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IGBP Report No ... 35

HDP Report No.7

Land-Use and Land-Cover Change
Scjence/Research PlanGLOBAL
CHANGEHDP

IGBP Report No. 35

HOP Report No. 7

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Land-Use and Land-Cover Change
Science/Research Plan

B.L. Turner II, David Skole, Steven Sanderson, Giinther Fischer,Louise Fresco and Rik Leemans
With Contributions from
Dean Graetz, Teitaro Kitamura, Yanhua Liu, Luiz Martinelli, Elena Milanova,
David Norse, H. W. O. Okoth-Ogendo, Martin Parry, Lowell Pritchard,
Kevin Strezpek and Tomas Veldkamp

LlNKOPINGS UNIVERSITETThe Intermitional Geosphere~Biosphere Programme:, A Study of Global-Change GGBP)of the International Council of Scientific Unions (ICSU) andThe Human Dimensions of Global Environmental Change Programme (HDP)of the International Social-SCience Council (ISSC)
Stockholm and Geneva, 1995

The international planning and coordination of the IGBP is currently supported by IGBP
National CoII'l'rnittees, the International Council of Scientific Unions aCSU), the European
Commission, the National Science Foundation (USA), Governments and industry, including

Contents

the Dutch Electricity Generating Board.
The HDP is currently sponsored by the International Social Science Council asSC). The
programme receives support from governmental bodies and programmes, private industries,
and foundations.

The IGBP-HDP link is supported by the European Network for Research in Global Change(ENRICH) of the European Commission and the Swedish Council for Planning and
Coordination of Research (FRN).

Introductory message

5

Executive Summary

7

Background and Acknowledgements

10

The Science/Research Plan
1.

Introduction

122.

Scientific Mandate and Aims

18

3.

Scope and Main Subjects of LUCC

20

4.

Structure of the LUCC Plan and Links to Other IGBP and HDP
Activities

52

5.

Focus 1: Land-Use Dynamics - Comparative Case Study Analysis

61

6.

Focus 2: Land-Cover Dynamics - Direct Observation andDiagnostic Models

69

Focus 3: Regional and Global Models - Framework for Integrative
Assessments

79

8.

Integrating Activity 1: Data and Classification

93

9.

Integrating Activity 2: Scalar Dynamics

105

10.

Bibliography

108

7.

Appendices
Appendix 1: Science/Research Plan for Land-Use and Land-Cover Change _Outlme of Research Foci and Summary of Activities

124

Appendix 2: LUCC Meetings and Participants

125

The HDP Report series is published as part of the HDP publication programme, which aiso

Appendix 3: IGBP Reports

129

includes a series of occasional papers and discussion papers. All HDP publications are
distributed free of charge to interested researchers.

Appendix 4: Acronyms and Abbreviations

131

The IGBP Report series is published as an annex to the Global Change NewsLetter anddistributed free of charge to scientists involved in global change research.

Cover illustration:

Credits to NASA Landsat Pathfinder ProjectTechnical editing: Magdalena Kanger, Joao Morais and Adam Czulinski
Copyright © IGBP and HDP 1995
Clipart used in Figures 1 and 4 courtesy of Corel
IGBP ISSN 0284-8015

Introductory Message
from the Chairmen of the International Geosphere-Biosphere
Programme (IGBP) and the Human Dimensions of Global
Environmental Change Programme (HDP)The Land-Use and Land-Cover Change Science/Research Plan is an important
document for the global change research community and those interested in thesubject for at least two reasons.
Firstly, the area of science is a vital one. Human alterations in land cover as a result of
the use of land-based natural resources not only have local and regional impacts, but
can also have important effects at the global level. For example, man-made changes inland use over the last 150 years have contributed about as much carbon dioxide to theatmosphere as has come from fossil fuel combustion. Many other examples are givenin the report.
Secondly, this is the first time that the IGBP and HDP have mounted a combined
initiative in which responsibility is equally shared between the two bodies. This is asignificant achievement because the task is intrinsically large, and particularly
considering the difficulties of developing productive partnerships, on an equal basis,
between natural and social scientists. These two groups come from different traditions
but, despite this, the joint IGBP /HDP Core Project/Research Programme Planning
Committee has produced a well balanced report.
The Science/Research Plan presents the subject of land-use and land-cover change andties it to the overarching themes of global change. It briefly outlines what is currently
known and what knowledge will be necessary to address the problem in the context ofthe broad agendas of IGBP and HDP. Drawing on the expertise of specialists in various
disciplines within the natural and social sciences, the authors have developed specificresearch questions and suggested methodologies for addressing them.
The next stage is putting this into practice, with the involvement of the widest
scientific community possible. The LUCC Open Science meeting (Amsterdam, 29-31
January 1996) provides an important opportunity for discussions on how this will beachieved. Everyone interested in the development and implementation of the LUCC
project/programme is strongly encouraged to come to the open meeting.
This consultation with a wide scientific community will provide input for the nextstage, which will be the elaboration of an implementation plan that will specify ingreater detail the activities and projects that will fuIfill the mandate outlined in thisdocument. Not only new projects but ongoing activities by individual scientists andother agencies will be potential partners for this path-breaking endeavour to address
the interactions between natural and social processes in the use of one of man's crucial
resources.

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We would like to thank all those who have given freely of their time and intellect tobring the LUCC project to its present favourable position. They are too numerous tomention all of them by name, but we must give special acknowledge~ent to the groupled by Billie Turner and Oavid Skole who, with Steven Sanderson, ?unther Flscher,Louise Fresco and Rik Leemans have edited and written mu~h ~f thIs report, together
with expert assistance from Joao Morais at the IGBP Secret.anat m Stockholm. To theseand all the others who have been involved we are greatly mdebted.
It only remains for us to wish the LUCC project/programme fair speed in the.
achievement of its ambitious agenda and express the hope that thIs fIrst collaboratIOn
between our two programmes leads on to further joint ventures in the future.

Peter Liss
Chairman,
Scientific Committee of the IGBP

Martin Parry
Chairman,
Steering Committee of the HOP

Executive Summary

Land-use and land-cover change is significant to a range of themes and issues central
to the study of global environmental change. The alterations it effects in the surface ofthe earth hold major implications for sustainable development and livelihood
systems and also contribute to changes in the biogeochemical cycles of the earth,affecting the atmospheriC levels of greenhouse and other trace gases. Understanding
the nature of land-use / cover change and its impacts requires the joint efforts ofnatural and social science because of the expertise of each in certain key facets of the
topic.
The global environmental change community has increasingly recognised thesignificance of land-use and land-cover change and the need for an interdisciplinary
research approach to the subject. This recognition prompted the International
Geosphere-Biosphere Programme (IGBP) and the Human Dimensions of Global
Environmental Change Programme (HOP) to explore the possibility of a cooperative
research project/programme with the general goal of improving our basic understanding of the dynamicS of Land-Use and Land-Cover Change (LUCC) globally, with afocus on improving our ability to model and project such change. The two programmes commissioned a Core Project Planning Committee/Research Programme
Planning Committee" for Land-Use and Land-Cover Change (CPPC/RPPC LUCC) tocreate a science/research plan" for a jointly sponsored LUCC core project/research
programme.
This report constitutes the LUCC science/research plan as developed by the
CPPC/RPPC in cooperation with a larger research community through several
workshops and meetings. Section 1 introduces the subject and its linkages with otherglobal change research programmes and projects. Section 2 outlines the CPPC/RPPC
LUCC's mandate from the IGBP and HOP. Section 3 describes the LUCC problem andthe main themes and issues involved in its study. Section 4 is an overview of thescience/research plan, while Sections 5-7 detail the three main research foci, andSections 8-9 are the two integrating activities of the plan.
The plan rests on the following observations:•That a truly international and interdisciplinary LUCC core project/research
programme is possible•

That a sufficiently large cadre of scientists and social scientists exists worldwide toundertake the effort now•

That LUCC-related projects and programmes are emerging in various segments ofthe global change research community, many of them in anticipation, but
independent, of an IGBP-HOP core project/research programme1) Core Project and Research Programme are designations used respectivelYI by the IGBP and HDP.
2) Science Plan and Research Plan are designations used respectively, by the IGBP and HDP.

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That these various initiatives are, individually and in the aggregate, insufficientfor the global nature of the problem, which requires the kind of integration andinter-disciplinary effort that an IGBP-HDP core project/research programme canprovide.

Focus 3bUIld ne,:" ones that provide a basis for projecting land-use ;han es based on~hanges In the und~rlying causes or driving forces. These mOdefs willIn~rporate the regIOnal an~ situational sensitivity provided from Foci 1
an d 21 to lenerate r,nore spatially explicit outcomes from regional and global
mo e s. oCUs ~ WIll develop a model structure able to inte ate a varie ofapproaches w~le stre~gthening agricultural sector models 'by includini
water, urban, bIOphysIcal, and other such linksges and cou !in thesp gemodels to forest/timber and livestock sector mod~ls.

The plan is guided by five overarching questions, specifically:1.

How has land cover been changed by human use over the last 300 years?

2.

What are the major human causes of land-use change in different geographicaland historical contexts?

3.

How will changes in land use affect land cover in the next 50-100 years?

4.

How do immediate human and biophysical dynamics affect the sustainability of
specific types of land uses?

5.

How might changes in climate and global biogeochemistry affect both land use
and land cover, and vice versa?

Re~ional and Global Models, aims to improve upon existin models and

Two integrating activities cross-cut these three research foci:Integrating Activity 1 Data and Cl 'f' .
. asSI Ication, analyses data availability and qualityand deVIses a classification structure suitable for the various
needs of the three research foci. It also identifies and if need ddevelopsthem'
" for
e
,
.
aJor dt
a asets an d measures important
LUCC
studIes.
Integrating Activity 2 Scalar Dynamics, recognises that the different scales at which
LUCC processes operate, and the different scales at which they
are analyse~, pose major impediments to developing a~omp'rehenslve understanding of LUCC. This activity seeks to
Identif~ the .major rules and lessons that should guide LUCC
efforts In. thIS regard, thus improving the integration of thethree fOCI.

Because the study and analysis of research addressed by LUCC covers a newinterdisciplinary area, and because it is recognised that considerable integration of
LUCC research with that of other Core Projects will be necessary, these goals will
only be met through close collaboration with other Core Projects.
The plan calls for a set of integrative research foci and activities linking the various
components of the LUCC research community in an effort to improve understandingof: (i) the driving forces (exogenous variables) of land use as they operate through theland manager; (ii) the land-cover implications of land use; (iii) the spatial andtemporal variability in land-use/ cover dynamics; and (iv) regional and global models
and projections of land-use/ cover change.

The.LUCC reslearch activities will contribute to the following needs of the global
enVlronmenta change communities:• :~~~:~~1ical advancement in the design and implementation of LUCC case

These questions are addressed by three research foci:Focus 1

Focus 2Land-Use Dynamics, is a comparative case study approach aimed at
improving our understanding of the variation in the nature-society
dynamics of land management, thereby facilitating a sophisticated approachto regional and global modelling. It aims to identify and analyse a series ofregional situations that represent the major clusters of LUCC dynamics
worldwide, including the dynamic forces of these dynamics, thus permitting
spatial and temporal fine-tuning of the overall modelling effort as well as
providing the local, and, with Focus 2, regional understanding that is vitalfor climate impact and sustainability research.
Land-Cover Dynamics, involves regional assessments of land-cover change
as determined from direct observation (e.g., satellite imagery and fieldstudies) and models built from these observations. It seeks to provide spatial
specificity in the land-cover outcomes associated with the management
practices of particular land uses. In doing so, it links the underlying driving
forces and land uses found in the case studies of Focus 1 to land-coverchanges through management or proximate activities. It also extends andspecifies the spatial coverage ofparticular LUCC dynamics, while providing'models of change in this coverage.

LUCC
case study protocols, the means to interpolate and extrapolate fromof inte;a~!ci~t~~ :~~:I~pace and time scales, and the structure and functioning• Analytical advancement in a suite of integrated LUCC models
household and farm to the globe. fhrangmg rom t e• :~~,:,r~:~:~: with other projects and programmes, LUCC data development and•

Empirically-derived inventories of geo
h' 11..
and analytically-derived p . ti'
hgraPf Ica y speClflc land-use/ cover changes
rOJec ons t ereo across specific time scales.

The understanding gained from the results of a LUCC.
to a wide range of researchers policy pI
d hProJect! rrogramme will be of use
improvedf"I
anners, an ot er declslon makers requiring(i) lobal e'::~i:~~;:' proJectmg lan~-use/cover c~ange in terms of its implications forass~ssment of resp;:st:~ e~~~:i ~~dlocal:to-reglOnall sustainability issues, and (iii) the
envlronmenta change.

89

Background and Acknowledgements•••

The LUCC Science /Research Plan provided in this document is the product of theforesight of various groups and organisations that laid the groundwork for thedevelopment of a formal IGBP-HDP core project/research programme. It is impossible
to identify everyone, but the CPPC/RPPC LUCC is grateful to them all.
The most immediate forerunner to the CPPC/RPPC LUCC was the "Land-Use/CoverGroup" of the Committee for Research on Global Change (1990), Social Science
Research Council (US), which developed the rudiments of an interdisciplinary
research plan. Movement towards a formal international programme of study beganwith the 1990 agreement between the IGBP and HDP to explore the possibilities of alinked natural science-social science effort concentrating on LUCC. An exploration ofsuch an effort. was undertaken under the auspices of the "1991 Global Change Instituteon Global Land-Use/Cover Change, uOffice of Interdisciplinary Earth Studies-UCAR(US), which published its findings and suggestions in Changes in Land Use and Land
Cover: A Global Perspective 0N. B. Meyer and B. L. Turner IT, eds., Cambridge:
Cambridge University Press, 1994). This work assisted the deliberations of the IGBPHDP Ad Hoc Committee on LUCC, whose report in 1993 on "Relating Land Use andGlobal Land-Cover Change: A Proposal for an IGBP-HDP Core Project, " 1GBP Report
No. 24 and HDP Report No. 5, led to the establishment in 1993 of the CPPC/RPPC
LUCC, the source of this science/research plan. This is summarised by Turner, Meyer
and Skole in "Global Land-Use/Land-Cover Change: Towards an Integrated Programof Study", AMB10 23 (1):91-95. In addition, a special issue of Bioscience (vol. 44, no. 5,1994), based on a special symposium held at the 1992 annual meeting of the EcologicalSociety of America (Honolulu) and partially funded by CPPC/LUCC-related sources,
contains several examples of the kinds of work that this science/research plan seeks toestablish. These four documents should be viewed as supplements to thisscience/research plan.

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International Geosphere-Biosphere Programme (ICSU)
Ky~to Unive~sity, Laboratory of Regional Planning
Na~onal InstItute for Environmental Studies (Japan) Centre for Glob I
nVlronmental ResearchIaNational Science Founda!' (US).h.
,WIt assIStance from the United States.
Ion
Departrn ent 0 f Agnculture
O~ford University, Environmental Change Unit
SCIence Council of Japan IGBP and HDP N ati'ana I Commlttee.
Social Science Research Council (US)United Nations Environment Programme
Un~vers~ty College London, Department of Geography
Un~vers~ty of Ne~ Hampshire, Institute for the Study of Earth, Oceans and S ace
Umverslty of Flonda, Tropical Conservation and Development Program
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The CPPC/RPPC LUCC was supported financially and otherwise by various agencies
and organisations. Without their help the effort would have been most difficult
indeed, and we thank them sincerely. They are:
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Cecil and Ida Green Center for the Study of Science and Society, University of Texas
at Dallas
Center for Advanced Study in the Behavioural Sciences, Stanford (US)Clark University, George Perkins Marsh Institute and Graduate School of
Geography
Consortium for International Earth Science Information Network's CoSponsorship to the IGBP-HDP Core Project Planning Committee on Land-Use andLand-Cover Program under NASA/CIESIN 1993 Grant NAGW-2901
Department of Agronomy, Agricultural University of Wageningen
National Institute of Public Health and Environmental Protection(The Netherlands)
Human Dimensions of Global Environmental Change Programme (ISSC)
10111. Introduction

The Problem
Land-use and land-cover change plays a pivotal role in global environmental change.
It contributes significantly to earth-atmosphere interactions and biodiversity loss, is amajor factor in sustainable development and human responses to global change, andis important to integrated modelling and assessment of environmental issues ingeneral (Table 1). These diverse roles have been recognised in a large number of
research publications and international conferences, symposia, and workshops
devoted to the subject over the past few years (e.g., Bioscience 1994; Land Degradation
and Rehabilitation [Thom 1994]; Meyer and Turner 1994), as well as the United
Nations' Agenda 21.
The international science research priorities on global environmental change require afirm understanding of land-use and land-cover change (Fig. 1). Natural science
research on the states and flows of the biosphere, undertaken by the various core
projects of the International Geosphere-Biosphere Programme (lGBP: established in1986 by ICSU), addresses the effects of land-cover change (both conversion andmodification) on ecological processes and systems and on earth-atmosphere dynamics.
Land-cover change is driven largely by land uses. These uses and the technomanagerial practices that sustain them are a product of environmental factors, but alsoof complex political, social, and economic processes. How these latter factors andprocesses come together to drive land-use change is a central research problem of the
Human Dimensions of Global Environmental Change Programme (HDP: establishedin 1990 by the ISSC). The two programmes share a concern for the systemic nature of
the use-cover relationship, inciuding the biophysical feedbacks on human activities
and sustainability issues. Thus, land-use and land-cover change has the potential tointegrate research on the natural and human dimensions of global environmental
change, and the understanding gained from this integration contributes to otherresearch and policy initiatives, such as those of the World Climate Research
Programme (WCRP 1990) and the Intergovernmental Panel on Climate Change(IPCC 1990).

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For all its importance to scientists and policy makers confronting the complexities ofglobal environmental change, land-use and land-cover change is poorly understood.
The long-term global character, extent, and rates of changes in land cover and someland uses are known in rough outline. Uncertainty and error remain relatively high(e.g., Meyer and Turner 1994), yet the advent of more precise and geographicallyreferenced data on cover and use has created opportunities for improved analysis.
Modelling the dynamics of land-use and land-cover change, however, has been
hindered by the large variation in those dynamics across physical and social settings.
Global aggregate assessments based on simple assumptions miss the target for large
sections of the world, while local and regional assessments are too specific to be
extrapolated to wider scales. Much work remains to be done to fill these increasingly
critical gaps in understanding.
Figure 1.

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LUCC Objectives

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The Science/Research Plan

Relationship to other IGBP-HDP Activities

Recognising the need to join the natural and social sciences to improve understandingof land-use and land-cover change, the IGBP and HDP in 1991 put together an ad hoc
committee to explore the possibility of creating a joint core project/r~search
programme on the subject. That committee recommended the c~eatlO.n. of such a core
project/research programme (Turner, Moss and Skole 1993) and Ident1fl~d the broadcourse of research that it might pursue. The IGBP and HDP agreed and m 1993
commissioned a formal Core Project Planning Committee/Research Programme
Planning Committee to develop a LUCC (globall~nd-use/ cover chang:) scie,:,~e/research plan for such a project/programme (SectlOn 2). That plan, with reVlSlOns by
the IGBP and HOP through a LUCC Interim Committee, is presented in this report.

Among the IGBP core projects (Fig. 2), LUCC links centrally to the activities of Global
Change and Terrestrial Ecosystems (GCTE) and directly to various activities of the
Biospheric Aspects of the Hydrological Cycle (BAHC), Land-Ocean Interactions in the
Coastal Zone (LOICZ), International Global At1nospheric Chemistry (IGAC), Past
GI~bal Changes (PAGES) and Global Analysis, Interpretation and Modelling (GAIM).
It lmks as well to the emerging agendas defined by various programmes for Global
Change Syst~m for .Analysis, Research and Training (START) programmes, of which~';ltheast As~a ReglOna~ Committee for START (SARCS) has made the most progressm mcorpo~atmg LUCC Iss~es. Within the HDP, LUCC links to programmes of study
on Industnal Transformation and Energy Use, Demographic and Social Dimensions ofResource Use, Public Attitudes, Perceptions, Behaviour and Knowledge, Institutions,and Environmental Security and Sustainable Development. Beyond the IGBP _ HDP
LUCC complements various activities of the World Climate Research Programme '(WCRP - UNEP), the Intergovernmenal Panel on Climate Change (IPCC - WMO andUNEP), Global Environmental Monitoring System (GEMS - UNEP), Global Terrestrial
ObservatlOn System.(~TOS - UNESCO and UNEP), and Man and the Biosphere (MAB
- UNESCO). In addition, .~UCC connects to the Food and Agricultural Organization's(UN FAO) land:t.;"e claSSIfIcation ef.fort and the International Institute for Applied
Systems AnalYSIS (IIASA) new project on modelling land use and land cover.

