy to manage and should assist them in focusing on the most
relevant aspects.
Different intuitions
Modellers use programming or modelling languages. Structured languages are
intuitive ways of communicating with the framework about the modelled system.
Spatial modellers are often also familiar with complex GIS platforms like ARCGIS.
Policy makers mainly use documents and reports in natural languages and web
interfaces. These web interfaces make them more and more familiar with relevant
but limited sets of interactive functions, e.g. to zoom in maps or to select indicators.
20
Developing a modelling tool(10/10)User group and end-user tool (2/2)
Attempts to combine these opposite focuses and intuitions result in
interfaces that are:
not flexible enough for modellers;
still too complex for policy makers;
One possible solution Two components: one focussed at modellers who aim at
simulating new or alternative policy scenarios and one focused at policy makers to
present and analyze the modelling results.
Pre-processing:
Policy scenarios
and drivers
SectoralModel 1
SectoralModel 2
SectoralModel 3
SectoralModel 4
Lan
d-u
se a
lloca
tio
n m
od
el
Post-processing:Analysis/assessment (indicator
calculation, presentation of
resultsMo
del
sR
esu
lts
Modelling system
Pre-processing
Defining problem definition, scenario specific conditions and background
assumptions
Data acquisition and manipulation
Core modelling system
Prediction of impacts caused by land-use changes
Sectoral models or sub-models
Land allocation model
Post-processing
Assessment of results
Calculation of indicators
Presentations of results
Existing modelling tools (1/7)General structure
21
Model/
modelling
framework
Policy questions considered Drivers/Data Policy Scenarios
LUMOCAP Changes in land-use and their impact
on the rural landscape according to a
Common Agricultural Policy (CAP)
orientation.
Different policy, socio-economic - and bio-physical drivers. Models
require pan-European databases (CLC, FSS, FADN, Natura 2000,
Image 2000, Soils, NDVI series, MARS meteo, EUROSTAT socio-
economic data, etc.
Different levels of market support and
farm income.
SENSOR SIAT The Policies related to multifunctional
land-use in Europe in general. The
reform of the Common Agriculture
Policy (CAP) is the first policy case for
which model outputs have been
produced within the SENSOR project
-Population growth,
-Participation rate in the labour force, for the same area,
-Economic growth in the world outside the EU,
-The world oil price and
-Expenditure on research & development in the EU
-Policy development
For the reform of the CAP, the
scenarios show the possible impact of
changes in the level of farm income
support and market support.
EURURALIS Europe’s future agriculture and rural
areas
-Policy developments
-World trade
-Demography
-Climate change
-Technology development
Four policy options that comprise
different levels of market support,
farm payments, rural development
support, and nature conservation
SEAMLESS Agricultural and environmental
policies. 2 Test Cases: one focusing on
assessment of Common Agricultural
Policy reforms and trade
liberalisations as a consequence of
WTO negotiations, and a second on
assessing local implementations of
environmental directives and
consequences of agro-technical
innovations.
A wide range of drivers are considered including climate change,
environmental policies, rural development options, an enlarging
EU, an international competition.
Models require pan-European databases for environmental,
economic and social issues. environmental data (soils, altitude and
climate), farming data and socio-economic data.
Policy scenario that have been taken
into account in the prototype 1
include:
-Reduction of import tariffs
-Elimination of export subsidies
-Expansion of tariff rate quotas
-Specific bilateral trade agreements
(not considered for Prototype 1)
Existing modelling tools (2/7)Pre-processing phase
22
Component type
Sub-models/compon
ents
Models Characteritics
Modelling tool using the component
Programme using/developing the
the componentThemeGeographical resolution
Glo
bal
mo
del
s LEITAP Economy Global/EU/national Eururalis 2.0 SCENAR, EURURALIS
IMAGEEcological-Environmental Global Eururalis 2.0 EURURALIS, SCENAR
NEMESIS Economy Global/National SENSOR SIAT SENSORSe
cto
ral m
od
els CAPRI Agriculture NUTS2 to grid
SEAMLESS-IF, SENSOR SIAT
SCENAR, SEAMLESS, SENSOR
ESIM Agriculture EU/national SCENAR
EFISCEN Forestry National/Regional SENSOR SIAT SENSOR
ASTRA Transport NUTS2
PHOENIX plus Demograpgy National to grid Eururalis 2.0 EURURALIS
Lan
d U
se
Mo
del
s
CLUE-s Land-use GridEururalis 2.0, SENSOR SIAT
SCENAR, EURURALIS, SENSOR
Land Use Scaner Land-use GridLUMOS projects, GLOWA-Elbe
Soft
war
e e
stru
ctu
re
GEONAMICA Various
MOLAND model, LUMOCAP, Environment Explorer
Modelling and simulation toolbox used in MOLAND, PSS Environment Explorer, and LUMOCAP
Existing modelling tools (3/7)Core modelling system
23
Existing modelling tools (4/7)Post-processing phase
24
Model/modelling framework What it explains (output)
MedAction PSS (currently
being further developed
within the FP-6 project
DeSurvey)
It simulates physical, economic and social aspects of land
degradation and desertification
Environment Explorer It predicts social (built-up area), open-space, recreational space,
flooding risk, residential density), economic (access to
employment, cost of land, congestion on the road system), and
environmental aspects (noise and emissions due to traffic and
spatial fragmentation) impacts of land-use changes.
