UCD UII Summer School Land-use modelling for sustainable ... UII Summer... · The value of...

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


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


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)


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


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)


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

19

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


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 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

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