LUCC is an interdisciplinary project/programme designed to improve understanding
and projections of the dynamics of land-use and land-cover change as i'.'puts to andconsequences of global environmental change and as elements of su.stamabledevelopment. This mandate requires new integrated global and reglOnal models,
informed by empirical assessments of the patterns of land-cover change and b.r. .
comparative case studies of land-use processes, and is based on data and classlflcation
development. It also requires major improvement in understanding how processes ofland-use and land-cover change vary across spatial and temporal scales and inincorporating that understanding into models. These five themes - integrated global
and regional models, land-cover patterns, land-use processe.s, database andclassification development, and cross-scale or scalar dynamiCS - form the research
agenda of LUCC.
Table 1.

Global Change Themes Requiring Land-Use and Land-Cover Change
Information.

LAND COVER ATMOSPHERE INTERACTIONS
Biogeochemistry
Atmospheric chemistry
Water and energy

BIODNERSITY
Ecosystem structure and function
Species and genetic diversity
Land-cover fragmentation

SUSTAINABILITY ISSUES
Soil use and erosion rates

Soil nutrient maintenance
Water use

Agro-ecological potential/"support" capacity
Rural planning/environment and development
National and international policy
RESPONSE TO GLOBAL CLIMATE CHANGE
Land sensitivity to climate change
Land use for mitigation

The CPPC/RPPC and LUCC Development
A LUCC initi~tive was approved by the IGBP and HDP in February, 1993, and a Core
Project Plannmg Committee (IGBP) /Research Programme Planning Committee (HDP)
was selected .to create a Ll!CC science/resear0 plan that would integrate the naturaland SOCial SCiences, followmg a mandate proVided by its sponsoring organisations.
The CPPC/RPPC LUCC membership was:Giinther Fischer, Austria (HDP)
Louise Fresco, The Netherlands (IGBP)
Dean Graetz, Australia (IGBP)
Teitaro Kitamura, Japan (HDP)
Rik Leemans, The Netherlands (IGBP)Luiz Martinelli, Brazil (IGBP)Elena Milanova, Russia (IGBP)

H. W. O. Okoth-Ggendo, Kenya (HDP)
Martin Parry, UK (HDP)
Steven Sanderson, USA (HDP)David Skole, USA (IGBP), co-chair
B. L. Turner li, USA (HDP), chair
Liu Yanhua, China (HOP)

The CO~mittee drew upon the assistance and advice of a wide range of experts.
ImmedIately central to the execution of the sclence/research plan were: David Norse(UK), Senior Science Advisor for Focus 3, who took the original lead in thedevelopment of that focus; Lowell Pritchard (USA) Science Assistant for Focus 1.
William B. Meyer (USA), Science Associate for LUCC; and Heather Henderson 'Administrative Assistant for the CPPC/RPPc. In addition, the committee tha~sThom~s Veldkamp (Net~erlands), Ken Strzepek (USA) and Riga Suprapto (Indonesia)
for their speCIal contrlbutlOns to the LUCC effort, and J. P. Hrabovszky(Australia/Hungary) for his valuable comments on the draft of the plan.

INTEGRATED MODELLING AND ASSESSMENT
1415

During the meetings of the CPPC/RPPC, the committee sought the advice of many
experts from throughout the international community. These individuals are:

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D. Bromley (USA)J. Bruinsma (Netherlands)
R. Brookfield (Australia)
G. Clarke (UK)J. Eddy (USA-ClESIN)
A. Gupta (India)
Y. Himiyama (Japan)
J. 1mbemon (France)
J. Ingram (UK)
L Kayane (Japan)
G. Leach (UK)D. Major (USA-SSRC)
J-P. Malingreau <Belgium)
M Mortirnore (UK)R. Moss (HDP-IGBP)
R. Munton (UK)
1. Olsson (Sweden)

K. Otsubo (Japan)c. Padoch (USA)P. Pingali (Philippines)

C. Poole (Spain)
C. Rosenzweig (USA)

P.
Y.
X.
V.

Richards (UK)
Satoh (Japan)
Singh (India)
Stolbovoy (Russia)
R. Suprapto (Indonesia)
N. Swanberg (IGBP)
K. Strzepek (USA)Y. Van Frausum (Belgium)
T. Veldkamp (Netherlands)
E. Wiegandt (HDP)
M Williams (UK)
A. Young (UK-FAO)

Finally, an Interim Committee on LUCC made revisions in the science/research plan
as directed by the IGBP and HDP. This committee was composed of:Giinther Fischer, Austria (HDP)

Steven Sanderson, USA (HDP)
Robert Scholes, RSA (IGBP)David Skole, USA (IGBP), co-chair
B. 1. TumerlI, USA (HDP), chair

Rik Leemans, The Netherlands (IGBP)

Jerry Meilllo, USA (IGBP)
Martin Parry, VI< (HDP)

For synopses and lists of participants for each CPPC/RPPC meeting relevant to various
facets of the development of the science/research plan, please see Appendix 2.

Acronyms and Definitions
This report contains many references to various agencies, programmes, and projects
whose titles have been abbreviated to acronyms. A list of these acronyms and theirdefinitions is available in Appendix 4.
An interdisciplinary SUbject such as LUCC involves the use of terms that havedifferent meanings and/or implications in different research fields. Throughout the
text we provide definitions for key terms of this kind. The distinction between land
use and land cover, for example, is detailed in Section 3. Land-cover change involves
both conversion and modification; in this document, the use of the term land-coverchange is intended to include both processes. The terms land-cover conversion andland-cover modification are used when referring to the individual processes.
Similarly, as land use involves both the biophysical manipulation of the environment
and the intent or purpose of the management processes, the term land use should beconsidered to refer to both processes, unless explicitly indicated otherwise. Driver(s),driving force(s) and forCing function(s) are used synonymously in this report to refer towhat are known in some fields as exogenous variables. Finally, the report avoids theuse of the terms prediction and cause, save in certain strictly defined cases.
Figure 2.

Links between LUCC and Major International Global Environmental
Initiatives, Programmes and Organisations.

1617

2. Scientific Mandate and Aims
Joint IGBP-HDP Core Project/Research Programme
Planning Committee on Land-Use/Land-Cover Change

Tasks
The CPPC is charged with drafting a detalled science/research plan for an IGBP-HDP
project/programme on land-use/ cover change, building on the framework of study
outlined in the report of the joint working group. The Science/research plan preparedby the CPPC will:•

Address the needs of the core projects and proposed core projects of the IGBP, inparticular GCTE, IGAC, BAHC, and LOICZ•

Contribute to the projects and activities of the HDP, including Industrial
Transformation and Energy Use, Demographic and Social Dimensions ofResource Use, Public Attitudes, Perceptions, Behaviour and Knowledge,
Institutions, and Environmental Security and Sustainable Development•

Define the data needs of the project/programme and specify how these needs canbe fulfilled in cooperation with the IGBP-DIS and HDP-DIS (Data and Information
System).

Introduction
Recognising the importance of land-cover change to environmental change and its
human dimensions, and noting the main conclusions of the joint IGBP-HDP Working
Group on Land-Use/Land-Cover Change, namely that:•••

Understanding the past and future impacts of changes in land cover is central to
the study of global environmental change and its human driving forces andimpacts, induding hydrology, the climate system, biogeochemical cycling,ecological complexity, land degradation and its impacts on agriculture and humansettlement
Land-cover modelling will require improved knowledge of land use, as it will bedifficult to project future states of the land cover without knowledge of the factorsthat determine land use and drive land-use change
The most likely determinants of land use are: demographic factors such as
population size or density; technology; level of affluence; political structures;
economic factors such as systems of exchange or ownership; and attitudes andvalues•Additional basic research is required to understand how these factors interact todetermine land use and drive land-cover change and how information about thesefactors could be used to project future patterns of land use, future rates of landcover change, or future states of land cover•Regionalisation and coordinated case studies are necessary for further
investigation of changes in land use, their causes, and their implications for thefunctioning of the Earth system•

As appropriate, the plan will also:•

Contribute to the definition of relevant START activities•

Make use of the outputs of PAGES•

Make use of the outputs of the HDP Data Programme.

Composition
The CPPC will be composed of 8-12 individuals with broad scientific backgrounds andwill be international and multi-disciplinary in composition. The members of the
CPPC will be appointed jointly by the Scientific Committee of the IGBP (SC-IGBP) andthe Steering Committee of the HDP (SC-HDP).

Mode of Operation and Timetable
In preparing the detalled science/research plan, the CPPC will:•

Actively interact with the core projects/research programmes and activities of the
IGBP and the HDP•

Hold an open scientific meeting to discuss and assess its detailed science/researchplan.

The knowledge gained through regionalisation and case studies will be crucial todeveloping regional and global land-use/ cover-change models.

The International Geosphere-Biosphere Programme (IGBP) and the Human
Dimensions of Global Environmental Change Programme (HDP) jointly establish aCore Project Planning Committee (CPPC)/Research Programme Planning Committee(RPPC) to set up a joint core project/research programme on Land-Use/Land-CoverChange.

The CPPC will complete its work in approximately one year. The IGBP and HDP
contribute to funding the work of the CPPC.

18

19

At the conclusion of the work of the CPPC, and assuming approval of the proposedplan by the SC-IGBP and the SC-HDP, a Joint Scientific Steering Committee for the
project/programme will be formed to carry out the science/research plan.

3. Scope and Main Subjects of LUCC

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Land-Use/Land-Cover Dynamics and Linkages
The terrestrial or land covers of the earth and changes therein are central to a large
number of the biophysical processes of global environmental change. Land cover isthe biophysical state of the earth's surface and immediate subsurface (Fig. 3). Changes
in land cover include changes in biotic diversity, actual and potential primary
productivity, soil quality, and runoff and sedimentation rates (Steffen et al. 1992). Land
covers and changes in them are sources and sinks for most of the material and energy
flows that sustain the biosphere and geosphere, including trace gas emissions and thehydrological cycle (BAHC 1993; Holligan and de Boois 1993; Matson and Ojima 1990).
Because contemporary land cover is changed mostly by human use (Allen and Barnes
1985; Turner, Kasperson et a/. 1990; Whitby 1992), an understanding of land-use change
is essential to understanding land-cover change. Land use involves both the mannerin which the biophysical attributes of the land are manipulated and the intent
underlying that manipulation - the purpose for which the land is used. Forestry,parks, livestock herding, suburbia, and farmlands are, for example, classes denoting
intent or purpose. Biophysical manipulation, by contrast, refers to the specific way inwhich human uses treat vegetation, soil, and water for the purpose in question: forexample, the cut-burn-hoe-weed sequence in many slash-and-burn agricultural
systems; the use of fertilisers, pesticides, and irrigation for mechanised cultivation onarid lands; or the use of an introduced grass species for pasture and the sequence of
movement of livestock in a ranching system. Biophysical manipulation can be seen as
the techno-managerial system.
Land use affects land cover with various implications. The present understanding of
use-cover relationships, however, is inadequate, impeding progress towards certain
objectives of the global change community, such as the ability to project use-coverchanges. To improve this understanding, land use and cover must be linked tohuman actions. These actions are the product of individual and group behaviours
within specific socio-economic and environmental settings. These behaviours andsettings are extremely complex, but can be grouped into common or typical patterns in
broadly similar environments and political economies.

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institutions) and influenced by the existing environmental conditions or context, lead

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Land-use and land-cover change and global environmental change form a complex
and interactive system linking human action to use/cover change to environmental
feedbacks to their impacts and human responses. Further complicating this system isthe fact that the linkages occur at different spatial and temporal scales. The outflow ofsoil nutrients, for example, has immediate impacts on land productivity, vegetation
changes and soil erosion, mid-term impacts on landscape fragmentation and land
productivity, and possible long-term impacts on climate change.

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Distinguishing Land Cover and Use.

21

to an intended land use (e.g., livestock herding) of an existing land cover (e.g., forest)
through the manipulation of the biophysical conditions of the land.

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Elsewhere these manipulations (e.g., cutting and burning) have been referred to as
proximate sources of change (to distinguish them from the underlying human forcesof change) or the most immediate activities or actions that create change. These
actions may convert the existing cover, in this case by cutting, burning and planting tocreate a grassland, or modify it through introducing new grasses into existing pastures.
Either cover response is further affected by biophysical forces that change it unlesshuman inputs are used to maintain the converted or modified cover (physicalmaintenance: e.g., fertilising and weeding). These land-cover changes act as sources orsinks of biogeochemical flows (e.g., greenhouse gases), the feedbacks from which may
affect the use-cover relationship. These feedbacks, as well as the changes in the land,
may themselves affect the driving forces and the social setting in which they operate,
and these effects, of course, may alter the intended land use.

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Examples of these kinds of dynamics have followed at least three research paths
considering: land use and land cover as forcing functions of other global environmental changes, both currently and in the past, as well as other global changes, such as
potential climate change, as forcing functions of land use and land cover (Melillo et al.
1993). The three paths, of course, cover much common ground, but the path chosen
may influence the conclusions reached. The third path - environmental-change
impacts on land use/ cover - largely addresses the "what if" question through scenariobuilding with the aim of projecting the use-cover consequences of certain levels andkinds of climate change (e.g., Emanuel, Shugart and Stevenson 1985; Houghton et al.
1990; Rosenzweig 1985; Parry, Carter, and Konijn 1988; Parry 1990; Cramer andLeemans 1993; Rosenzweig and Hillel 1993; Rosenzweig and Parry 1994). Emphasis isplaced on modelling the scenarios, all of which are based on simplifying assumptions
about human behaviour and decision making and their meaning for land-use change.
The former two paths - the causes and consequences of land-use/ cover change - largely
aim toward understanding the social, political, and economic factors that influence
land use, occasionally addressing environmental components of the problem, butrarely those directly relevant to most global change studies. A major exception is work
drawing on remotely sensed imagery of land cover linked to land uses, proximate
sources of change, and, to a lesser degree, the underlying human causes in order toimprove knowledge of carbon flows and biodiversity change (e.g., Moran et al. 1994;
Skole et al. 1994). As noted, however, land-use/cover change is not a recent
phenomenon, and the "what was " path has produced considerable documentation of
it for various regions and locales, particularly for the recent past (e.g., CrumJey and
Marquardt 1987; Foster 1992; 1993; Foster et al. 1992). This information andinterpretations generated in the path offer lessons with which to frame land-use/cover
dynamics, particularly for transitory stages of change, and provide a factual basis onwhich to test models by "backcasting " them.
The programme of study proposed here seeks to join the research following all threepaths. Its primary aim is to improve our understanding of current and future landuse/cover dynamJcs in order to model land-use/cover change (what is). To do so,
however, requires an understanding of these dynamics at various times in the past
(what was). Achieving this understanding is essential to the "what if " path toimproving projections and scenario building (Meyer and Turner 1994; Turner, Meyer
and Skole 1994; Turner, Moss and Skole 1993). In addition, the central path we havechosen is the one least developed within global change research.
22

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LUCC Dynamics.

23

Land-Cover Conversion and its Environmental Impacts
Humankind has altered terrestrial ecosystems since, at least, the use of fire to hunt andthe advent of plant and animal domestication (Thomas 1956). Such change increased
dramatically throughout the agricultural phase of history (Wolman and Fournier1987), most strikingly in deforestation (Williams 1990a) and the transoceanic
movement of species (Crosby 1986; Turner, G6mez Sal and di Castri 1994). Thesechanges were of no small consequence, and yet in spatial scale, magnitude, and pace
they pale in comparison to those produced by modern industrial society. Today, landcover changes of many kinds are global in spatial scale and magnitude and rapid, if
variable, in pace, some of them large enough to contribute significantly to changes in
global biogeochemical flows.
A significant amount of literature documents and interprets the character of modern
land-use/ cover change. It is too vast to be fully treated here; the several examples
provided below must suffice (for a review, see Meyer and Turner 1992).
Impacts on Land Covers (States/Faces)
From 1700 to the rnid-1980s, the largest land-cover change involved cropland, which
increased globally by 392% to 466%, depending on the means of estimation, or from anarea roughly the size of Argentina to that of the South American continent (Richards
1990). It grew at the expense of forest, grassland, and wetlands. Change accelerated
globally, in terms of both the conversion of lands to cultivation and the intensificationof agriculture on land already cultivated. The net global area of irrigated croplandincreased by 2,400% over the last 200 years, from 80,000 km'to 2,000,000 km' (Richards
1990). Today, cropland conversion and, perhaps, intensification are most rapid in theless industrialised portions of the world, while the area of cropland has decreased inEurope (Richards 1990).
Since pre-agricultural times, worldwide forest/woodland/tree cover has diminished byabout 15% (Williams 1990a), although this figure could change considerably withchanges in the definition of what is counted as forest or woodland. Currently,
forestation is significant in the western world, where land is being taken out ofcultivation, while large-scale tropical deforestation is occurring because of logging,
cultivation,and livestock uses (Bioscience 1994; Palo and Mery 1990). Taking bothpatterns of change into account, the annual global loss in forest cover may be as high as
100-200,000 km' (Williams 1994).

Two important patterns emerge from a brief review, with implications to which wereturn later. From the dawn of the Industrial Revolution until the early part of thiscentury, major changes in land cover were centred primarily in the mid-latitudes of
the Northern Hemisphere (v. Turner and Butzer 1992). Even where these lands havereverted to a cover type that existed previously, it has been in altered form. For
example, the beech-hemlock-sugar maple forest of central New England that was
cleared in the 18th and 19th centuries for farms, timber, and fuel has been replaced bybirch, oak, hemlock, pine, spruce, and red maple (Foster 1993). During this century,and particularly in its latter half, the major land-cover changes have occurred in thetropics. In this realm, cropland and grassland/pasture expansion, deforestation, andurbanisation, among other changes, are increasing rapidly.
Land-cover changes, and therefore land-use changes, are environmentally significant
in their own right. They degrade or enhance the land's capacity for sustained use andability to regain its original cover. In some cases land-cover changes, or their impacts,
can become so large or widespread that they are identified as global change inthemselves. Elsewhere this kind of change has been referred to as globally cumulativechange (Turner, Clark et al. 1990). Biodiversity loss is one example. Land-coverchange has led to, or is leading to, significant losses in species numbers and varieties
worldwide. Wilson (1992) estimates the loss in tropical forests alone to be on the orderof 27,000 species annually, although much higher estimates exist (e.g., Ehrlich andEhrlich 1981). Ecosystem structure and function, long-term ecological processes, andgenetic diversity are also at risk in biodiversity loss. Biodiversity losses take place atmultiple levels (landscape, ecosystem, species, gene) and in multiple dimensions(structural, functional, and processual) and, therefore, are particularly important forthe structure and function of large-scale ecological processes, with implications forland use as well as other forms of global change (Schulze and Moaney 1993).
Impacts of Land Cover on Biogeochemical Cycles
Land-cover conversion is an important historical and contemporary component ofother forms of global change (Leemans and Zuidema 1995). The historical conversionof natural systems to agriculture and other human uses of the land has resulted in a
net release of carbon dioxide to the atmosphere (Houghton et al. 1985; Houghton et al.
1987; Houghton and Skole 1990), one roughly equivalent to the release from fossil fuelburning over the last 150 years, although the current release of carbon dioxide fromland-cover conversion is approximately 30 percent of fossil fuel combustion. Landcover conversion may have an important iniluence on regional climatology andhydrology (Shukia et al. 1990).