SENSOR SIAT Impacts of policies affecting land use on environmental, social
and economic aspects. Besides land-use changes, 60 indicators
have been identified in total. In the 1st prototype of the SIAT,
there were 5 indicators (GDP growth per capita, gross value
added, farm and woodland birds, N surplus in water, and
unemployment rate).
EURURALIS Impacts of different policies on rural development (social,
environmental and profit aspects). For example, the modelling
tool uses biodiversity, carbon sequestration and landscape
change as indicators of changes on the planet; employment,
agricultural employment and value added per farmer as
indicators of the impact on people, and crop production and
farm income as indicators of the impacts of land-use chain the
case of the profit dimension.
SEAMLESS A set of environmental, economical, social and institutional
indicators. These include in the first prototype: agricultural
Income, Money metric (consumer surplus), Profits of the
processing industry , Total welfare , Tariff revenues, Budgetary
expenditure, Nitrate leaching, Energy consumption due to use of
mineral fertilisers , Global warming potential.
Relevancy
Most of the European modelling frameworks can analyse different types
of land-use change simultaneously
Land-use classification similar to the one used in the CORINE database
but adapted (e.g. SENSOR SIAT 17 and EURURALIS 8)
Existing modelling frameworks and land-use models have a spatial
resolution ranging from 250 m2 to 1000 m2
A multi-scale approach has been adopted in many recent modelling
frameworks, such as EURURALIS or SEAMLESS
Time horizons vary in most cases between 2015-2050
Existing modelling tools (5/7)Comparison of modelling tools (1/2)
25
Operation
In most cases, some basic modelling experience is required to calibrate,
run and in some cases, even for interpreting the results
In the case of the EURURALIS and SENSOR, an easy-to-use PSS had been
developed allowing users to browse through already modelled results
Model runs can take from a few minutes to several days depending on
the scenarios and the questions to be analysed
Technical requirements
Actual modelling tools usually have high computational and data
demands
Computational demands of the easy to use and simplified DSS tools
(such as the EURURALIS 2.00 and the SENSOR SIAT) are easily met
Existing modelling tools (6/7)Comparison of modelling tools (2/2)
26
Current versions of existing modelling frameworks focus on specific
policy questions, e.g. the CAP reform
Environmental related issues are addressed to a limited extent
Many different existing modelling tools do only cover certain levels
needed within the specific assessment they have been designed to
address and they do not link the micro and the macro levels
Social aspects and drivers are generally not well represented in
most modelling tools
Limited re-utilisation in different policy questions than the ones
addressed
One of the main difficulties is the linkage of the different
components or models
Existing modelling tools (7/7)General remarks
27
28
Application of land-use models in the Netherlands
Applied for:
Environmental Outlooks
ex-ante evaluation National Spatial Policy Plan
Sustainability Outlook 1 and 2
Assessing the future of the Dutch agriculture (2002), and for investigating the
potential impacts of biofuels (2006) (EURURALIS)
The Netherlands Environmental Assessment Agency (MNP) participated in
the development of
Land Use Scanner (1997)
Environment Explorer (1998)
UrbanSIM (2005) and CLUE (2003)
Recent applications (1/2)MS level
29
Examples of application of land-use models at the EU level
PRELUDE (EEA) Developing coherent scenarios to describe plausible future
developments for land use in EU25 plus and their potential environmental impacts for
the period 2005–2035
Project SENSOR (EC) Developing an ex-ante Sustainability Impact Assessment Tools
(SIAT) to support decision making on policies related to multifunctional land use
SCENAR project (DG Agriculture) Quantitative analysis on the impacts of the
different scenarios considered on parameters such as the agricultural income or
employment
ESPON 2006 programme (EC) Applying research and studies on territorial
development and spatial planning from a European perspective in support of policy
development ( e.g. MASST and KTEN models)
MOLAND model (JRC) Applied to an extensive network of cities and regions. Since
2004, MOLAND is contributing to the evaluation and analysis of impact of extreme
weather events.