If grassland is defined very broadly, it has changed little over the past 300 years,

perhaps a net global decline of one percent (Richards 1990), as its loss to cropland(primarily in Europe, North America, and Southeast Asia) has been compensated by its
gain from forest land (mostly in Africa and Latin America). If it is defined morenarrowly (Graetz 1994), it has declined by some 20% since pre-agricultural times. More
important than change in extent may be changes in the quality of grasslands and theirsoils.
The long-term, worldwide loss of wetlands is difficult to compute (Gosselink andMaltby 1990), although it is known to be extensive, possibly several million km'.
Losses have primarily been the result of cropland expansion. Finally, rural and urban
settlement now covers some four million km' (Douglas 1994).
24

Both land cover and land-cover change data are important for determining thebiogeochemical cycling of carbon, nitrogen, and other elements at regional to global
scales. The estimates of carbon released from land clearing and biomass burning
combined with the estimates of oceanic uptake of carbon cannot now be reconciled in abalanced global budget. The land estimates are either incorrect or incomplete.
Land-cover data are integral to analyses of other gas dynamics (Penner 1994). Natural
ecosystems determine the dynamics of many important species such as CH, and N,O.
Ecosystem conversion results in changes in trace gas dynamics. Conversion of tropicalforest to pasture seems to be an important factor in trace gas dynamics for years after

25

pasture formation. Land is often converted through biomass burning, which may be
an important source of CH" CO, and other radiatively important trace gases (Crutzen
and AndreaeI990).
The atmospheric concentrations of CO, and other trace gases are closely linked to eachother through their involvement with and interactions in chemical processes in theatmosphere (Prinn 1994). When compiling a list of the sources and sinks of thesegases, it is apparent that both the land cover and land-cover change play major roles indetermining their actual emissions and thus final atmospheric trace gas concentrations(Leemans 1995). Assessments aimed at evaluating the dynamics of global sources, sinks
and fluxes of trace gases have to emphasise comprehensively the many different
aspects of land-cover change (conversion, modification, and their characteristics) on
many different spatial and temporal scales.
Land-cover change has an important influence on water and energy balance. Land
cover determines surface roughness, albedo, and latent and sensible heat flux, andchanges in the distribution of land cover alter the regional, and possibly global, balanceof these fluxes. Such changes are important parameters for general circulation models.
These models use coarse grids of 200 km horizontal resolution; because of rapid
mixing in the boundary layer finer-scale data are presumably not required. Therefore,a general distribution of land cover might be sufficient. Nonetheless, the aggregate
sum of various boundary layer transfers for each coarse grid would be dependent on a
sub-grid parameterization. Latent heat flux, for instance, is mediated byevapotranspiration. Actual Evapotranspiration (AET), in turn, is a function of landcover type, soil moisture, and climate (e.g., temperature).
Changes in vegetative cover, which mediate the water balance, also influence AET.
Since AET is a function of whole plant and xylem water potentials, leaf area andstomatal closure, rooting depth, and canopy structure across the soil-plant-atmosphere
continuum, water use and AET vary spatially across different ecosystems andtemporally as one land cover is converted to another. They also vary as a function ofseasonality. In these terms, geographically referenced actual land-cover datasets with aseasonality component are important for climate modelling beyond their simple
utilisation as a means to parameterise sensible heat flux. Because the water balanceand physiological controls on latent heat flux mediated by vegetation occur seasonallyand at somewhat fine scales, there is a need to develop the appropriate datasets uponwhich coarse inputs to the General Circulation Models (GCMs) can be derived.
Part of the hydrological cycle involves the movement of water over continents. Plants
act like waterpumps in this part of the cycle, extracting water from soils and returning
it to the atmosphere through evaporation and transpiration. Water recycling in the
Amazon rain forest is exemplary; the present precipitation patterns observed there arepartly a function of the vegetation cover (Salati et al. 1979; Victoria et al. 1991).
Changes in land cover, therefore, may trigger changes in the hydrological cycle which,in turn, would have Significant implications for land uses. The impacts of thehydrological cycle caused by land-use/ cover changes in the Amazon are not yet
adequately assessed. One of the few such assessments (Shukla et al. 1991) indicates thata significant regional decrease in evaporation and precipitation would follow massive
removal of forest there. At the global scale, land-use/cover change has been shown tohave an impact on atmospheric circulation (Foley et al. 1994; Henderson-Sellers 1990,
1991, 1993; Henderson-Sellers, Wilson and Thomas 1985).

26

Land Use Links to Land CoverLand cover may be changed by natural processes. Climate variations, of course, affectterrestrial ecosystems globally, while volcanic eruptions and changes in river channels
or sea level have more localised impacts. Changes of these kinds are always operating
and are, in some cases, difficult to disentangle from human influences, as in the case ofdesertification in the Sahel (Tucker et al. 1991). Regardless, the land-cover changes
worldwide of the present and the recent past are overwhelmingly the result of humanaction - of activities largely aimed at modifying or converting land covers for the
purposes of production and, to a lesser extent, settlement. These activities constituteland use.
The production-consumption demands of modem society cannot be met withoutmajor modification and conversion of land covers for various uses. Most of the uses
fall into one or more of these broad categories: cultivation, livestock production,
forestry / timber production, settlement (including transportation infrastructures andmanufacturing), recreational uses/parks/preserves, mining, and, if near-shore
environments are included, fisheries. The areas beyond frontiers, those yet to be
substantially inhabited but not protected from settlement or use by a recognised
political organisation, may be seen as areas that essentially lack an intended use. Of
course, many such areas considered" open" have long been occupied and/or used atleast ephemerall y.
Every major category of land use has expanded significantly through human history
and particularly since the Industrial Revolution. Currently, agriculture and livestock
production have slowed in areal expansion globally, but with notable regional and subcontinental variations, while settlement expansion is escalating (Berry 1990). During
the next decade and century, according to many experts (e.g., Ruttan 1994), agriculture
will shift from expansion towards intensification, while urban areas, particularly alongcontinental margins, will continue to grow. By the end of this century, most of theworld's land area will be intensively and formally managed, and "open" lands will nolonger exist. Moreover, much of world's prime agricultural lands will be increasingly
influenced by local atmospheric pollution (Chameides et al. 1994.)
Specifying these trajectories of land-use change is essential to understanding landcover impacts. Inasmuch as terrestrial ecosystems are spatially complex, land uses andland covers need to be matched by georeferencing. Any broad category of land use,
however, includes many varieties of biophysical use of cover. Agriculture incorporates uses as different as long-fallow slash-and-burn cultivation versus annual
irrigated cotton farming, each with very different land-cover dynamics and globalchange impacts. Hence, locational specificity must be paralleled by use specificity.
Such specificity is difficult to achieve beyond the immediate future, however, because
land use, driven by changing production-consumption dynamics, is subject to thevagaries and complexities of the social, political, economic, and even cultural andreligious factors that give rise to those dynamics. Different researchers dealing withthe social dynamics of land use draw different lessons for the level of detail at which
they can be usefully modelled. Certainly models can be made more precise andaccurate, particularly by incorporating subglobal components that capture regional andnational variations in production-consumption dynamics and among land managers.

27

What pass for land-use models are typically models of economic sectors predictingchanges in production at the country level (v. FAO 1993a). They need to be better
linked to outputs of locationally specific land use and land cover.
Land-Use/Cover Impacts on Sustainability
Changes in land use and land cover have significant environmental implications
independent of the global variety, such as the direct use-cover impacts from soil
degradation, surface runoff alterations, or the draw down in ground water. These
kinds of changes - those confronting the land manager on a daily basis - as well as theirimpacts on, and sensitivity to, global environmental change are referred to here as
issues of sustainability. We need not reiterate the magnitude, spatial scale, and pace ofchanges in sustainability inasmuch as they are intimately linked to, indeed often thesame as, those detailed above for land-cover changes (impacts on states/faces andbiogeochemical cycles). At least three points are important here. (i) Increasingly, theglobal environmental change community appears to realise the centrality of landuse/ cover change in its own right to sustainability issues as recognised in the various
outcomes of the United Nations Conference on Environment and Development in1992. These sustainability issues link to developmental ones (e.g., AMBIO 1995; Chen
and Kates 1994; Walker 1993). (ii) Many of the projected problems associated withland-use/ cover sustainability, such as ground water depletion, may well trigger largescale environmental problems in the near term that will have impacts on landuse/cover dynamics (Chameides et al. 1994; Graetz 1991; Tolba and El-Kholy 1992;
Vitousek et al. 1986). (iii) The sustainability of any land-use is not only tied to theenvironmental attributes of the land and the techno-managerial strategies employedon it, but to the socio-economic condition of the land manager (Arizpe, Stone andMajor 1994; Blaike and Brookfield 1987; Brookfield and Paddoch 1994). Land-use/coversustainability, therefore, is largely captured in the kinds of integrated modelling efforts
that are central to understanding land-use/ cover change.

Modelling and Projecting Land-Use/Cover Changes
Modelling land-use/ cover change has been approached in at least three different ways:
through field-based case studies of land use; thematic assessments of the patterns ofland-cover change; and prognostic, regional and global models of land-use/ cover.
Unfortunately, all have been stereotyped. Case studies and the models generated fromthem are too often equated with the specific-rich narrative, lacking generalities thatcan lead to macro-models; thematic assessments of cover change are considered too
labour-intensive, too long on detail, and too short on explanatory power; andprognostic macro-models are criticised for their unrealistic assumptions andsimplifications that preclude real-world usefulness, let alone accuracy. These
stereotypes are not only unwarranted but miss the critical point that each approachcomplements, and, if integrated properly, improves the others.
Land-Use Dynamics: Land-Manager Studies
A global subject of study requires a large number of case studies comparable instructure and content, providing a firm empirical basis for characterising the major"situations" of land-use/cover dynamics. Case studies, along with spatial analyses
28

from direct observation (cover pattern approach) can be used to build sets of microand mesa-level models of land-use and land-cover change through time. The goals ofsuch an approach are both description and explanation in the form of useful causal
understanding (Clark, Jones and Hailing 1979). The changes described by these models
may be iterative, punctuated, or disjOinted by historical periods. Mechanistic
modelling based on cases adds to the credibility of larger models to the extent that it
validates the broader-scale application of simple functional forms and aggregate
parameters. Case-based empirical and qualitative modelling will advanceunderstanding of LUCC if subnational and lower-scale Oocal and regional) models can
incorporate local driving forces (such as cultur.ally-specific institutions and/ or policy
intervention) in ways that global models will not.
Such an aim is new and challenging, both in its comparative dimension and its effort
to join social science and natural science concerns. It constitutes a new analytical
approach to land-use/cover change that transcends the divisions between natural andsocial science methodologies, addresses the cross-scale problematique directly, andoffers empirically testable hypotheses about land-use situations in which bothbiophysical and human dimensions are represented as ever-changing forcing
functions or driving forces.
The primary energy sources - solar, lunar, and geological - drive all the varied earthsystems, including the human ones, whatever the convoluted transformations thattake place within and across those systems. in one sense then, biophysical forces alone
are the ultimate cause of both land-use and land-cover change. At temporal andspatial scales relevant to modelling human impact on land cover, however, theseprimary sources are apparent as an extraordinarily diverse set of driving forces thatmake up a distinctive" energy signature" for a given landscape, including both social
and biophysical drivers (Odum 1983).
A view of nature as static (unchanging) or passive (changed oniy by social driving
forces) is inconsistent with the notion of biophysical "drivers". Conversely, for an
ecological determinist, society is the passive term, or dependent variable. The term
"driver" or "driving forces" used here makes no claims as to first causes; it only
stipulates that some land-uses/covers are strongly influenced in the long or short run
by biophysical forces and some by social forces, and that the two should be consideredjointly in analysis. These stipulations are made in a framework that recognises therelative dynamics of the interacting forces, so that variables that appear to be drivers at
one scale may seem constant at another, and feedback effects are possible at scales otherthan that of the driving force. For example, the aggregate effect of groundwater
withdrawal from individual wells may be coastal subsidence or a generalised
desiccation of the landscape. By conSidering the cross-scale aspects and the biophysicaland social driving forces together, the analysis framing in Focus 1 escapes the single
equilibrium trap of some optimal models.
Analysis of LUCC, therefore, requires cross-scale dynamics and an historical dimension- not just human history, but natural history, too. An improved land-use change
analysis must take into account the path-dependency of system evolution, thepOSSibility of muitiple stable states, and multiple trajectories. Land-use change cannot
be Simply explained as the equilibrium result of the present set of driving forces(Arthur et al. 1987; for an example, see Foster et al. 1992). in other words, land-covertype may be dependent on initial conditions, and small, essentially random events
may lead to very different outcomes (Ruelle 1991), making prediction problematic.
29

Exemplary is the effect of transportation infrastructure on the pattern of development.
Road expansion and improvement not only lead to more development but may also
lead to a different pattern through a reorganisation of market structure, which thenfeeds back to further infrastructure development. Thus, certain trajectories of land-use
change may be the result of "lock in " that comes from systems that exhibit autocatalytic behaviour (Arthur 1990; Arthur et al. 1987; Krugman 1991). Non-cyclic, pathdependent systems show three particularly troublesome properties for modelling andfor policy: inherent non-predictability, potential non-superiority of outcomes, andstructural rigidity (Arthur et al. 1987).
The complexity of the problem deepens with the understanding that three dimensionsof drivers - socio-economic, biophysical, and land management (proximate causes) are relevant to land-use/cover change, two of which involve adaptive agents andsystems that respond to and sometimes anticipate changes in the other spheres. Globalchange modellers have only recently begun to deal with this problem with regard evento biotic feedbacks (Baskin 1993). An approach that integrates the three spheres,
therefore, is not only necessary, it is forward looking.
A case study approach of LUCC needs to build on this view - the three dimensions as
illustrated in Fig. 5. These forces may be put into historical and cultural contexts at-various scales. The general idea is to compare geographically different but analyticallysimilar land-use situations along these three dimensions. Each of the dimensions is
implicitly multi-scalar, though in the context of global environmental change, themodalilies of land management tend toward the micro-scale, whereas the biophysicaland social forces are larger-scale processes expressing themselves in different ways
across temporal and spatial scales (Fig. 6). In this perspective, the human dynamics ofland-use change can be fitted to large-scale processes and to small, and the variable
importance of human and biophysical forces that operate at different spatial andtemporal scales will be more apparent. For example, cultural practices are importantsources of variation in land management (proximate causes) at the level of the unit of
prodUction, and may endure over long periods of time, transcending shorter-term
historical periodisation. Those important local variables may not be significant at themacro-scale (e.g., local practices in long-standing Amazonian settlements are notprincipal variables in the determination of overall Amazonian land use), and are
generally dominated in a hierarchical system of political and economic power.
A multi-scalar, hierarchical analysis is more likely to reveal the cross-scale changes insalience among such variables, as well as the emergent properties of systems at
different scales.
Figure 7 reveals the concepts behind the three-dimensional approach. The drivers that
determine land cover - proximal, social, and biophysical - are flows of energy ormaterials or information that arise from identifiable systems or agents. In dynamic
modelling we are likely to associate land users (the human agents of land management) with modalities, institutions and macropolitical frameworks with social drivers,
and physical and ecological systems with the biophysical drivers.
Each suggests some differences in methOdology. To model proximal drivers (thosefactors most immediate to the actual change), for instance, one would want to model
the agents behind them, since it is their perceptions and decision-rules in the context
of the" exogenousll drivers that determine their actions. At the macropolitical level,a choice-oriented perspective is more limited by various structures (e.g., organisations,institutions, system constraints).
30

BIOPHYSICAL DRIVERS

Roads
Biomassburning

EH

Logging market
Population growth'~'\~'/0.\O~'So'

Figure 5.

>j.,,\o~cW\~'<i*,'Il~t<~iP

Three Dimensions of the Driving Forces of LUCC.

Our approach !n~icates that land cove,: ch~nges i;' mul~ple ways (Fig. 8). It can change
as a :esult of (1) mdepende~t changes m bIOphySIcal dnvers (e.g., ciimate and atmosphenc.change, natural erOSIOn and deposition), (ii) human activity, either direct
alteratIOn (e.g., ~eforestation) or (iii) mediated through the biophysical realm (e.g.,groundwater WIthdrawal leading to a lowered water table and to reduced stream flow
a~d alte;ed vegetation!, or (iv) a more complex chain of human activity in thebIOphYSIcal world, :VhIch feeds back. to human activity, which then directly alters land
cover (e.g., human mtroductIOn of rmderpest, change in wild herbivore population,
a?van.ce of woodland WIth tsetse, leading ultimately to mechanised clearing:
Smclau 1979).
There are .two ste~s in the. case stu~y ap'proach to disaggregating the problem. The first,
as .noted, IS to diVIde. forcmg functions mto social and biophysical drivers and proximal
dnve,:s. The second IS to analyse each set of drivers in tenns of spatial and temporalscale m an atte~pt to .r~solve at least some of the complexity and controversy
regardI.ng multIple dnvmg forces. This step draws on Holling's argument that the
dynamIc behaVIOur of many ecological systems can be explained by a few driving forces
31

MultiscaIe Driving Forces in Land UselLand Cover Change

Spatial Scale of LUCC

Social Driving

Globe

en

en
Q)
OIl

Q)
(,)

I-<

Q)

~

0

Regional
tradingsystem~OIl
I=i
CZl ......
(,)

Q)

OIl

Q)

§

(,)

U

Regionl1rbanlruralnenvork

13..W:.'!.:~~'!.~,!~:.,!!~:~~!.~..~~.,:!!~~s)~ ..!:I
CZl ......
Q)

.:::

OIl ......
til enI-<

til~......'l ~Infrastructure
Intensification
Extensification
Groundwater depletion......'l,g:Nation......
(,)

Proximate agentsand processes0......

0CZl

I=Q

Sub-nation
Landscape
Cultural
Ecological.......~!~~::?o/.....(J!c:!.e.:'!.~.e.<!!. ..
Region'"0)"Cl

Location
Irrigation
Ditching
Erosion

0)
....
0

f.L<

on

:;1'

"

f.L<

.~

:>
.>::

gp

Land-use change takes
place at these scales

'""

.~

....
Cl

Landscape

.~

Cl
Oi
0)
.~

j'"

Oi

'u0

en

.~

~

Unit of Production
Farms, households

Unit of
Production

Clearing
BurningEnhancement
Soil

Figure 6.

Spatial Scale of LUCC.
Figure 7.
32

Muliiscale Driving Forces in Land Use/Land Cover Change.
33

operating at characteristic frequencies and spatial scales - the extended keystone
hypothesis (Holling 1992). Is it possible to find such keystone processes in the complex
tangle of driving forces and systems in land-use/ cover change? This query is central tothe modelling of land-use/ cover change at the global and smaller scales.

Framework for Understanding Land-UsetCover Situations

A case study approach provides a testing ground for predictions of use/cover change
from global and regional modelling efforts. More than that, it can provide theempirical basis for confidence limits on model predictions which at an aggregate levelare bound by eeteris paribus restrictions that prove debilitating in a eeteris non paribus
world. Structural change cannot be predicted or even anticipated in such models, andtheoretical associations mayor may not hold up under changing conditions. Casebased mechanistic modelling can discriminate between valid and spurious
correlations, and the development of use/ cover situations can provide a basis for
scenarios detailing the multiple pathways of land-use/ cover change.

Socio-economic

drivers

Land-Cover Dynamics: Diagnostic Models from Empirical Measurements
Technological

Another major approach to understanding land-use/ cover change involves the use of
direct observations from a variety of empirical sources of land-cover change, including
satellite remote sensing, national censuses and land-cover inventories, and field-based
measurements. These observations can be used to directly calibrate empirical,
spatially-detailed models of land-cover change (Lambin 1994).

Regionalchangeand global
Backgroundchangeplus indirect
effects

This approach has a twofold emphasis. First, it emphasises the need to makeobservations with the appropriate frequency and spatial scale to explicitly quantify
land-cover change and land-use distributions. These observations provide afoundation upon which a range of models can be calibrated or validated. To the extent
that these measurements can provide quantitative measurements of spatial patterns ofland-cover change, they provide additional important information for: (a) analyses ofspatial relationships between land-use and land-cover change, (b) analyses of land
cover and landscape fragmentation, (c) analyses of spatial trends and spatial diffusionof land-use/ cover change, and (d) a suite of other geographically-specific dynamic
analyses. Second, spatially explicit direct measurements of land-cover change can beused in conjunction with other forms of geographical or spatial information todevelop diagnostic models of land-cover change over time. Associated spatial
information related to the physical environment (e.g. soils, vegetation, topography)
and socio-demographic conditions (e.g. population structure, economic activity, land
tenure) can be merged with the data on land-cover change to develop empiricalmodels with limited capability for predicting land-cover change over short intervals.
These models would provide a basis for defining the contemporary land-cover change(i.e. last 20 years) to begin to close the carbon budget regionally and globally, and would
also provide short term predictions (next 20 years) in support of vulnerability
assessments and other forward-looking analyses.
The Land-Use and Land-Cover Projections Working Group of the OlES Global Change
Institute on Changes in Land Use and Land Cover provides a review of an approach toempirical, diagnostic modelling of land-cover change (Robinson et af. 1994). Theirconclusion was that relatively simple empirical studies are preferable to more complex
global modelling. Many of the basic forces that drive land-use/ cover change operate
on time scales of decades rather than years. These include population size and34

11'

Figure 8.

Framework for Understanding Land-Use/Cover Situations.

35

geographic distribution, technological options, income and income di~tribution,transportation infrastructure and other variables. A methodology whIch captures
simple, strong relationships and the impact of development sequences is likely to
succeed reasonably well as a structure for projections for periods of decades .. Thus, edevelopment of empirical models provides an approach for both extrapolatIOns durmg
the period of existing measurements and projections of trends beyond the period of
measurement.

Second, it will be necessary to have explicidnformation on the spatial and geographical distribution of land-cover change with a high degree of spatial resolution.
For example, the effects of land cover on energy balance and water flux are a functionof the size and spatial arrangements of land-use and land-cover changes. As anotherexample, sediment delivery rates are related to where in the watershed land-coverchange is occurring, as a function of stream order, slope, and other geographicallyspecific factors.

This approach assumes that the forces which dominate durin~ the peri~d o.f
observation and calibration would persist throughout the perIod of projectIOn or
extrapolation. Such models based on the assumption of persis.tence are re.asonably
predictive, particularly over intervals of a few decades. There IS an emer~mg body ofliterature which suggests this approach is feasible (v. Lambin 1994). For Instance, thereis evidence that deforestation in tropical forests is persistent spatially and temporally
for up to 10 years. More work must be done on defining the parameters andapproaches for different regions and ecological zones. While such models are probably
viable for deforestation, further development is necessary for other types of land-coverchange. Even so, such models provide no information ~bout th~ ':Inderly!ng driving
forces, even if they may provide key insights or correlatIOn to dnvmg vanables. Thus;~
this kind of modelling needs to be tightly coupled to case study analyses (see above).
With added information on causality, these models can be integrated with case-studybased rate modifiers which limit or expand the spatial and temporal trends of theempirical model. The alES Global Change Institute on C~an~es in Land Use and Land
Cover Working Group on Land-Use and Land-Cover Projections recommended a
range of information which can be obtained ITom case-study based analyses to enhanceempirical models.

There are other requirements for spatially explicit models and estimates of land-coverchange. Attempts to develop global budgets of important trace gases, such as nitrous
oxide, suffer from the lack of spatial data. Frequently, regional extrapolation of trace
gas fluxes has been based on representative, or average, in situ measurements.
Matson, Vitousek and Schimel (1989) argue that global budgets could be improved byaccounting for spatial and temporal variability, and support analyses based on spatial
gradients, from which functional relationships between fluxes and land cover, ciimate,and disturbance could be derived.

tI:

An important aspect of this approach is the development of verifiable models of landcover change during the period of time in which other global change n;odels (e.~.
global carbon models) need information o~ the la~d-cover change f?rcmg functIOn:
One aim of current global change research IS to bUIld a comprehenSIve understandmg
of the linkage between three important areas: (a) global climate, (b) global biogeochemical cycles, and (c) global water and energy balance.
There are two general requirements for integrated global change models of this type.
First, it will be necessary to develop models in which actual, rather than average,
conditions and parameters are used. For example, close the glo~al ~arbon bu~getactual estimates of climate, atmospheric concentratlOn of carbon dlOxlde, oceanl~.
uptake of carbon dioxide (CO,), and biotic fluxes - both natural and ~nthropogeruc. -.w!llneed to be integrated simultaneously into a model framework. It wI~1 not be suffICIent
to use decadal mean values; matching model results and atlnosphenc measurements
over the last twenty years of atmospheric measurements requires estimates of theactual, time-dependent land-cover forcing. The objective of such an exercise :would be
to link annual changes in land cover to annual measurements of atmosphenc
concentrations and other components of an earth system m<;del. Another example .
would be the case of ENSO (the El Nino - Southern OscillatIOn phenomenon), where It
would be necessary to know the actual land use and cover change responses to thisshort term, but globally Significant, climate perturbation. The average annual rate ofland-cover change will not be a good indicator of the land-cover and land-use response
to a change in climatic patterns in a particular year.

:036

The spatial arrangement of land-cover conversion, particularly deforestation, also
influences results of model simulations of continental-scale climate and energybalance. Deforestation distributed as a few large blocks may have greater influence on
sensible and latent heat flux than the same distributed as many widely scattered small
patches (Henderson-Sellers 1987; Henderson-Sellers and Gornitz 1984).
Finally, there is increasing concern that land-cover conversion in humid tropicalforests will result in the loss of a significant number of species (Ehrlich and Wilson
1991). The impact on biodiversity is related to the total area of forest conversion andthe amount of forest fragmentation. Quantifying fragmentation requires anunderstanding of the spatial arrangement of cleared areas (Soule 1991; Wilson andPeter 1988).
Knowing what cover occurs where, its spatial characteristics, and its trajectory ofchange, therefore, is crucial to much research on global change. Yet, at this time, little
is known about the coincident distribution of land cover, land-cover attributes, andland-cover conversion. We know even less about the geometry and spatialorganisation of land-cover conversion. New initiatives must focus on spatial andtemporal characteristics of both natural land cover and conversion activities. These
initiatives are particularly important for the contemporary period (the last 20 years).
Efforts to balance the global carbon cycle will require spatially disaggregated results thatcan be coupled directly with terrestrial ecosystem models, general circulation models,direct observations of atmospheric carbon dioxide, and climatological data acquired
during the period of observation. The need for such work based on high spatial
resolution for the last 20 years and five to ten years hence is noted by the Framework
Convention for Climate Change and the IPCC.
Most of this work to date has focused on land-cover conversions, which are emphasised here, although in principle it can be expanded to include cover modification as
well. This emphasis is understood in terms of the significance of the conversion
process to several global change themes. The current conversion of tropical forests topasture and crop land, for instance, contributes as much as 30 percent of the net flux ofcarbon dioxide, even though the rate of forest conversion is less than one percent/annum. In other words, comparatively small amounts of conversion of some covers
can have significant environmental impacts.
37

Integrated Regional and Global Modelling0:

A major aim of the LUCC effort is to extend understandin.g cause-use-cover .
dynamics to improve regional and global models and proJectlOns of these dynamics.
Model systems must be developed that are geographicall~ ~ufficiently ~isaggregated(e g province sub-national or national models for descrIbmg economic systems) but
c~n'1)e aggreg~ted to the global, are multi-sectoral and sensitive to the non-lin"ar andinterrelated driving forces of land-use and land-cover change, account for majorbiophysical feedbacks, and are capable of coupling to biophysical models, s~ch as global
circulation models (Frederick and Rosenberg 1994; Riebsame e~ al .. l~94; Riebsam",
Meyer and Turner 1994; Robinson et al. 1994; Turner 1994). It IS difficult to conceive ?f
any other mechanism than models for projecting the impact of such a complex matrIXof driving forces and biophysical feedbacks.· Such models, If constructed properly, are
not limited to land-use and land-cover change, but can provide the ~uantitative
framework for scenario analysis relating to climate change, hydrologlcal.cycles,
biodiversity, sustainability, and food security as well as general changes m tastes,
values, and norms of society.
LUCC models should be crafted so that they can handle the major directions that land
use and cover and their dynamics appear likely to take over the next 50 to 100 years,
and yet be capable of dealh'g with the surprises that .will surely occur. Some of t~emajor directions are especially clear. World populatlOn growth alone together withexpected levels of economic development will fuel increasi~g demands for lan.d-based
resources. These demands will drive the expansion of certam land uses, but gIVen thatmost of the world's potentially prime agricultural lands are already in production(FAO 1993a, Crosson and Anderson 1992), major intensification is inevitable withinclasses of land uses, such as the intensification of crop cultivation. Development, or,more broadly, modernisation, is changing the structure of economies and.settlement.
An increasingly Significant proportion of land-use and land-cover chang~ IS a result ofurban demands for agricultural or forest products rather than rural subSIStence needs.
Currently, at least 25% of the world's population is engaged in peasant agriculture(Cancian 1989), covering a significant proportion of the earth's land surface. Therefore
models must be able to account for partial- or non-market conditions. On the other
hand 44% of the world's population lived in an urban setting in 1990 compared with
34% in 1960 (Simpson 1993). By 2025 the proportion will have grown to 60%, and by
2050 it is estimated that more than 75% of the developing world's population is likely
to b~ urbanised, less than 25% being economically active in agriculture. Thus landuse/ cover change and particularly land-use practices will increasingly be affected bywhat is happening in the urban economy. Models n:ust capture the sp:e~d of market
systems. If by 2050 much of the world's agr~cul~re IS large~y co~me~'C1ahsed: thenland-use decisions and resulting land-cover m thiS sector Will prImarIly be prIce- andwage-driven (Parikh el al. 1988).
Until the early part of this century, almost all of the increase in food production was
obtained by bringing new land into production; by the end of this century, almost all of
the increase in world food production comes from higher yields (Hayami and Ruttan
1985). For example, the FAO estimates that about 80 percent of agricultural production
increases in developing countries (excluding China) between 1990 and 2010 will result
from yield increases and intensification of land use; arable land use in these regions
will expand by about 12 percent (FAO 1993a: 104). In developed countries, agricultural
productivity increases are likely to command a deciine in agricultural areas as was thecase in the recent past.
38

Technological change has been and will remain central to the intensification in crop
production. In many existing models, the process by which technological change is
induced has been treated as exogenous to the economic system. Advances in theory
and the accumulation of empirical evidence, however, suggest that technolOgicalchange is largely induced endogenously (e.g., Hayami and Ruttan 1985; Binswanger
and Ruttan 1978; Pingali et al. 1987; Tiffen and Mortimore 1992; Turner et al. 1993).
Pressures from environmental constraints drives technological innovation. Given
that technolOgical change is an essential element of growth, thereby also a major
determinant of future land-use, it will be necessary to introduce the mechanisms oftechnological progress dynamically into the land-use and land-cover model.
The prototypical actors in the social and economic systems - producers, consumers andgovernments, to name three - act with more or less foresight, depending on theseverity of individual short-term constraints, amount of information available tothem, and the prevailing value systems. The value and use of land, as well as thequality of other resources, like water, forest, or mineral resources, are critical to thediscussion of viable and sustainable economic development, environmental change
and pollution control strategies. The production potential of agricultural resources isoften reduced by physical and chemical degradation, and may be at risk for negative
impacts from potential climate change. On the other hand, agriculture itself may
generate pollution, affecting, for example, water quality and tropospheric trace gas
concentrations. Environmental protection and improvement can be achieved
through various countermeasures, such as land-use regulation, purification technologies, dean-up, and emission control strategies. Consequently, it is important that themodels are able to represent such policies as well as other policy alternatives, such as
investment in infrastructure of a region or investments in land reclamation andimprovement.

Any discussion of human interactions with the environment must also come to grips
with uncertainties and resulting risks. Strategic decisions can result in virtually
irreversible impacts, such as constructing a dam, clearing rainforests for agricultural

purposes, or diverting agricultural land to urban and industrial uses. At the time ofdecisionmaking, there is often considerable uncertainty regarding future economic
costs and benefits as well as possible environmental risks. Concepts dealing with
foresight, uncertainty and risk must be given due consideration in designing LUCC
model systems geared towards long-term projections of human-environment
interactions.
Biophysical feedbacks play a critical role in long-term dynamics of land use and land
cover, but there is no consensus on their strength or temporal and spatial scales. For
example, estimates of soil erosion losses and their implications for long-term
agricultural productivity and land-cover change may have been exaggerated. The UN
estimates of desertification (UNEP 1987; UNEP /GEMS 1991) and others on global soils
loss (e.g., Rozanov et al. 1990) are not without critics who suggest that not only arethese estimates inflated but the economic risks of soil loss have been exaggerated<Hellden 1991; Graelz 1994; Crosson and Stout 1983; Rhodes 1991). Some earlier
observers suggested that overgrazing in parts of Africa would shortly destroy thelandscape for that activity, but other assessments taking account of traditional
management practices, local soil conditions, and the spatial characteristics of soil
erosion and deposition suggest that substantial land-cover degradation and change at
the sub-continental scale are 100 or more years away (Biot et al. 1992), though this does
not mean that there is no ecological degradation (de Queiroz 1993).
39

Over a long time span, there may be major changes in the driving forces: some ofwhich are likely to be positive rather tha.n negative for land co.ver (~.g., Improvements
in management practices and reduction In t~e human popul~:lOn dl:ectly dependent
on crops or livestock for subsistence or c~sh. Inco:ne). TI:e cnti~al ~Olnt here IS thatmodels must be able to handle major vanations In the bIOphysIcal Impacts andfeedback of land use, and their projections must incorporate b?th negative andpositive biophysical considerations. They must take note of: (I) the vagueness ofdefinitions about cover or cover impacts; (il) the uncertainty of causes, human or
physical, and their linkages; (Hi) the uncertainty of estimating or projecting impacts
into the future; and (iv) the difference between short-term human responses andlonger-term adaptation and innovation.
Finally, it is increasingly clear that supply of and demand for water fro,:, a?Ticultu:e, inparticular for irrigation, will be criti.cal.eleme:>ts of th; land-use dynamICS III certain
regions, such as West Asia and semI-and Afnca. AgrIculture accounts for as much as
70-80 percent of water use worldwide (e.g., Kulshreshtha 1993), and other s;ctors arecompeting for more water resources as countries de,:el?p. In .'ome coun~les a very
high proportion of cropland (e.g., shares of cropland Irrigated III 1989 were. Egypt 100%,
Pakistan 78%, China 47%, Iraq 47%, World 16% [PosteI1992]), and ~ven a greater.
proportion of crop production, depends on irrigation. The increasmg shortages m thecoming decades projected by a number of water-use assessments hold major
implications for land-use/ cover change (Postel 1992; Gleick 1993; Kulshreshtha 1993).
Moreover, these shortages may be amplified by land-cover change, notably
deforestation, and by possible global warming. Consequently, the land-~se/coverchange models need to ~d~ress. two specific~sp~cts ?f t~e water sect?r: (I) the ..
mechanisms of water dIstributIOn and use, I.e., InstItutions, water rights and pncmg
mechanisms and (il) linkages of land-use and land-cover change to variability andchange of str,cks of usable water resources. v.ery few global. agricultural models haveattempted to do so since the Systems AnalYSIS Research Umt Model (~ARUM) ?f .themid-1970s which had a water development sector (HMSO 1977), and mcluded irrigation in ~he agricultural production functi?n (v. FAO 19?3a). Fortunately, however,a number of effective approaches at the natIOnal, sub-natIOnal, and watershed levels
point the way for more comprehensive attempts (e.g., Strzepek et al. 1994).
With these characteristics in mind, it is hardly conceivable that a single model iscapable of providing a comprehensive global yet geographically detai!ed assessment ofland-use/cover change. LUCC-related global-scale models are not WIthout exemplars,
however. These models were generally built for specific purposes and have applied awide range of methodological approaches and theoretical rigour. Several examples
illustrate.
The impacts of climatic change on the location and extent of natural ecosystems(e.g., Bultot et al. 1992; Emanuel et al. 1985) and agrosystems (Pa:ry et al. 1988a,b) .
have been analysed. These static studies conclude that large shIfts could OCCur ~Ithimmense consequences for current land-cover patterns and agrIcultural potentIal.
The climatic change studies address only a few aspects of the earth system, but havebeen improved by including the transient response of eco- and agrosystems andaccounting for the direct effects of increasing atmospheriC CO, (e.g., Solomon 1986).
None of these studies accounted explicitly for changes in land use, however; they
were attempting to assess the impact of global climate change.

40

Among the first global change models was the Integrated Model to Assess theGreenhouse Effect (IMAGE 1) (Rotmans 1990; Rotmans et al. 1990). This model aimed
to project the concentrations of different GHGs in the atmosphere for the period 1900
to 2100. IMAGE 1 consisted of a series of highly aggregated sub-models including anenergy-emissions module, carbon cycle models, an atmospheric chemistry module,
and so forth. The model was driven by different population and energy scenarios, andit simulated the trends for atmospheric concentrations of different greenhouse gases,from which a global mean temperature change was computed. The approach of thismodelled to the development of the ESCAPE framework (CRU and ERL, 1992), in
which a more advanced climate module allowed for linkage of several different
impact modules: sealevel rise, agriculture, and ecosystems. These models had major
disadvantages with respect to changes in land use and their human causes. Changes inland cover were prescribed, often only accounting for tropical zones, and few covertypes were represented. Deforestation rates were mainly extrapolations of the highrates listed in the early 1970s and 1980s, while current rates have decreased (Skole andTucker 1993). Furthermore, the consequences of the impacts of global change did not
feed back into the causes neglecting important feedback mechanisms (Vloedbeld andLeemans 1993).
An ambitious attempt to model complex relationships between agriculture and therest of the economy was the IIASA global model of the world food and agriculture
system (Fischer et al. 1988). It consists of a number of linked national models based on
welfare economics and applied general equilibrium (AGE). The model system
includes the dynamicS of population and rural-urban migration, socio-economic
factors, capital accumulation, and market clearing conditions to project demand,
supply and agriculture land use at aggregate national level. Recently, elaborate processcrop models (IBSNAT 1989) have been coupled to the IIASA model (Rosenzweig et al.
1993; Fischer et al. 1994). Although these studies were rather detailed and covered
large regions, they emphasised global change impacts on agriculture only and did notassess future changes in land-use and land-cover of other sectors.

Another example of a long-term bioeconomic assessment with reasonablegeographical detail was the spatial equilibrium model formulated in a study of theeconomic effects of global climate change on U.S. agriculture. The model represents
production and consumption of 30 primary agriCUltural products including both cropand livestock products. The model consists of two components, a set of micro- or
farm-level models integrated with a national sector model. Production behaviour isdescribed in terms of the physical and economic environment of agricultural
producers for 63 production regions encompassing the 48 contiguous states of theUnited States. Availability and use of land, labour, and irrigation water is determinedby supply curves defined at the regional level.
An integrated economic analysis of the potential impact of global warming on a fourstate region of the United States (Missouri, Iowa, Nebraska, Kansas) is known as the
MINK study (Rosenberg and Crosson 1991). The study team has included four sectorsof the economy (agriculture, forestry, water, and energy) in the analysis, and aims for a
spatial representation of the mutual relationships and interdependencies between
these sectors and climatic conditions.

A different set of models was developed to assess availability of natural resources
suitable for food production and forestry. The basis of many of these models was theAgro-ecological Zones approach developed by the FAO (FAO 1978; FAO/IIASA/
41

UNFPA 1982; Brinkman 1987; FAO/IIASA 1993). The approach assesses the local
suitability to grow crops on the basis of climate, soil and crop characteristics. The
approach was used in several applications; for example, to analyse land use in thecontext of national development planning (FAO/IIASA 1993) and to determine crop
distribution and yields under different climates (Leemans and Solomon 1993).

Integrated Land UselLand Cover Modelling

Demographic
Model

A global integrated system that addresses explicitly changes in land use and cover is the
IMAGE 2 model (Alcamo 1994). It includes a rule-based land-cover change model thatis linked to the changing demand for agricultural commodities (Leemans and van den
Born 1994; Zuidema et al. 1994). The model aims to simulate the transient dynamics ofatmospheric greenhouse gases, accounting for the major interactions within theearth's system. The human driving forces are derived from exogenous scenarios for
demographic, economic, and technological developments, which are implemented fora number of broad aggregate regions. However, these exogenous forcing functions
affect the land-use system without accounting for demographic, economic, or
technological feedbacks in response to simulated scarcities.

Policies,
Institutions

Most of the livestock models and the underlying vegetation dynamics models of thoselinked explicitly to rangeland management are too static, too partial, or too micro toprovide a starting point for land-use and land-cover change modelling. They tend tobe location-specific or to focus on biophysical relationships to the exclusion of
livestock/ grazing land management and sodo-economic aspects. Nonetheless, someof them contain lessons and approaches useful to land-use and land-cover change
modelling at higher spatial scales. Thus, although FLIPSIM (Firm Level Income andPolicy Simulator Model) (Richardson and Nixon 1986), which is a dynamic, stochastic
simulation model, was developed originally for micro-level analysis, it lends itself toscaling up to the regional or national level through the representative farm approach.
Representing an ecological modelling approach, vegetation cover and soil organic
matter dynamics in managed (and unmanaged) grassland ecosystems can be assessedwith the CENTURY model (Parton et al. 1987; Parton et al. 1993). Related to this is
SAVANNA (Coughenour 1993), a process-oriented model of pastoral ecosystems that
could be applied to larger regions.
At the national and regional scale, there are forest models that contain more detailed
treatment of the socio-economic driving forces for land-use/ cover change and notably
for human colonisation and deforestation (e.g., Grainger 1990; Southworth et al. 1991;
Dale et al. 1993). Some of them are spatially explicit and contain feedback relationships
to simulate the impact of land-use on sustainable development. In the main,
however, the feedback relationships in both small- and large-scale models tend to beuni-directional, with little, for example, on how the biophysical side of the model
affects the socio-economic. A recent review of modelling approaches applicable todeforestation processes can be found in Lambin (1994).
Appropriate LUCC models will require the kinds of improvements noted above.
Fashioning them and assessing their contributions to the robustness of the models do
not pose insurmountable problems. The complexity of the problem and pastmodelling experience suggest that for a comprehensive assessment and projection ofland-use and land-cover change a variety of models will need to be developed andintegrated. Figure 9 shows a generic integrated LUCC model system indicating several
important components: a demographic component and modules for representingchanges in social expectations/ values and policy settings, an economic model, a landuse allocation component, models of resulting land cover and environmental impacts,
42

Values,Expectatious

International

ClimateSystem~::~~A~lb:e~d~o'~~~';C~YC:k""e"ro''''''''''''''
Figure 9.