Recent applications (2/2)EU level
30
Advantages of the use of such modelling tools for sustainable policy
making:
Integrative frameworks allow visualising sectoral policies, trade-off and
potential conflicts.
The development of such modelling tools is an interactive process towards
the end-product, which is as important as the actual final results for policy-
makers (from a learning point of view).
Results allow to set agendas for policy-makers.
Modelling tools provide insights into the pressures of land-use changes on
different sectors, nature areas, and flood prone areas.
Modelling results show possibilities and best options under certain
conditions, and also options for policy optimisation.
Achievements and drawbacks (1/2)Achievements
31
Limitations were also encountered when using such land-use
modelling tools:
Dependency on base data, expertise for allocation rules, coherence of
assumptions.
Wrong expectations due to level of detail.
Communicating results sometimes complicated.
Indicators are not always sufficiently quantified.
Behavioural components are still missing in existing modelling tools (e.g.
human preferences).
Achievements and drawbacks (2/2)Limitations
32
Current and future work (1/4)Modelling tool for DG ENV (1/3)
Identified requirements for a EU land-use model
Identified analytical needs
Simulation of multiple land-use changes
Support the policy needs of different DGs of the European Commission
Estimate the economic, environmental and social impacts of land-use changes
Simulation at multiple scales (from EU-27 to MS and regional level) while taking into
account global sources
Illustrate cross-sectoral side effects of land-use policies
Be flexible to allow taking into consideration new policy developments
Identified accuracy and precision requirements:
Projections are reliable and plausible to a degree that is useful to the Commission
The tool has to be transparent regarding the data, scenarios, baselines, etc. that are
used
The modelling tool can be applied to locations other than the one(s) for which it was
originally developed and results can be replicable by others
33
Current and future work (2/4)Modelling tool for DG ENV (2/3)
Identified operational issues
The output of the model is easy to interpret and usable by policy makers
The modelling tools allows linkage to other models currently in use by, or of interest
to, the Commission
Maximum flexibility to incorporate a wide range of scenario and policy conditions
The modelling framework should cover EU-27 and different geographical scales
The time coverage should comprise two observation points for comparison,
including ‘current state’ and ‘future state’ taking into consideration EU policies
lifetime.
Use of existing land use modelling tools and an existing software framework for
integration of these tools
34
Current and future work (3/4)Modelling tool for DG ENV (3/3)
Model characteristics
Model characteristics
Current proposal
Spatial resolution 1000m grid cells
Thematic resolution Full range of urban, agricultural land-use types based on CORINE simulating a maximum of 17 types per application
Geographical extent Full EU-27 territory
Time horizon 2030 with possibility to extent to 2040/2050.
Degree of dynamics Yearly time steps (aggregations possible)
Allocation principle Dynamic allocation based on econometric estimation of suitability + process knowledge (e.g. growth processes); neighbourhood processes included for urban growth. Dyna-CLUE mechanism (Verburg et al., 2006)
Regional divisions for aggregation
Nuts 2/3 (nuts x)
Reliability Validation of model on multiple cases presented; validation for CLC 1990-2000 made. BIOPRESS case 1960-2000 validation.
Performance Depending on policy scenario and requirements in terms of sector-specific models. Core configuration (most scenarios) will run within a few hours on a single fast PC
Interoperability Open Source for all core-modelling components and the modelling framework
Flexibility Maximum flexibility as result of framework that even allows alternative model configuration.
35
Current and future work (4/4)Further research needs
To improve our knowledge about the relationship between land-use changes
and the resulting environmental impacts.
To develop the methodology for assessing the resulting environmental
impacts.
Social and economic impacts are not addressed to an appropriated detail in
most existing modelling tools.
Better ways to accommodate behaviour patterns and human preferences in
modelling tools, which cause important impacts on land-use changes.
The link between changes in land use and their impacts into landscape is not
very well known. This is one example where the scaling issues becomes
important.
Awareness raising is necessary about the current state of modelling tools,
their potential, policy analytical needs, and the needed development among
policy-makers and also scientist.
36
Integrated modelling is a major effort
Requires good scientific knowledge, and good integration of different
disciples (interdisciplinary perspective)
Communication plays a crucial role
A potential failure for a modelling framework is a mismatch between the
modelling and the policy context. End-user interaction is essential!
General remarks