Integrated Land Use/Land Cover MOdelling.

and a land p~oductivity module, feeding the simulated impacts back into the economic
and other SOCial components, thereby closing the feedback loops. The task is to selector develol? models that are appropriate to the specific questions asked, methodologically conSIstent when c~upled, and compatible in time and spatial scales. Importantly,
the land cover ~nd e?vlt?nmental impacts, land productivity, and climate system~odul~s as depIcted m FIg. 8 should link directly to other global change models,mcludmg those developed llIrough the IGBP.

La~tly, the qu~stions of sensitivity analysis and model verification and validation areof Importan~e m the deliberations of Focus 3. It is commonly agreed by modelling
methodol?gI.sts that model validation is one of the most important stages in the::,odel ~Ullding pr?cess. Despite this agreement, formal methods of model validation
nly eXlst for certam types of models, usually those applied to systems that exist in thereal world and where it is possible to conduct a series of active experiments. In such43

:if

cases statistical methods can be used for validation (e.g., Schruben 1980). Many authors
point out that model validation should be goal-oriented (Lewandowski 1981). In theprocess of developing LUCC models different situations will arise. Some models willserve to improve our understanding of certain processes. Other models, specificallythose developed in Focus 2, can be used for short-term forecasting. In the process ofgenerating long-term LUCC projections, models will be used for scenario analysis andnormative goal-seeking (e.g., optimisation). The validation methods to be applied will
have to vary with the type of model being used. In many cases formal validation
methods will not be available. In such situations, the necessary validation needs tostress: (i) rigorous testing of specification and methodological foundation of themodels; (ii) thorough testing of model sensitivity with respect to parameterization
including backcasting; (Hi) sensitivity of model results with respect to quality of useddata sources; and (iv) econometric estimation of parameters as warranted by quality
and amount of available data.
Issues of Spatial Scale
Understanding the local, regional, and global dynamics of land-use/ cover change
obviously requires crossing spatial and hierarchical (as well as temporal) scales(Figs. 6-8). At present, our understanding of the links between scales is poor. Yet,
it is well known that changing the spatial scale of the analysis may change the result(e.g., Meyer et a/. 1992). Many global and large-scale sub-global analyses identify
variants of the so-called PAT variables (population, affluence, and technology) as
having the strongest statistical correlations with environmental change (Bilsborrow
and Okoth-Ogendo 1992; Rudel 1989), often implying that the specific variables inquestion are the underlying driving forces of change. Local case studies, however, do
not always concur. Indeed, if a common theme emerges from them it is that the PAT
variables are much less important in LUCC than institutions, policy, or other suchvariables of social organisation (e.g., Arizpe, Stone and Major 1994; Kasperson et al.
1995; Zaba and Clarke 1994). Alternatively, in these cases, PAT variables may have adelayed or mediated association that masks their influences.
Why this is so is not well understood. It may reflect the biases brought to the study bythose engaged in either scale of analysis, a conclusion that, if substantiated, would be ofno minor Significance. It may also reflect problems of aggregation/disaggregation.
There is yet a more profound possibility, suggested by, but not dependent on complex
systems theory. Such a possibility can be summed up in a few straightforward but
empirically vexing principles. These are:(i)

That natural and social systems at different temporal and spatial scales areimbued with different kinds and degrees of organisation. This allows us to treat
the scales of social and natural systems together only in certain circumstances.
Fossil fuels pose a considerable problem for linking social to natural systems, forexample, since they allow the focusing of concentrated energy from a much larger
scale in the past.

(Hi) That the relationship between scales of organisation (cross-scale dynamics) is

unknown but important to determining scale boundaries and the influences ofkey variables on emerging properties at different scales. Scales of organisation are
not the same as scales of observation (level of analysis).
(iv) That temporal scales are more than simply chronological, and must account for
natural and social history, with their implications for qualitative shifts in land
cover and use through time. This suggests recourse to notions of path-dependentchange and limited reliance on Single-equilibrium models or those tied to time asa simple Chronological index.
These issues are complicated by the fact that spatial, hierarchical, and temporal scales
must be understood in terms of their real world, measured (empirical), and modelledcontexts. Real world scale effects exist in all land-use/cover phenomena but can only
be assessed by actually measuring their properties. Since all such phenomena andproperties cannot be measured, we are limited to empirical scales, which are, in asense, subjective because of the choice of data and the selected spatial and temporal(also hierarchical) stales. Similarly, models are generally only valid for given, welldefined scales. Thus, LUCC must pay considerable attention to the systematic
assessment of empirical and model scales. Case studies must be selected in such a waythat they can be scaled up to less detailed levels.
LUCC research is confronted with two different scale effects that must be taken into
account: (i) each scale has its own specific units and variables; and (ii) the interrelationships between sets of variables and units change with scale. How can valid
regional models be developed and linked to global models given these effects?
The solution lies in the development of a truly hierarchical approach in bothobservation and explanation of the processe,s of land use/cover change. As different
scales allow us to answer different questions, explanation of land-use drivers can only
be achieved by combining observations and explanations from different levels of thescale hierarchy. A comprehensive study of LUCC requires a nested set of scales andcorresponding data. Once scale effects are known and quantified, models can be madefor each measured scale level. The scale hierarchy then functions as a key for crossscale dynamics.
The following example is drawn from a study of the drivers (or exogenous variables)of land-use/ cover in Costa Rica (Veldkamp and Fresco 1995), with drivers selectedfrom environmental, population, and agricultural classes. The population and~gricul.tural data for 1973 and 1984 were taken from the country's census and converted
mto grid cells. The selected minimum grid size (0.10 geographical grid or about 7.5 km
x 7.5 km or 56.25 km') was based on the estimated average district size or the finest
resolution possible with the census. These data were matched with biophysical map
data converted to similar grids. The 0.10 grid data were aggregated into five larger
grids of 225 km', 506 km', 900 km', 1,406 km', and 2,025 km' or 4, 9, 16,25, and 36 grids
respectively on the x-axes of Fig. 10.

(ii) That such organisation of systems, both natural and social is loosely hierarchical;
that is, systems are funcionally or operationally layered in their relationships
with one another. The description of such hierarchical relationships isimportant.

Multiple regression models were made for the six spatial scales for each available year
to explain the variance of major land-cover classes. Here we illustrate using
permanent crops.

44

45

"

1973

u

l~

-E 1.0I8~.aAgricultural labour force (ALF)•••••• Coefficient of detenninationU- - Urban population (URB)

0.7
0.6

.•..... Relief(REL)

~.

.~
"'0

_

0.9

r,7'¥---""'."'..;...;..:;;..",..",..;;;..:;:...:::::1 0.4
-0.

0.3

.0.

0.2

~ .0.60.1-<1.8

i,--,_.-_.-_---,,-__-r'0.0
1

4

9

16

"

36

No. of aggregated grids

~

1984

U
1.0

1.0

.~ 0.8lE 0.6•u

0.9

IISimilarly, it is generally conceded that the relationships among global, national andsubnational scales change as the international system changes. So, the rules for
producing, consuming, and trading commodities change with the advent of global
shipping in the 1870s, and the' onset of the Great Depression. In fact, the scalar issue
revolves in part around the division between discussions of "appropriate scale"(i.e., the strategy of addressing scales without crossing them), versus the complementary need to analyse the relationships between scales at different times in society
and nature. The" appropriate scale" concern would suggest deriving a function formapping local to national to global linkages, or partitioning the data more coarsely andapplying local equations to the data, or recalibrating the local equations to coarser data.
The cross-scale concern is explicitly empirical and focused on tracking influences acrossscales of organisation through historical time, allowing for - and even emphasising system shifts across spatial and temporal scales.

0.8
0.7

0

0.4

0.6

!1, 0.0

0.4

~ ·02

0.3

]

·0.4
-0.6

0.2

it) -O.S

0.0.~ 0.2iii

Without specific attention to scalar dynamics, as illustrated for the Costa Rican case, anumber of research possibilities might be ignored to the detriment of the study of landuse/cover change. In this example, for instance, the influence of global agricultural
prices on cropping decisions by local agriculturalists is empirically unclear, but often
modelled as a given relationship from global to local scales. For land use and cover tobe integrated across those scales, static model parameters must give way to plotting
specific cross-scale transfonnations, which are much more sophisticated and subtle
than an economic pass-through mechanism".

O.SR2

0.1
1

4

9

16

36

25

No. of aggregated grids
Figure 10. Fit of Selected Variables to Permanent Crops in Costa Rica, 1973 & 1984.

Regression models of the drivers of permanent crops showed varying fits (30% to 75%)
with spatial scale for both years (1973 and 1984), but a m~~um fit was observed forthe same range of aggregation level (506 km' and 900 km) (Fig. 10). In 1973, therelative relationships between the driving forces and permanent crops showed that theagricultural labour force had a strong positive relations~!, with p.erm~ent crops, .
while urban population had changing negative and pos:bve rel~ti0r:shlps, and ~ehefdisplayed only a slight positive relationship. These findmgs vaned httle by spatial
scale. The data, however, show a clear change in the relative contributions of thedriving force by spatial scale. The positive cor:tribution of agric~lbiralJabour
decreased with an increase in spatial scale, while urban population s~tched fro.mstrongly negative to a positive relation with scale increase - a change m model fit andvariable contribution with spatial scale. The scale of 506 km' (9) revealed a completely
different picture from that for 2,025 km' (36). The expl~na~ions for th~se di.fferences are
not important for our purposes here; the important pomt IS the relationship between
spatial scale and statistical outcomes.
46

Issues of Oassification and DataClassification

The study of land-use/ cover change requires either standardised classification (ortypologies) of use and cover and/or data provided in a manner that allows various
standardised sets of classifications to be constructed. Methods of defining land in termsof climate, topography, soils, vegetation, or productive purpose have a long history.
Yet there is no satisfactory and commonly accepted method of defining and classifying
land use globally, let alone a definition of the major classes of land use as such
(Duckham and Masefield 1970; Evenson et al. 1970; Kostrowicki 1984). This situation,of course, thwarts the systematic collection of data pertinent to use classification. The
situation is much better for land cover, where global databases exist, although, again,
no agreed set of principles is applied worldwide (for a review, see Leemans et al. 1995).
Land use lacks a common tenninology and unit of analysis, a problem that longplagued soil and vegetation classifications. In some cases, no distinction is madebetween use and cover; in others, use is considered purely as the socio-economic side("what people do ") of biological cover ("what you see "). It must be recognised,however, that land use ("what people do ") also has a biophysical side that is not
identical to cover and is not captured in classifications that follow from that emphasis
alone (Fig. 3). In short, the land-use/cover community requires classifications thatmeet several research needs and, therefore, involve different data.

47

Land-Use/Cover and Classification Dimensions

The community's varied needs suggests that land-use/cover classification should
involve at least three dimensions. The first dimension involves the concrete
manipulalion of land characlerislics: "how the land and cover are used", as in theslash-and-burn sequence of cutting, drying, burning, planting, weeding, andharvesting. These manipulations are biophysical in nature and are not always easy todetect. They can range from strategies that protect an ecosystem (e.g., wildlife
preserves) to minor appropriation of photosynthetic products in which most of theecosystem structure and functions are left intact (e.g., culling trees among some forest
gatherers or grassland burning among some pastoral groups) to the creation of an
artificial or semi-artificial system bearing little resemblance to the ecosystem thatwould exist without human presence (e.g., drainage of wetlands). These manipulations can only be determined over their full sequence or time period. A framework
already exists to describe land use through the operation sequence concept (Stomph
and Fresco 1991; Stomph el al. 1993), which involves the relevant features relating toenergy, nutrients, water, implements, and the timing of applications. Finally, the unitof analysis in this biophysical meaning of land-use is a geographical one, referring to
the field, plot, or part of the land surface in question.
The second dimension refers to the land user's purposes or objectives served by the
manipulation: "why the land is used". These objectives may vary considerably amongindividuals, societies, and historical periods, but generally include the satisfaction ofneeds for income, food, feed, fuel, pharmaceutical products, shelter, and landscapevalues. This dimension should not be confused with biophysical land use and cover.
The same need for, say, 200 kg of rice per ha may be satisfied through very different
land uses and covers, ranging from long-fallow shifting cultivation with average
yields of less than 1,000 kg/ha to irrigated triple-crop rice production with annual
yields of up to 10 t/ha. The purpose/objectives dimension is important, however,to distinguish such critical attributes as subsistence versus market orientations, whichusually respond differently to changing conditions. This dimension of land use andcover nearly always operates at the level of the farm or management unit; it relates,
therefore, to a soda-economic unit.
.
Few classifications of purposes/objectives have been developed and applied globally,
although location-specific studies exist from which some universal descriptors may be
drawn. Typologies are far more prevalent here than classification (v. Turner andBrush 1987). If this dimension is to be incorporated into a classification, suitable
descriptors (i.e., purpose equivalent of the biophysical operation sequence [above])must be found. The unit of analysis (parcel, farm, farming system, household) also
needs to be defined. Classification of land users is probably the easiest route to a
purpose-oriented classification. It is noteworthy that the objectives of land use are notnecessarily coincident with biophysical manipulation.
The third dimension of use is the broader biophysical and socio-economic circumstances or underlying conditions. Biophysical conditions - for example, climatic zone,
soils, occurrence of pests and diseases - determine in part what type of land use andcover may be found. Bananas cannot be grown in Scandinavia outside greenhouses,
and rubber in Central America cannot be grown because of disease pressures, although
the climate is suitable. Detailed world databases on biophysical resources (e.g., topography, soils, climate) and a global agreement on what constitutes important
descriptors will permit the classification of these broader biophysical conditions.
48

What land use and cover is chosen within the boundaries they set is a function of thesocio-economic and technological circumstances, such as demographic factors,
marketing, and infrastructure systems, and land tenure arrangements - commoniyreferred to as socio-economic land-use drivers. Even within a homogeneous
agrociimatic and socio-economic region, however, individual farming units differ inland use and land cover.
Major classification efforts aimed oniy at the broader circumstances of land use andcover are unnecessary nowadays because of data storage and processing technology(Anderson et al. 1976; Vink 1975). New databases from remote sensing will allow
individuals to build different typologies for their specific needs. However, there isconsiderable merit in disentangling the broader biophysical and socio-economic
circumstances from land use and cover sensu stricto, as in the FAO/UNESCO soil
classification (1974, 1991; also FAO 1993c).
LUCC research should emphaSise the development of classifications and data on thethree dimensions noted. Global classifications combining these dimensions into landuse systems have proven difficult to achieve, in part because the kinds useful fornational purposes may not be so for international comparative research. Of course,
having the three dimensions should allow the construction of the specificclassification for local-level analysis (Fresco and Westphal 1988; Gils et al. 1991).
Previous Attempts at Land-UselCover Classification

Land-use/ cover classifications, which can be traced back to early civilisations, were
almost always based on field surveys until the middle of this century. In the late 1960s,
however, such surveys declined because of their costliness compared to new survey
techniques based on computer processing of aerial photographs and satellite images.
These technologies directed classifications towards the land-cover attributes captured
in such imagery. In fact, many existing land-use classifications are based on thevegetational and artificial cover of the land surface: the World Land Use Classification, The Canada Land Inventory and Land Use Classification, the Second Land
Use Survey of Britain Classification, the Canadian Land Use Classification, and theWorld Map of Present-Day Landscapes (Moscow State University-UNEP 1993;
Rjabehakov nd.), to name a few.
World-wide classifications based on cover alone are insufficient for the use
dimensions noted above; a few attempts to include these other dimensions exist(v. Kostrowicki 1983).
A recent review (Mucher el al. 1993) indicates that none of the many "land-use"classifications is acceptable or satisfactory in a global change context. All reviewed
classifications suffer from one or more of the following drawbacks:(i)

The lack of a sound definition of the units of analysis, ranging from field to farmto region '(confused with mapping units)(ii) Overlapping land-use classes (because of the lack of clearly defined criteria; mosthierarchical classifications are oniy comprehensive at the first level, and are far
from comprehensive at lower levels)
49~

(iii) The near-total absence of quantitative class boundaries (critical or thresholdvalues of the criteria), adding a significant subjective element to land-use
assignments(iv) The combination of land use with other dimensions, such as climatecharacteristics, that may influence land use but are not inherent features of it(v) The multiplicity of land-use classification objectives, often closely tied to regional
or disciplinary foci.
Past attempts at classifying land use and cover are either not global in character or not
sufficiently comprehensive. Furthermore, existing classifications do not use common
classificatory principles and often conflate use and cover. Recently, several international agencies, including FAO and UNEP, have initiated a discussion on the subjectof land-use/cover classification and databases and have commissioned preparatory
studies for the purpose ofrectifying the situation.

Data
Only a few datasets on land-use/cover change exist that are readily adaptable for LUCC
now - that is, spatially comprehensive and sufficiently accurate (e.g., Flint and Richards
1991). There are three areas of uncertainty that need much better documentation andanalysis: (i) the state (e.g., information on biomass, net primary production, etc.) anddistribution of existing land cover, (ii) the rate and distribution of land-cover conversion, both historically and currently, and (iii) the underlying factors which describe
land-use and land-management practices. Clearly, some combination of historicalreconstruction and remote sensing is needed to refine the first two areas. The third
area of uncertainty will require closer linkages of physical and social analysis.
Coarse resolution remote sensing data could provide the basis for defining the
distribution of current land cover. The advantages these data have over existing maps
are temporal consistency and .an explicit definition of actual, rather than estimated,boundaries between cover types. The most straightforward approach would be toderive maps of current land-cover types from remote sensing measurements along
pre-defined classification systems. It seems unlikely that a single classification will suit
all needs, but much could be gained by initiating international efforts to collect thenecessary datasets from existing satellite sensors (such as AVHRR) from which various
classifications could be made on a case-by-case basis. A remote sensing-based map ofcurrent land cover could form the basis of a pre-disturbance land-cover map, created bycorrelating existing natural land cover with physical variables (e.g., temperature,
precipitation, edaphic conditions), or through approximation based on simple
assumptions of contiguity and spatial clustering. With such maps of both current andpre-disturbance land cover, it might be possible to reconstruct the history of land-coverchange with the addition of geographicallY'referenced time series of human use andconversion, such as maps of the expansion of deforestation. Since much of theanalysis is spatial, a geographic information system (GIS) would be used to organise thedata and analysis.
One of the most important land-cover changes is the conversion of temperate andtropical forests. The use of coarse resolution remotely sensed data (1 km or greater) to
map land-cover conversion has frequently been considered the optimal approach for.
50

monitoring land-cover change since it requires fewer data than do high resolution
sensors (less than 100 m). However, when coarse resolution datasets have been usedin the past, they have tended to overestimate deforestation. This overestimation bias
is partly related to the geometry of clearing, so a single conversion factor cannot readily
be developed. Considerable work remains to be done before mIxture modelling, andother techniques which could derive an accurate estimate from coarse sensors, can beused. Meanwhile, the best approach appears to be one based on high-resolution datafrom such satellite systems as Landsat.
While high resolution satellite data are improving measurements of deforestation,
the dynamiCS of clearing, abandonment, regrowth and re-clearing are completely
unknown, yet could be important to analyses of the net flux of carbon. In addition
to quantifying deforestation, the use of high resolution data provides detailed information on regrowth and abandonment. More difficult still is the monitoring ofchanges in non-forest vegetation. High resolution satellite data will be invaluable
sources for measuring these changes but considerable methodological work remains
to be done.
Documentation of land-cover change is only the first step toward understanding theunderlying agents of the change. Systematic and sub-national data on land-use
management, including the operational sequences and techno-managerial inputs, arerequired. Likewise, systematic and sub-national data on a range of socio-economIc anddemographic variables are needed. Tenurial arrangements, informal market data,
population growth rates, levels of subsistence and market production, and other suchcomplex data are examples. Such data may prove very difficult to collect; much careshould be taken in formulating research approaches (see Section8).
Policy Relevance of LUCC Research Programme
The human driving forces of land-use/ cover change are the primary foci of LUCC, set
within the biophysical parameters of land cover. LUCC offers the scientific researchand policy communities a global-to-Iocal (and local-to-global) basis for analysing how
land cover is converted, what kinds of land uses and covers result, the local, regional,
and global environmental effects of those results, and the likely points where humancommunities can intervene to change the trajectories of global land use according tochanging needs and values.
In short, then, LUCC proposes to provide a broadly augmented, scientifically rigorousand dynamic information base that can inform the policy process at the local, national,
and transnational levels. Specifically, it can provide information relevant to land-use,resource, and environmental policy and planning, including the human responses toenvironmental change and the sustainability of rural activities. LUCC cannot, in theabsence of a clearly stipulated set of policy values and institutional settings, offer policy
prescriptions. Nor should it aspire to do so. But it can provide science advisors andpolicymakers with: (i) the informational backdrop for improved policy (within a given
policy framework); (ii) the databases for scenario analysiS and improved adaptive
management systems; improved pathways to integrated assessment and observation;
and, (iii) a long-range set of scientific goals to assist in setting future policy priorities
within the complex of global environmental change as it occurs and ourunderstanding of it grows.
51£

4. Structure of the LUCC Plan and Links toother IGBP and HDP Activities

C. (Questions 2-5) Empirical identification of the major driving forces (exogenous

variables) of land-use change as they relate to the land manager and use-system for
critical land covers.
D. (Questions 2-5) Empirical identification of the major kinds of land-use/ coverchange dynamics operating throughout" the world.

A LUCC 'progra~e that serves the wide-ranging needs of the global change
commumty ~eqUlres an appro.ach that is broad in its implications but specific in its
content and ImmedIate objectives. LUCC received its mandate from both IGBP and
HDP because of the recognition that land-cover change was a crucial component of
global change and that it:s dynamics could oniy be understood through an integrated
SCIence resear?, agenda mcorporating nature and social science approaches. Such a
mandate requITes the engagement of a broad range of perspectives and approaches(Turner 1991). It also demands focus on some specific science goals, through which
other IGBP and HDP projec:s and activities link into the LUCC agenda. Appropriatebalance among these needs IS best achieved by identifying the major science questionsof LUCC and linking those questions to specific research outputs (research foci).
Signif~cant improvement in understanding land-use/cover change for the range ofuse:s m the .global-change arena would follow from improved resolution of these five
major questIOn:
1. How has land cover been changed by human use over the last 300 years?
2. What .are the major human causes of land-use change in different geographicaland h,storIcal contexts?
3. How will changes in land use affect land cover in the next 50-100 years?
4. How do immediate human and biophysical dynamics affect the sustainability of
specific types of land uses?

E. (Questions 1 and 3-5) Refinement and development of new suites ofgeographically explicit land-use/cover models using both empirical-based
diagnostic and behavioural-based regional approaches.
F. (Questions 3-5) Refinement and development of new suites of prognostic
land/use models capable of incorporating biophysical and climate impacts.
G. (Questions 3-5) Determination of the sensitivity of such models for use inassessing future scenarios of land-use/ cover drivers and conditions.
The major questions may be addressed through a range of approaches, some ofwhich may require assessments of competing theoretical models, whereas
others may well invite empirical examinations, without explicit recourse toformal theoretical constructs. Both modes of analysis have proven useful.
The IGBP-HDP LUCC research projectlprogramme, therefore, seeks to improve understanding of land-use/ cover change while maintaining an openness to the varied andcompeting community of approaches to the problem. It does so through a science I
research plan that integrates empirical and comparative research with modellingthrough three research foci and two integrating activities (Fig. 11):
Focus 1: Land-Use Dynamics - Comparative Case Study Analysis
Focus 2: Land-Cover Dynamics - Direct Observation and Diagnostic Models
Focus 3: Regional and Global Models - Framework for Integrative Assessments
Integrating Activity 1: Data and Classification
Integrating Activity 2: Scalar Dynamics

5. How might changes in climate and global biogeochemistry affect both land use andland cover, and vice versa?
~ecau~e ~e. study and analysis of research addressed by LUCC covers a new
mterdlsclplinary ~rea, and because it is recognised that considerable integration of
LUCC research WIth that of other Core Projects will be necessary, these goals will

Research FociB. (Q~estions 1 and 3-5) Detern:ination of the spatial scale and pace of changes in the
major land uses and covers, mcludmg cover conversion and modification.

Focus 1 is a case-study approach to understanding the dynamiCS of land use and coverby kind or class of situation (usel cover context). It is constructed on the premise that alarge measure of understanding these dynamics is gained from the perspective of theland manager (i.e., fanner, forester) who is the agent of direct change in land use andcover, responding to the events and processes that impinge upon this use. Focus 1,
therefore, aims to identify the major kinds of land managers and the dynamics inwhich they are engaged (Question 2) but in so doing, engages the kinds of uselcoverchanges that have taken place in the past (Question 1) (Table 2). Focus 1 will plan andcarry out comparative case studies of land-use/ cover dynamics using common
protocols and standardised terms and measures of land use and its dynamics; analyse
the results to identify and demarcate spatial situations of land-use/ cover dynamics,
and improve understanding of the intricacies of these dynamics, stating thegeneralities that can be gleaned about them; and build from these cases and analyses to52

53

only be met through close collaboration with other Core Projects.
Investigating these questions requires research progress towards the following
goals:A. (Question 1 and 5) Improvement of the data and data-based estimates for the~ajor l~d cov~rs and the changes in these covers for the last 300 years, withmcreasmg spatial and temporal resolution for last 100 and 50 years, respectively.

Table 2.

Matching LUCC's Major Questions and Goals with its Science/ResearchPlan.

~jor Questions

boundary conditions &-"T~-

exogenous
influences
specifics ofIntegrating Activities• Data & Classification

behaviour1• Scalar Dynamics

t. How has land cover been changed
by human use over the last 300 years?
2. What are the major human causesof land-use change in different
geographical and historical contexts?
3. How will changes in land use
affect land cover in the next 50-100
years?
4. How do immediate human andbiophysical dynamiCS affect thesustainability of specific types ofland uses?
5. How might changes in climate
and global biogeochemistry affectboth land use and land cover?

ScalarFocus 1:
Focus 2:Focus 3:lData & CIas
Land-Use ~nd-Cover Regional &Dynamics
Dynamics Dynamics Global Models
./
./
./

./

./

./

./

./

./

./

./

./

./

./

.../ ........

.../ /

land-cover transition
probabilities

spatial pattern dynamics

Figure 11. Structure of LUCC Science/Research Plan.

local to regional explanatory models of land-use/cover change. Focus 1, therefore,draws the specificities and generalities of regional situations of land-use/cover change
for incorporation into Foci 2 and 3, making regional and global models more sensitive
to the great variations in LUCC. It provides land-cover transition probabilities to Focus
2 and the local to regional specificities of the human and biophysical forces of change to
Focus 3.
Focus 2 incorporates direct observations into spatially explicit empirical models ofland-cover change processes. The emphasis of this Focus is to capture the dynamics ofland conversion and modification for key regional issues, such as conversion oftropical forests, degradation of savanna systems, and the like. It accomplishes thesethrough the use of remotely sensed imagery of land-cover change to capture the spatial
range and pace of cover change, and combines the results with case study informationon land-use dynamics through diagnostic models that can be used to understand theprocess of cover change and make credible near-term projections. As such, Focus 2
address questions 1, 2, and 3 (Table 2). Focus 2 activities contribute to Focus 1 byfacilitating the coupling of site-specific use dynamics with large-scale regional changes
in land cover, while they prOvide the spatial patterns of these changes to Focus 3,
allowing more aggregated analyses to have an explicit spatial component.

54

A. Improvement of the data and databased estimates for the major land
covers and the changes in these covers
for the last 300 years, with increasing
spatial and temporal resolution forlast 100 and SO years, respectively.
B. Determination of the spatial scale
and pace of changes in the major land
uses and covers, including coverconversion and modification.
C. Empirical identification of the
major driving forces (exogenous
variables) of land-use change as they
relate to the land manager anduse-system for critical land covers.
D. Empirical identification of the
major kinds of land-use/coverchange dynamics operating
throughout the world.
E. Refinement and development of
new suites of geographically explicit
land-use/cover models using both
empirical-based diagnostics andbehavioural-based regional
approaches.
F. Refinement and development of
new suites of prognostic land-use
models capable of incorporating
biophysical and climate impacts.
G. Determination of the sensitivity ofsuch models for use in assessing
future scenarios of land-use/coverdrivers and conditions.

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55

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Focus 3 develops various structures for new and improved behavioural models ofland-use I cover from the regional to global scale. These models will be used to provide
projections of land-usel cover change (Question 3) and, in turn, provide a means forassessing the impacts of environmental changes on land use (Question 4) (Table 2).
Models of the kind sought in Focus 3 must be dynamic and geographically explicit andinvolve the major socio-economic and biophysical driving forces of land-use/coverchange together with biophysical feedbacks to those forces and to global change.

The IGBP studies the physical, chemical, and biological processes that regulate the earthsystem, and the manner in which these are influenced by human activitie,:. Most IGBP
core projects can provide LUCC with an enhanced understanding of the blOp~yslcal
driving forces that influence the potential range of land uses. LUCC can prOVide theother core projects with projections of changes in land cover and kno,:"led.ge base.d on
the processes involved in land-cover change. Besides these overa~chmg mteractlOns,
most cover projects need specific contributions from, and can contribute to, LUCC
research (IGBP 1994).

Such models aim to provide projections of land-usel cover change and associatedbiophysical parameters, including vegetation attributes and resource accumulation anddegradation, for periods of 50-100 years and a spatial resolution of 10 km' to 50 km'.
Thus, the models must also be adaptive in the sense that tastes and values ofsociety(ies) change and are likely to do so over the time periods investigated here.
Finally, Focus 3 will perform model validation and sensitivity analysis. This focus
provides the boundary conditions and temporal dynamics needed for Focus 2 and theexogenous or international influences on the case studies in Focus 1.

GCTE (Global Change and Terrestrial Ecosystems) aims to define the contributions,
responses, and feedbacks of terrestrial ecosystems and agrosystems to I?lobal cha~ge.
This research on biogeochemical cycles, vegetation dynamics, and agricultural yield
response is of direct importance to LUC,? because it defines to a large extent thebiophysical driving forces needed to defme land-use potential. The.L:-;CC resear~. onscalar dynamics should be compatible with GCTE's rese~rch on defml."g these drlvmg
forces across local and regional scales. LUCC could proVide an analYSIS of land use on
the GCTE transects studies, which then could become an important benchmark for
integrated IGBP research.

Integrating Activities

BAHC (Biospheric Aspects of the Hydrological Cycle) aims to understan~ and. model
the biospheric processes that control the hydrological cycle. Land cover IS an Important
determinant of these processes, and BAHC, therefore, can draw heavily on theoutcomes of LUCC research. BAHC has developed a strong focus on biophysicalscaling dynamics on which LUCC should draw. BAHC further develops with DIS a setof advanced databases that LUCC can utilise.

Cross-cutting the three foci are two important activities - information and conceptualissues central to the research objectives of LUCC as whole, but not grounded
specifically within any focus (Fig. 11). The first activity is data and classification related
to land use and cover and is particularly important for Questions 1 and 2 (Table 2).
Other IGBP and HDP projectslprogrammes and other agency activities have been
charged to develop and maintain datasets on land cover, land use, and socio-economic
variables related to both. These efforts, however, will not necessarily generate thesedata in forms useful to LUCC, unless the LUCC requirements are identified andtranslated to those projects and agencies. The data and classification activity does thisby providing a rationale for the kinds of data needed and how they can be combined tocreate the variety of classifications and typologies that will, no doubt, be used inforthcoming LUCC-related work.
The second activity - scalar dynamics - addresses the differences in land-use I cover
dynamics at different spatial, temporal, and hierarchical levels of analysis of operation.
It aims to cull from the knowledge gained in the activities of the three foci, as well asfrom other related efforts, the general lessons about the nature of these dynamics as
they are observed at different scales and levels of analysis, including the identificationof heretofore neglected variables, their influence and distribution. These lessons arecentral for systematic understanding the flow of processes through different scales,
contributing to Questions 2, 3, and 4 (Table 2).

Linkages between LUCC and other Research Projects
LUCC maintains strong linkages with various international research activities andprogrammes (Fig. 2). As a member of the IGBP and HOP, however, particular attention
is given to LUCC's linkages with the other projects and activities within the auspices ofthese two programmes.

56

LOICZ (Land-Ocean Interactions in the Coastal Zone) seeks to understand how changes
in processes in coastal zones affect global change. Coastal land use and cover may beaffected by sea levels and may involve other phenomena such as sea de~ense,. .
construction and groundwater use; and, a large proportion of humans hve wlthm, andtransform, the coastal zones. For these reasons, LUCC needs to work closely with .
LOICZ. It can provide LOICZ with the driving forces of coastal land usel cover and, mturn, receive information about the impacts of sea-level changes on land use.
PAGES (Past Giobal Changes) aims to understand past change in vegetation and sea
levels at high levels of spatial and temporal resolution. Together with ~OICZ: a focus
has been developed on the historic changes of coastal zones. Land use IS cons~dered
and the historic activities of LUCC should link to those in PAGES where pOSSible.
The use of historical data on land use and land cover to calibrate LUCC models andthe use of LUCC models to simulate landscape change should provide insights on
which PAGES can draw.
IGAC (International Global Atmospheric Chemistry) addresses the processes that
determine the chemical composition of the atmosphere. Greenhouse gas f1uxes fromthe biosphere and land use are of importance for such unders:a".ding. IGAC .
developed a comprehensive database on land- use related emiSSIOns, s,:c~ as bwmass
burning and rice paddies. For future projections of greenhouse gas emiSSions .and
fluxes, IGAC is dependent on a firm understanding of land cover .and use, ,:"hich LUCC
should provide. In addition, LUCC complements well the emergmg effort m IGA<? toexamine the interactions between trace gases emitted by metro-agroplexes and theirimpacts on soda-economic activity in those same places.

57

GAlM (Global Analysis, Interpretation, and Modelling), a task force among projects,
involves developing, interpreting, and applying comprehensive prognostic models of
the global biogeochemical system and linking them to the climate system on different
spatial and temporal scales. LUCC should provide GAIM with model capabilities of awide range of land-cover changes under various soda-economic conditions, while
GAIM could assist in defining scalar dynamics appropriate for LUCC.
IGBP-DIS (Data and Information System) develops improvements in the supply andmanagement of data and information. It is important to LUCC in respect to data
harmonisation and standardisation, and could provide a link between data collecting.
organisations and LUCC researchers.
HOP advances research on topics that are critical for understanding both the humanrole in global change and the implications of global change for society (Jacobson andPrice 1991; HOP Work Plan 1994-1995). It has identified six areas of human behaviour
that have particular relevance for global change research. Land-Use and -CoverChange is one of these themes, but all of them are interrelated as each addresses particular aspects of social systems and processes that affect or are affected by changes in thephysical environment. To bulld cumulative understanding of the human dimensionsof global change, each research theme will provide input to the others and receive
output from them. Some of the relevant linkages are presented below.
Research within the context of "Industrial Transformation and Energy Use" addresses
the spatial and temporal changes in the production system in order to evaluate theirimpact on the environment. It studies the different patterns of industrialisation,different regulatory systems, and material and energy flows associated with different
production systems. It will model energy production and consumption, attempt todevelop trajectories of future energy use, and assess the cost and effectiveness ofvarious policies enacted to influence energy consumption. LUCC can provide thisresearch programme with data on the evolution of land-use patterns in relation toindustrialisation and in the context of urban-rural dynamics. Understanding thedemand functions in these dynamics is essential for LUCC models because they affectland managers and their decisions about land use. Energy models provide anothermeans of assessing potential impacts on land management decisions.
L?CC i~ also closely tied to the research programme on "Demographic and Social
DImensIOns of Resource Use." Indeed, part of the goal of this latter focus is tosynthesise the findings of the other research areas to develop models of interaction
between popUlation and resources. LUCC addresses this goal in its emphasis on land
as a fundamental resource and the role of population and institutions on its management. Thus LUCC will provide the data on the associations of land-use/cover changewith different population and institutional dynamics, such as rates of growth andproperty rights. The "Demographic and Social Dimensions" focus links these issues
more broadly to general resource and policy questions, and thus can inform LUCC ofthem as they act as exogenous influence on land management. Because water, unlike
energy and land, is not the focus of a particular research programme within HOP,
"Demographic and Social Dimensions" will pay particular attention to water issues
within these interactions. Moreover, it can provide understanding of distributional
Issues, both through time and across space .. It will develop models to describe
population evolution, including migration, as it relates to exchanges and transactions
such as trade and financial flows.

58

Understanding human perceptions, assessments, knowledge, and attitudes is essential
to explaining why people act in particular ways and to assess whether policy devised tomodify behaviour will be accepted within specific contexts. Research within the theme:'Public ~ttitudes, Perception, Behaviour, and Knowledge" can potentially provide
rnformatlOn to LUCC on, for example, native classifications of land resources,
evolution of tastes, or attitudes and perceptions about policy and regulation of landuse. Diagnostics of land cover and land use will be essential to attitude surveys toassess the relation between attitude and behaviour. LUCC can also provide details
about the validity of the proclaimed and actual actions of land-mangers.
Many of the factors influencing land use and therefore land cover are related to
institutional arrangements determining property systems, land management, and land
reform. Ll~C,? will describe the variety of these within different social systems andanalyse theIr Impact on land use and land cover. The "Institutions" theme will
inform LUCC of the role of international treaties and government regulations on landuse dY','amics and their effects on rules of access and use that will in turn shape the.
dynamIcs of land use and land cover.
To be able to respond and adapt to changes in the land base caused by environmentalc.hange requires understanding of the mechanisms that influence land use through~me a:,d across space .. In the cO.n.text of developing mitigation strategies and designing
mcenllves and constramts to faClhtate appropriate response to rapid change or topreserve the land base for the future, LUCC can provide the research programme on"Environmental Security and Sustainable Development" with diagnostics about
current land use. and cover and its likely change based on improved understanding ofland-use ~yna~~cs. As. such, LUCC provides a basis for identifying a range of security
and sustamabhhty attnbutes about places. In turn, the "Environmental Security andSustainable Development" provides LUCC with an understanding of the broader facetsof the problem as they impinge on land managers. Together, the two themes will help
LUCC to assess the role mitigation strategies in changing land use patterns and willcontribute to the identification of communities at particular risk in the face of change.
The HOP is also developing a DIS (Data and Information System) to improve in the
supply and management of data and information. As with IGBP-DIS it will be
important for LUCC to work with this DIS to identify standard measures and data.
pertinent to LUCC's agenda.
LUCC also contributes to the START (Systems for Analysis, Research and Training;
HOP, IGBP, WCRP) effort. The START regional research centres could provide a basis
for a globally comprehensive network of case studies linked into land-use/coverissues. Such a emphasis has already been taken by SARCS (Southeast Asian Regional
Center for START) in cooperation with members of the CPPC-LUCC, providing a trial
for many of the research themes articulated in this report (see Sections 5-7). In
addition, the IAI (Inter-American Institute) has been in contact with members of the
CPPC-LUCC about a complementary land-use/ cover effort in the Americas.
Those programmes concerned with climate impacts and climate research will benefit
from information on the sensitivity of land use and land cover to climate change and?n the interactions between land cover and the atmosphere. These programmes'
mc1udes the WCRP (World Climate Research Programme), WCIRP (World Climate
Impacts and Response Programme), and the IPCC (Intergovernmental Panel on
Climate Change).
59

:1l'

5. Focus 1: Land-Use Dynamics Comparative Case Study Analysis

The FAO will be both a major source of data for LUCC and an important user of LUCCderived projections as a basis for considering the causes and consequences of future
agricultural and forestry development. IIASA's new initiative on regional modellingof land-use/ cover change in mid- to high-l<ititude Eurasia, which strongly complements the LUCC strategies in this science/research plan, should provide leadershipparticularly for global and regional prognostic models of LUCC.
Finally, LUCC will complement existing global monitoring programmes such as
UNEP's GEMS (Global Environment Monitoring System) and GTOS (Global
Terrestrial Observation System), which is presently in a planning stage.

Introduction
A comparative case-study analysis of the human dimensions of land-cover and -usechange can serve several distinct objectives:•

Link biophysical and human aspects of land cover and use•

Outline a framework for an eventual global catalogue of land-use situations anddynamics•

Link the analysis of human dimensions to global land classification and land-covermodelling efforts•

Take a first step in determining what regions of the world deserve priority infuture empirlcal research on global land-cover and -use change.

Focus 1 has two purposes: (i) to build a firm understanding of the regional dynamics
of land-use/ cover change through the comparative analysis of land-use change, and(ii) model empirically land-use change situations and dynamics at the subnational andnational (local and regional) scales. It addresses the following basic questions:
1. What are the main driving forces and constraints that infiuence human land

managers to maintain or change land use over time?

2. What are the mechanisms and processes by which land managers develop a landuse system, defined in terms of an operation sequence? How are their purposestranslated into action?
3. What are the effects on land cover of the application of a land use over time?
How do these consequences feed back to land uses and their driving forces?

Aims
(i)

To undertake comparative studies of land-use/cover dynamicS using common
protocols and standardised terms and measures of land use and its dynamicS(ii) To use the results of these studies to identify and map situations of landuse/cover dynamics, and to improve understanding of these dynamics, gleaning
generalities from these studies(iii) To build, from this analYSiS, local and regional models of land-use/cover change.

60

61

Activities
The activities of Focus 1 (Fig. 12), as they are linked to Foci 2 and 3, should lead
ultimately to an empirically derived modelling framework that builds on the essenceof comparative empirical analysis: the consideration of micro-scale phenomena (whereland management takes place) against other phenomena of similar kind and scale,within the ambit of the social system as a whole (Ragin 1981). The Focus 1 modelling
framework should interact with Focus 2 empirical thematic assessments and with
Focus 3 global modelling efforts, which emphasise global to national scale andmacroeconomic phenomena. As a modelling effort, Focus 1 should not pretend toexhaust the full range of land-use practices or locales; it should concentrate on areas ofpriority to other IGBP and HDP projects/programmes and to global environmental
change.
Focus 1 activities also include an effort to determine the scales at which importantsocial forces such as politics and policy, cultural practices, different forms of socialorganisation on the land, and so on, are most important to land-use and cover change,
and where they are not important at all, or perhaps important only as rate modifiers.
Focus Activity 1.1. Developing a global sampling and study framework
A rich, diverse body of literature on land-use/ cover change already exists. This wide
range of scholarly knowledge, linked neither to global change per se nor to supranational modelling perspectives, must be brought to bear on Focus 1 case-study efforts.
Proper use of this literature and its various methodological approaches can accelerate
Focus 1 efforts to select research sites from the universe of possibilities. The firstactivity of Focus 1 will be to organise and assess this literature with that purpose inmind. It is clear, however, that sites and study teams must be chosen according to an
explicit set of criteria, including the availability of qualified interdisciplinary researchexperts in both biophysical and social dimensions; fit with the highest priority land-use
modalities identified; geographic location; theoretical significance; and so forth.
This activity must consider judiciously the extensive literature on land-use change,
which is too large and diffuse to review in its entirety. Selection should be guided by
the quantity and quality of relevant work on particular areas and by the centrality of
the areas to the issues addressed in LUCC. The latter consideration requires the identification of land-use/cover change areas and dynamics of greatest interest. From theareas so identified a number should be chosen based on the availability of data andresearchers as well as linkages with studies in Foci 2 and 3. The size of the areas to be
examined will, of course, vary, but would normally be larger than the land unit,
smaller than the nation (with some possible exceptions), and roughly equivalent to theecological notion of landscape (Bailey 1983; Klijn and de Haes 1994). These areas
should also be catalogued according to their land-use/cover situations (or modalities)
and bounded in space. The cataloguing effort should expand on other such typologies(Tiryakian 1968; Weber 1949) by including dynamic and historical elements of change
through evolving sets of drivers and outcomes. A situational catalogue will influence
the level of spatial disaggregation and, hence, the spatial specificity of global LUCC
models. In the end, however, it may be as interesting for its identification of outlying
areas, or the areas in which the situations are not or are only marginally applicable.

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6263

To be comparable, the studies require a common protocol to gUide regional analyses
and retrospectively organise existing literature Such a protocol should identify
aggregate data relevant to the HDP-DIS and IGBP-DIS efforts, methods of analysis
appropriate to the principal hypothesised social and biophysical driving forces, andagreement on the terms used to classify land use and the modalities of use/ cover
dynamics. This protocol is intended not to restrict the research, but to set a minimum
standard for comparability and approach. Complementing the protocol should be a setof methods and field strategies that will enable natural and social science analysts toaddress linked questions: methods and strategies that should be periodically evaluated.
Focus Activity 1.2. Identification, description, and qualitative modelling of the role ofkey driving forces of land-use maintenance and changeThis activity, anchored in site studies, should be seen as an empirically-driven landuse modelling effort informing empirical assessments of land-cover change (Focus 2)
and making global models more robust and regionally sensitive (Focus 3). It aims to
improve understanding of biophysical and human processes and activities thatmaintain or change land use. Where human driving forces are weak, land cover isdetermined by biophysical energy fiows and the state characteristics that these forces
influence. Biophysical variables generally constrain land use at most of the time scales
over which land use changes, as recognised in various models of land-use potential,
such as crop suitability models and the FAO's agro-ecological zones (Rosenzweig 1993;
Turner and Benjamin 1994). These constraints can change over time, sometimes quite
rapidly, and events that over a long period are quite normal can come as surprises
because of their episodic nature. The biophysical world is also a source of driving forcesthat at times can change the path and state of land use. Natural dynamic cycles ofdisturbance both influence human use and determine the ways in which humandisturbance will affect the system (UbI et al. 1990). Examples include fire cycles, pest
outbreaks, the El Nino Southern Oscillation, and ecological succession (Holling 1992).
Phenology and successional pathways on natural and anthropogenically disturbed landalso determine the consequence of human intervention and constrain future land-use
possibilities. Multiple equilibria in land cover are possible, even in the long term,
meaning that the timing and character of intervention determine successional
outcomes (Holling 1973; Foster 1992).
The salience of socio-economic and political driving forces determines the paths ofland-use change, the propensities for certain operation sequences, the time scale overwhich systems are in apparent equilibrium, and the susceptibility of use/ coversituations to external or internal human-induced change. The range of possible
drivers, the prevalence of certain kinds of drivers over others, and the importance of
outlying cases must be identified and linked across scales. In addition, landesquecapital (long-term inputs for land improvement, such as terraces) and infrastructure(e.g., transportation networks) should be considered. On scales ranging from fields tofarms and sometimes up to communities, their effects resemble those of biophysicaldriving forces, in that they alter the biophysical constraints on land use. On scales
from communities through regions and up to nations, they are more closely related tosocial driving forces. The development of landesque capital has two kinds of effects onland cover: (i) direct effects through the physical manipulation of the environment,
including habitat fragmentation and disruption of hydrology by road building,reclamation of wetlands, and reservoir clearing and filling; and (ii) indirect effects oncover through effects on other land uses, giving rise to decreased factor costs in
64

agriculture, increased market access, dampening of oscillations in water supply,
catalysis of immigration initially for construction and later for settlement, and soforth. TIle sum of indirect effects is often much larger than the direct effects on cover.
Finally, the driving forces of change must be considered over the course of a system's
development, permitting analYSis of historical change as an exogenous variable.
It may be, for example, that one of the greatest period shifts in 20th century history, theGreat Crash and onset of the Great Depression, did not produce a commensurate shift
in land-use patterns at the local scale in many cases (e.g., subsistence maize cultivationin the Andes), but did produce such change in others (e.g., cotton production in thesouthern United States). The impacts on existing systems of shocks of this kind cannot
be adequately understood without tracing the historical context in which they occur.
Such observations on the differential impact of macrohistorical change reveal thesusceptibility of local land-use systems to exogenous change and suggest some limits torational economic models imputing homogeneous impacts. Similarly, adding ahistorical dimension avoids the problems of trapping the modelling exercise within a
specific historical conjuncture or mode of production. Failure to do so has led land-use
analysts to conclude, for example, that swidden disappears in the presence of permanent agriculture or agricultural modernisation, when the literature demonstrates its
persistence as a land-use type across broad historical time (Dove 1988; Richards 1985).
Focus Activity 1.3. Assessing the dynamics of change and stability in systems ofland use
As noted in IGBP Report No. 24/HDP Report No. 5, land-use/ cover dynamics involvean intricate set of relationships among the land user, the larger socio-economic setting,the land in question, and biophysical feedbacks to the use employed. Local andregional models must be grounded in a firm understanding of these relationships,
involving several attributes.
1i.'

(i)

Lands are managed differently by different classes of human agents. For example,
the simplest categories of distinction between agricultural producers may be
between those who are consumption-oriented (for subsistence, or to trade for themeans of subsistence), commodity-oriented (for profit), or somewhere in between(Kates, Hyden and Turner 1993; also Brush and Turner 1987). Agents also differ
in such attributes as temporal and spatial scale of production, intenSity, integration into non-local market processes, adaptations and attitudes toward risk,
demographic and tenurial characteristics (Popkin 1979).

(ii) The second attribute is the land-use practices that influence land cover. The
proximate anthropogenic determinants of land cover can be usefully portrayedusing the concept of an operation sequence (Stomph and Fresco 1991), defined for
agricultural use but expandable to include other human uses (see part 3 above).
Because an operation sequence occurs over time, and because its effects on land
cover depend on temporal interactions between human and natural driving
forces, the description of its temporal characteristics is vital. Similarly, the spatial
characteristics of an operation sequence influence its impact on the landscape.
Ideally, the operation sequences should be georeferenced. The technology mustbe specified in a way that includes factors of production, capital equipment, andtechnique. Finally, the operation sequences must be evaluated in terms of theirstability and sensitivity to change.

65

(iii) Third are the key sets of driving variables and endogenous dynamics (by class ofhuman agent [iD that govern the choices of land use. The driving variables orforces will vary by situation, of course, but it is important that a wide range be.
explored and/or the data collected in a way that their exploration is feasible (e.g.
Ostrom 1990). These variables should be qualitatively or topologically modelled
to summarise relationships in the form of pattern models (Wilber and Harrison1978), circuit diagrams (Odum 1983), or fuzzy cognitive maps (Kosko 1986). Suchmodels serve the purposes of stimulating discussion, revealing hidden issues andtheoretical biases, and generalising the findings and intuitions of case-based
researchers. If made spatially explicit, these models can be extended to serve themodelling functions of Foci 2 and 3.
Focus Activity 1.4. Analysing land-cover consequences
The LUCC project/programme will aid other core projects and research efforts by
specifying the land-cover consequences resulting from land use and its driving forces.
The relation of land-cover change to other regional and global environmental changes
is investigated in LUCC only inasmuch as it feeds back on land management systems.
Land-use effects on land-cover change and on ecosystem structure and function onscales from the patch to region are also investigated in GCTE, and these tasks must,
therefore, be collaborative.
Land cover is the result of the interaction of human land-use operations with naturalbiophysical conditions, including the past history of the site itself. The same operation
on similar sites may have different results for cover if such factors as seasonal andlonger-term fluctuations in rainfall amount and intensity, seedbank and seed rain of
successional species, pest cycles, soil condition, and context within different operation
sequences differ between sites. The challenge for comparative land-use analysis is todevelop generalisations about land-cover consequences not only for individual
operations but for their application in sequences, including the role of natural cycles
and landscape patterns.
Land-cover change has immediate environmental consequences (e.g., soil nutrientchange, habitat fragmentation) that feed back on the land use and on the biophysicaland human driving forces. These feedbacks should be examined as they amplify orattenuate land-use dynamiCS. Actions in the biophysical realm have both intended
and unintended consequences for land cover, which generally correspond to positive
and negative feedback mechanisms, respectively. An example of a rapid positive
feedback is successful crop production, a cover consequence clearly intended by theland manager. Delayed feedbacks also exist, such as soil nutrient exhaustion or
improved soil moisture control through incremental irrigation development.
Feedbacks can also affect the larger social system, particularly those that engenderpolicy reformulation and reaction, such as forest degradation leading to logging
controls leading to local labour adjustments.
It is expected that remotely-sensed data on land cover will be produced and distributed

much faster than socio-economic data over the next decade or more. Incentives will
exist, therefore, to relate ground-based data to characteristic signatures and changes inremotely-sensed data, with an eye to working backwards from land-cover information
to reconstruct likely land-use situations. Such an effort will necessarily involve careful
comparison over time with paired remote-ground information from biophysically66

simila.r control sites. As relations between process and pattern become tentatively
estabhshed, they may allow LUCC models developed in both Foci 1 and 2 to beextended to areas where socio-economic data are unavailable, sparse, or suspect.

Focus Activity 1.5. Theoretical work: Model building and prediction
The activities above will provide detailed and comparative understanding on which toconstruct 10c~1 to re!?o~allan?-use/cover change models unencumbered by the biases
and assumptions bwlt mto eXlstmg larger-scale models. This case-study-driven
approach to modelling can enrich the global models, by making them more robust andregionally sensitive, if a series of important steps can be taken.
(I)

The sampling effort outlined in Activity 1.3 must be extended and elaborated into
~ true typology of regional situations, with the categories corresponding not to
Ideal but to real or nominal types (Diesing 1971) of cases with common
characteristics and dynamics. Such a typology can be used as a gUide in further
consideration of cases, or it can be used as a classification system at the regional
level to feed into larger-scale modelling efforts.

(il)

The LUCC dynamics identified by types through case studies must be aggregated
and/or extrapolated, either case raiSing a number of cross-scale linkage issues(also refe~re? to as the micro-macro issue; see Section 9). For LUCC modelling ina mechanlStlc context, at least three types of aggregation methods should be
investigated (Rastetter et al. 1992), using: a statistical expectation operator based on
fme-scale data and model behaviour to derive larger-scale functional forms (withthe attend~nt risk of analytic intractability); a spatial partitioning and simple
Imear scahng of small-scale model relations (with the cost of computational
complexity); and, large-scale calibration to relate aggregate data (with the risk ofspurious correlation: Przeworski and Teune 1970).

(Hi) Although methodologically distinct, Foci 1, 2, and 3 should be integrated in

multiple ways through model-building, data sharing, and verification. As
mod~ls are g~neralised and scaled up to a subnational (regional) level, they will
proVIde a baSIS for the large-scale macro-modelling exercise. In some areas of theworld and for some processes that display loose vertical coupling, they may
provide a justification and verification for simpler, less mechanistic models based
mostly on large-scale socio-economic parameters. In more problematic areas of
the world, and for processes that display stronger vertical coupling across scales,
they will pro:,ide insight into the level of detail needed for successful predictionand explanation. In all cases they will establish in mechanistic terms the~onfidence limits and conceptual boundaries for valid models. In many
Instances, cases WIll provide estimates of sodo-economic parameters andland-cover sensitivities not available on a global extent. In addition, work
establiShing a typology of situations and their dynamiCS will provide a basis forapfrop~iate differential application of these parameters across the globe for
calIbration purposes. Leemans and Zuidema (1995) have noted the problem oflinking basically dimensionless socio-economic data with two-dimensional
biophysical data. A !?eneral typology of situations will help somewhat by reducing
the scale and mcreasmg the number of socio-economic regions.

67

(iv) Focus 1 models will be used to probe the stability regimes and comparative

dynamics for land-use/cover situations relative to parameter shifts and over thecourse of system evolution. It will be essential to investigate the necessary .
conditions under which land use (and land cover) may be expected to vary
continuously and unambiguously, an~ .what sort of pred.iction i~ possible overthese periods. Where necessary condItions. d? not prevall, n;ultiple steady states
may be identified, and scenario-based predIction may be ~easlble .. Such . .
investigation at the scale of land management may provIde confldence hmlts forpredictions on a larger scale.

6. Focus 2: Land-Cover DynamicsDirect Observation and Diagnostic Models

Introduction
Although it is an important aspect of global change, our understanding of land-coverchange is inadequate for two reasons: (i) we lack accurate measurements of its rate,
geographic extent, and spatial pattern, and (ii) we have a very poor capability ofmodelling from empirical observations. This Focus develops an interdisciplinary
approach for analysing land-cover change by coupling empirical observations anddiagnostic models.
Direct observations of land-cover change can be made using remote sensing. It is apromising tool for objectively making these measurements at different spatial andtemporal scales, from large-scale assessments of regional trends to local-scale analysis
of complex dynamics. Additional information can be obtained from tabular census
documents. By directly measuring land-cover change, it is possible to explicitly
quantify its rate and spatial pattern. This information can be used for specific analysisof land-cover fragmentation as well as for analysis of spatial trends in, and geometricpatterns of, land-cover change. Direct observations provide a quantitative assessmentof rates of change, which can be used as forcing functions for a variety of biophysicaland socio/demographic/economic models. These observations of spatial trends andrates can be used to develop empirical diagnostic models and short-term prognostic
models (Lambin 1994).
The synthesis of observations through modelling is central to this Focus. The
approach would be to use a combination of region-wide observations, site-specificobservations, and case studies to develop models which, although they do not provide
functional or process level drivers, can provide credible short-term predictions as well
as spatially disaggregated results. Moreover, the results of such observations andmodels would lend insights into driving variables by highlighting important spatial
and temporal occurrences.
Modelling would thus provide a diagnostic capacity of the overall programme todefine what is happening in terms of a set of selected important land covers. The
importance of this diagnostic modelling for current global change research, such as theimbalance in the global carbon budget, cannot be underestimated. To the extent thatsuch models also provide credible near-term (5 to 10 years) prognostic models forunderstanding future trends in land-cover change, and hence, climate forcing, they
provide a basis for integrating land-cover change transients into terrestrial ecosystemmodels.

68

69

The activities in this Focus would emphasise the following questions:• What are the rates of land-cover change, and how will they progress?
• Where is land-cover change occurring now, and where will it occur in the future?
• Which spatial and environmental attributes contribute the most to an explanationof land-cover change?
Land-cover change spans many scales of analysis. In the case of deforestation in theBrazilian Amazon region, it has been shown that regional trends are influenced bylarge-scale external forces but mediated by local-scale conditions (Skole et al. 1994).
A multi-level, interdisciplinary approach is therefore necessary. Focus 2 starts withdirect measurements of the rate, location, spatial pattern, and temporal characteristics
of land-cover change for large regions. At a second level of analysis, site-specificobservations could be carried out using multi-temporal, high resolution satellite data
to gain insight into local-scale dynamics of land-cover changes. Regional analyses
provide information on general trends in land-cover change, while site studies nested
in the regional analysis provide insights into fine spatial and temporal dynamics ofland-cover t~ansition sequences.
Spatially-explicit observations and empirical models developed in this Focus readily
couple to the analyses and models of Focus 1 and Focus 3 (Fig. 13). In one sense, theanalyses conducted in this Focus centre on land-cover changes, while the emphasis of
Focus 1 is on the relationship between land cover and land use. For instance, sitespecific studies in this Focus provide a detailed documentation of patterns, while thecase study emphasis of Focus 1 emphasises the underlying causes or processes that leadto the observed patterns. The site studies couple to activities in Focus 1, incorporating
survey research and data from census documents to define the parameters that describe
the local land-use strategies of the land manager, and how changes in the local
environment are brought about by changes in the physical environment that influence
the land manager. The work included in this Focus couples to Focus 3 by enhancing
the aggregate results with spatial information and detail. One advantage of thislinking between direct observations of the land-cover changes with the modelling inFocus 3 is that an explicit treatment of scale and aggregation problems could take place.
This Focus also provides an explicit validation of results of more aggregate prognostic
models.
The output from Focus 2 provides: (a) diagnostic model results of land-cover changes
occurring over the last 20 years and next 10 years; (b) a basis for validation of integrated
prognostic models against explicit observations; and (c) the distribution of land-coverchange by various cover types. The latter output is significant. Macro-models
developed in Focus 3 will be able to predict the increase in crop land area defined
through a specified demand function and the availability of existing crop land.
Should the model need to bring new land into production, these models will need todefine how to partition it between: (a) complete conversion of native vegetation;(b) modification of native vegetation; and (c) re-clearing of successional or fallow
vegetation.

Aims
(i)

To provide, through direct observations and data, regional and continental
patterns of land-cover change needed by the global change research community.

(ii)

To provide a basis for analysing the time-varying spatial dynamics of land-covertransitions.

(iii) To develop an empirical and data-rich framework for diagnostic models of

current situations and short-term predictions through models based on direct
observations.

(iv) To establish a foundation of observations and measurements for spatiallydisaggregating results from macroeconomic analyses.

Activities
The approach to Focus 2 is shown in Fig. 13. Large-scale observations with hightemporal resolution and low spatial resolution data (e.g., AVHRR 1 km data) can
provide information on land-cover types and some limited information on land-coverchange (e.g., biomass burning).
Regional observations using high spatial and low temporal resolution satellite remotesensing provide data on land-cover change, its spatial geometry, and the temporalsequencing of land-cover change.
Region-wide patterns of land-cover change are the result of many local activities.
For example, net deforestation is the sum of several land-cover transitions: primary
forest conversion, abandonment of agricultural land to secondary succession, andre-clearing of successional vegetation. These fine spatial and temporal scale dynamiCS
are important, since the pattern and timing of clearing and abandonment affectbiogeochemistry and other physical processes. The implications for carbon storage areimportant, since regrowing vegetation accumulates carbon previously lost to theatmosphere from clearing.
In some land-use systems, especially in the tropics, there is an important relationshipbetween land in active agricul ture and secondary growth. The mode of production ispredicated upon maintaining both classes of land use. Local ecological conditions,
methods of agro-ecosystem resource management, and local-scale decisionmaking are,therefore, important variables in the land-cover conversion process.
It will be necessary to couple large area measurements sampled synoptically every

decade or half- decade with a sample-based distribution of site-specific measurements
made annually. These site measurements could provide detailed information on theinterannual cover-change dynamics. Case studies would become an importantcomponent of the work, and links between Focus 1 and this Focus would occur at thisnexus.
In addition to regional observations from satellite data, non-satellite information willbe v~ry important Data on land uses, particularly agricultural areas, can frequently beobtamed from natlonal censuses. Sociodemographic information can be compiled
from censuses and other inventories, or through field activities.

70

71

Focus Activity 2.1. Determining important land-cover changes and regions ofconsideration

I

The analysis of land-cover change could be a daunting and monumental programnle,
particularly in terms of the observations required to document land-cover changes
exhaustively. Therefore, the first Activity of this Focus is to develop a strategic andconceptual framework for analysis of important regions and time periods. Nominally,
the period of the last 20 years is important when geographically distributed atmospheric records make integrated global analyses possible. There is, however, a need todevelop longer-term historical analyses as well. Regionally, much emphasis is now
being placed on the tropical forests, but other areas may become important in the
future.

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Focus Activity 2.2. Direct measurement of regional and global land cover and land use
There are two major uses for global land-cover stratification. First, such stratification
will be used as a framework for geographically mapping in situ measurements todefine biophysical attributes for land-use models; and second, as an input to global
biosphere modek A rationale for global land-cover stratification for global biospheremodels is provided by the IGBP (1992), which also supports the LUCC models. This
Focus Activity has direct links to existing efforts to assemble the requisite datasets being
coordinated through IGBP-mS, and should be conducted jointly by LUCC and ms.
A global land-cover and land-use classification should be emphasised (see Section 8).
The classes would be relevant to the needs of the core projects/research programmes
and the needs of the modelling proposed in this Focus and Focus 3. The classification
could be generated using satellite data and through the integration of existing maps or
documents. The integration of non-satellite information would be especially necessary
for the development of land-use (as opposed to land-cover) datasets. The emphasis
would be placed on developing datasets which provide geographically referenced
information on inputs (such as fertilisers), management practices, tenure and otherfactors related to land use.
There is a need for agreement on the land-cover and land-use classification schemes.
Such an agreement is currently being sought by the IGBP-DIS Global Land CoverWorking Group. The proposed programme would pursue close involvement withthis international activity, and would encourage further development of land-use, as
well as land-cover, classification schemes.
The research and development activities needed for this component are primarily
methodological. The focus should be on refining the appropriate methodology for
multHemporal, multi-spectral, and multi-year analysis to generate the classificationneeded for the programme. The appropriate timing needs to be determined for thenecessary repeated classification using coarse resolution data. Similarly, tools need to
be developed and applied for using coarse resolution data to flag potential areas ofchange detection. As part of the mid-term development agenda, multi-resolution
tools must also be developed for land-cover mapping. In the longer term, procedures
need to be established for directly parameterising land-cover characteristics such as
biomass and vegetation structure, and to advance them from research demonstration
to operational prototyping.
72

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73

Focus Activity 2.3. Direct observations of land-cover change dynamics
In the last twenty years land-cover change, particularly deforest~tion in the tropics, hasbeen accelerating as a result of population pressure and economIC development. It has
been consistently singled out as a key element of ~any areas of gl.obal ~hange research,and is also important to various international policy issues. Yet, m spIte of thegrowing need for precise estimates of rates of land-cover chanlSe to support bo:hinternational policy and basic scientific research, comprehensIve and systematic
information is not available on a global or regional basis. The latest IPCC report, for.
example, considers the rate of tropical defor~station to be .one. of the key ~nknowns mglobal climate change assessment. Any lasting and effe~1Ve Implementation of a
global emission inventory to support the IPC~ proce~s ,:,,'ll reqUIre a new concerted
effort to measure and map tropical deforestatIOn. It IS likely that othe: su~ land-coverchanges will soon be identified as important, for instance the loss of SIberian forest,
which may increase in the future.
The concern over land-cover change arises because of its impact on the global
environment and its potential influence on climate change. In.deed, some experts
believe the direct effects of deforestation or cropland degradation on the e:,vlronmentand human habitability will be even more signific~nt than climate chang~ Itself. As
noted, land-cover change has historically resulted m as much atmosphen~ carbon
dioxide as fossil fuel burning. If current trends in land;cover change contm~e, asmuch carbon dioxide and other trace gases will be put mto the atmosphere m the next
75 years as have been put into the atmosphere since 1700.

Two elements are important in this Activity. The first is the development of regional
assessments through direct observations, preferably with satellite remote sensing, butusing any other suitable means such as aerial photography, census-based mapping, andother cartographic sources. High spatial resolution satellite remote sensing provides a
uniform approach to measuring and mapping land-cover change over large areas at
fine spatial resolution (lOO m), tracking land-cover conversions (and some modifications) at a sub-national level with a high degree of accuracy. This also emphasises
rates of secondary succession and the turnover of converted land to regrowth
vegetation. This dynamic has important implications for terrestrial ecosystem models
as a potentially important carbon sink, as well as forest fragmentation patterns. The
latter insight would be useful for extending what we now know concerning the overall
impact of land-cover change in forests, and for enhancing with quantitative information the discussion of biodiversity.
The second element develops studies in specific locations or countries, providing thebasis for detailed analyses of the large-area analyses provided by the first programme
activity. These site-specific studies serve multiple functions. At one level, they
provide an ideal basis for developing field validation and accuracy assessments for thelarge-area analyses. At another level, they provide the basis for detailed temporal
analysis of the dynamics of land-cover change, emphasising the analysis of land-covertransition sequences and the issue of land uSe and the dynamics of secondary growth
turnover.
Focus Activity 2.4. Analysing the spatial relations of land-cover change

It is well known that land-cover change is not a unidirectional process (e.g., forests

being converted to agriculture). In many parts of the world, abandonment tosecondary growth is a significant type of land-cover change. In the Amazon, forinstance, this secondary growth amounts to as much as 30% of the deforested land.
This important dynamic must be captured in analyses of the land-co~e.r change pr<:cesssince it determines the correct calculation of net emissions. Determmmg the locationand timing of secondary growth is not a simple problem. The mere. existenc~ of a !argesecondary growth pool is not itself an indication of a large carbon smk; consIderatIOn
must be given to the dynamicS associated with this pool.
Recent scientific findings suggest that land-cover change can influence climate changeby altering sensible and latent heat flux, planetary albedo, and surface roughness at theplanetary boundary layer. More local effects include an increase in soil erosion, an .
increase in the fraction of precipitation as surface run-off, and an eventual local declme
in precipitation. Perhaps the greatest irreversible chan!Se associated with ~and-coverchange is the loss of biodiversity from habitat destructIOn and fragmentation. Someestimates suggest that at current global rates it could result in the lo.ss of .up t<: one .halfof the world stock of genes, which would dramatically reduce the blOloglcal d,vers,ty ofplant and animal species and severely limit the future of genetic stocks forbiotechnology development.
At a national level, numerous reports point to the critical need for reliable land-coverchange analyses to support national programmes. For instance, accurate and up-todate assessments of forest area and rates of depletion are fundamental to the development of improved national forest management strategies. Moreover, issues such as
soil fertility and erosion, water yield, water pollution, and land-use planning aredirectly linked to land-cover management issues.

74

New tools of geographic information systems and computer analysis have made it
possible to develop quantitative analyses of spatial relationships associated with landcover change. An important need is analysis of the geometry of land-cover conversion
and its associated effect on forest fragmentation. Current approaches to analysiS ofeffects on species composition relate the area of cover converted to species-area curves
obtained from empirical data. There is, indeed, a paucity of data on rates of land-coverchange, and it is the intention that Activity 2.2 will address this critical analyticalrequirement. It is becoming clear, however, that the effect on habitat fragmentation is
also related to the geometry of the disturbance (as well as the type of cover which
replaces the changed cover), indicating that the spatial pattern of land-cover change
and the fragmentation of the landscape is the crucial measurement to be made.
The fragmentation of a landscape is a land-use question; the use to which a landscapeis subjected results in different patterns and geometries of land cover. For instance,
small patches of cleared land are created by small farmers in tropical forests, while large
rectilinear patches are created by largeholder cattle ranchers. Different land use
influences pattern and geometry, and different patterns and geometries have different
effects on the environment. Detailed examination of sites across an organised suite ofsituations is an important activity to be linked with Focus 1. Effort must be made tocompile detailed assessments of this kind if the community is to begin to understandthe effects of land-cover change on ecosystem structure and function, and couple thisunderstanding with analyses of the indirect effects of climate change.
Spatial analYSis of land-cover changes, as associated with various physical, social,demographic, and economic factors (e.g., distance to roads, soil type, population
density, population structure) could elucidate fundamental issues in the land-cover75

research. For instance, there is a view that population growth is directly related toland-cover change, yet there have been very few direct empirical analyses across a
range of scales which explicitly test this hypothesis.
Focus Activity 2.5. Observing the proximate causes of land-cover change
The human proximate causes of land-cover change are the immediate landmanagement strategies employed that convert cover from one type to another ormodify an existing cover type. If it were possible to measure quantitatively theproximate causes - their magnitude, frequency, and geographic distribution - better
understanding of the (non-linear) links between human activities and land-coverchange consequences could be developed. A large number of proximate causes exist,
and identifying the most critical for monitoring and study requires a systematic
assessment as proposed in Activity 2.4. Since biomass burning is one of these, we use it
to illustrate.
On a global scale, biomass burning is one of the more important proximate causesof land-cover change. It is a sources of carbon dioxide in humid tropical forests(e.g., Skole et al. 1994). In savanna systems it is also an important source of trace gases
and particulates (Crutzen and Andreae 1990). It should be noted, though, that theannual regrowth of savanna systems makes savanna burning less important as asource of carbon dioxide. In the boreal zone, the stochasticity of fires is an importantconsideration. Biomass burning and non-point source emissions are poorly
documented at a national scale, and accurate information is needed for nationalemission inventories.
The process of burning is an important step in the conversion of natural systems toagriculture, removing unwanted herbaceous cover and releasing nutrients. to improvesoil fertility. In the tropics, there are two distinct types of anthropogenic biomassburning. The first occurs when natural ecosystems are initially cleared. This burning
is often associated with deforestation, but also occurs in savanna and grassland systems
opened for the first time. The second is the repeated burning of existing sa vannas or
pastures on a short rotation as a form of land management to maintain forage
productivity.
Biomass burning in temperate and boreal ecosystems has not been extensively studied,but could be important. There are two general issues. The first is gaining a better
quantitative understanding of the anthropogenic fires, or fire suppression, as a form ofland-cover change in mature ecosystems. The second is determining how the
temporal frequency of natural fires may change over time, and in turn influence theglobal budget calculations during the time period of observations (i.e., the period forwhich atmospheric records exist). There are very few data on the timing anddistribution of fires worldwide (v. Pyne 1991). This impedes progress in global change
research as well as international policy. There is, as yet, no operational mechanism forthe monitoring of fires, which requires daily global observations.
No study has yet attempted to define the relatively fine scale (less than 20 km) spatial
and temporal (daily) distribution of biomass burning over time. There are a number ofadvantages to developing a geographically referenced analysis of terrestrial carbon
fluxes in the tropics. For instance, the wide range in estimated current net flux ofcarbon results, in part, from uncertainties concerning the kind of vegetation converted

76

to human uses and the rate of tropical deforestation. Since current analyses have notbeen able to geographically co-register maps of land cover with maps of land-coverconversion activities, such uncertainty might be resolved, or precisely defined, bymaking geographically detailed analyses (Emanuel, Shugart and Stevenson 1985;
Houghton et al. 1985; Emanuel et al. 1984). Among other things, this would permit thelinking of flux estimates to tropospheric chemistry models, atmospheric circulation
models, and direct observations.
Focus Activity 2.6. Developing empirical diagnostic models
Direct measurements alone will not provide enough understanding to analyse thedriving forces of land-cover change. Thus, linking observations at a range of spatial
and temporal scales to empirical models provides a comprehensive approach tounderstanding land-cover change and at the same time provides important inputs topolicy. Assessment of the magnitude and ecological implications of land-cover change
is most relevant and useful when it is accompanied by modelling the linkages between
sodo-economic configurations and the processes of changes.
The primary utility of models is to provide a systematic approach to understanding a
research problem. An important aspect of the work described here is the link between
direct observations, case studies, and models in an effort to test or identify dominantfeatures of land-cover change. Development of diagnostic models can lead to an
improved understanding of the current and recent situation and at the same time
provide credible, geographically-referenced predictions. The length of time overwhich a prediction is valid is a function of the persistence of the observed phenomena.
There is evidence to suggest that much, if not most, land-cover change is spatially andtemporally persistent over 10 to 15 year intervals. It should be noted, however, thatcertain events can alter trends significantly and rapidly. Changes in political,
institutional, and economic conditions can cause rapid changes in the rate or directionof land-cover change. Therefore, an effort to understand the primary kinds of influences which cause land-cover change trends to diverge rapidly is also an important.
component of this programme.
It is possible to develop models with considerable spatial resolution in the scaledomain of 1:250,000 with horizontal resolution of less than 1 km. For an in-depth
perspective see Lambin (1994). Markov chain models provide one approach toempirical models of the land-cover conversion process. The central mechanism of a
Markov chain is a probability function which refers to the likelihood of transition
from one cover to another cover. The probability function can be static over time(assumes stationarity) or can be adjusted an specific intervals to account for changes inthe stationarity of the processes controlling the transition sequences. The probability
function and transition sequences can be derived from direct observations using
satellite data. Another appropriate model framework is the suite of logistic function~odels. These models have been used in various case studies to account for changes
m the rate of land-cover conversion under constraints. It is conceivable that these twomodels can be combined and adapted for the spatial diffusion process.
Another class of empirical models includes the regression models, which utilise asystem of observations in conjunction with ancillary variables, such as socio-economic
data, to identify explicitly the causes of land-use change. These types of models attempt
to relate rates of cover-conversion to data expressing the various hypothesised driving
77{I7. Focus 3: Regional and Global Models Framework for Integrative Assessments

forces or proximate causes of deforestation, although they could be applied tomodification as well. Regression analyses can be conducted in two ways: by crosssectional analysis (i.e., at one point in time across a large number of specific locations),
or by panel analysis (by relating change in cover during an interval of time to changes
in other variables during the same interval across a large number of specific locations).
Because of requirements for relating data at specific locations and times, there is astrong requirement for direct observations with detailed spatial resolution.

Introduction
Spatial statistical models constitute a third class of empirical models. These models
have been developed in recent years as a response to the availability of remote sensing,geographic information systems, and multivariate-multitemporal mathematical.
models. This approach consists of analysing land-cover conversion in relation togeographically referenced data on natural and cultural landscape variables.
In essence, these classes of models form a constellation of approaches which, whentaken together, can be used to analyse when (Markov and logistic), why (regression)
and where (spatial statistical) land-cover conversion (or modification) processes
operate. The suite of empirical models can serve as a foundation upon whichmechanistic and systems dynamics models can be built, the essential feature being
the use of direct observations of spatial phenomena.
The development of spatially explicit data and empirical models of land-cover change
will benefit spatially aggregated macroeconomic models by providing a means for
spatial disaggregation of results at finer spatial scales relevant for watershed and basin
scale biogeophysical models. For instance, macroeconomic analyses produce estimatesof agricultural land over time as a function of various national and international
factors. It is also important to know, however, how much new arable land will bederived from various ecosystem types and where in a watershed, basin, or ecotone theconversion will take place. Moreover, it is also important to know if new land will
come into production through the conversion of native forest, fallow forest, or
through degradation (but not outright conversion) of forest.
Empirical diagnostic models differ somewhat from the mechanistic prognostic models
described below. Although somewhat restricted in their ability to explain theunderlying processes which control the conversion process, they are well grounded inobservational data and their representation of actual conditions, including conditions
relating to the measurements made, such as spatial and temporal dynamiCS. Thus,
while the models described in the next section (Regional and Global Models Framework for Integrative Assessments) provide a basis for prognostic analysis of
future trends for purposes of determining policy responses to current trends andconditions, the modelling approach framed here provides a basis for detailed
description and analysis of current situations. The two approaches are obviously
complementary.

78

Developing the basis for a new generation of LUCC models is a major task requiring
substantial work in both database preparation and methodological innovation (Fig. 14).
There are, however, near-term needs for more precise land-use/cover change
projections arising from the intergovernmental Panel on Climate Change (IPCC), theFramework Convention on Climate Change (UNFCCC), and other international
bodies. Focus 3, therefore, should follow a two-track approach: a short-term or "fast"
track and a longer-term" development" track. The fast-track approach (Focus Activity
3.1) should review and extend existing regional- to global-scale agricultural, grassland,
and forestry models to give more reliable land-use/cover change projections over the
short term (2-3 years); the development approach (Focus Activities 32-3.7) should seek
to create a new model structure over a longer term that is capable of a fuller
representation of land-use / cover change and its main driving forces. Both of theseapproaches need to (i) elaborate a methodologically rigorous yet flexible structure forthe models capable of including the understanding of driving forces and their LUCC
impacts derived from the socio-economic situation analysis of Focus 1 and the spatial
analyses of Focus 2, and (ii) extend the structure of current models to obtain ageographically more detailed and sectorally more complete representation of the fullrange of land uses, of national economies, and of rural-urban linkages.
Focus 3 should develop an integrated model system capable of representing andprojecting the major driving forces highlighted in this report and elsewhere by the
IGBP /HDP (Turner 1994; Turner, Moss and Skole 1993). Different opinions exist on therobustness of long-term projections of various driving forces; models, then, must be
constructed so as to be sensitive to the range in those projections. Development of
databases and modelling techniques for the more complete and interrelated
representation of crop, livestock, forest, and non-agricultural activities must be
undertaken. The science/research plan seeks to develop approaches that advance thestate of that modelling "horizontally" between sectors and "vertically" througheconomic and physical levels:

Aims
(i)

Develop both an integrating framework and a range of dynamic and geographically explicit regional and global models capable of simulating the majorsocio-economic and biophysical driving forces of land-use and land-cover change,
including major feedbacks from land-use and land-cover change to those forces
and to global change. The models should be able to handle interactions at several
spatial and temporal scales.

(ii)

Provide robust projections of land-use/ cover change and associated biophysicalparameters, including vegetation attributes and resource accumulation and79degradation, for periods of 50-100 years and a spatial resolution of approximately
10 by 10 km to SO by SO km. The appropriate scale will be a matter of earlyconsideration in the project/programme.

Structure of Research Focus 3(iii) Improve understanding of (a) the local, regional, and global dynamics andconsequences of the relationships among the main driving forces and land-use
and land-cover change; and (h) the sensitivity of land-use and land-cover change
to exogenous variables (e.g., technological change, demographic and economic
development, consumer preferences, land-use related policies, and environmental conditions).

Activity 3.1
Refine existing models

Provisional
projections

Activities
The activities of Focus 3 are designed to interact with those of Focus 1 and Focus 2,
and take advantage in the short run of the experience and investment accumulated
to date in global-scale analyses of agriculture and the forestry sector. Ultimately,
Focus 3 should create a new framework for integrating regional and global models
representing biophysical and human drivers to project land use and cover in ageographically explicit way.
Focus Activity 3.1. Extending existing regional and global models projecting land use
and land cover
A number of the existing global agricultural and vegetation models deal in some detailwith crop-related land-use/cover change, but they take insufficient account of forest
and rangeland/pastures, and they do not formally, or only weakly, link the economic
production modules to biophysical processes. They also tend to emphasise the spreador expansion of land uses and covers (v. FAO 1993a). Studies show, however, that at
the global and regional levels (save in the tropical frontiers) land-cover change fromexpansion has been slowing in recent decades, reaching a current rate of perhaps lessthan half of a percentage point per year (FAO 1993a). An important issue for the futureis likely to be the biophysical and biogeochemical consequences of land-use changes inplace, particularly their intensification. Existing agricultural models could provide
meaningful projections of this intensification in the short term. Furthermore, there
are forest, livestock, and biophysical process models available that could complement
current agricultural models, either by their partial integration or by iterative
application. This accomplishment would add to the robustness and breadth of interim
projections from existing models and extend their role in model development.
Existing models can be improved in several ways: by (i) increasing their robustness toproject land-use/ cover change for periods of 50-100 years and, where possible, at spatial
scales from the sub-national (regional) to the global; (ii) qualitatively andquantitatively improving understanding of the links between land use and coverchange; and (iii) testing ways of representing and relating crop production and resource
accumulation/ degradation processes. These improvements should be viewed as
immediate goals.

Activity 3.6
Validation/sensitivity analysis(l£!~)-~ Activity 3.7
L:S~c~en~ar~io~sp~e~c~i~fi~c~at~io~n~an~d~s~iI~nu:la~t~io~n~~~~~

Figure 14. Structure of Research Focus 3.

80

81

Global-scale models of agriculture and forestry can be improved for LUCC in two basic
ways with modest investments. They can be strengthened by integrating (e.g., formal
or informal protocols) the analyses of agriculture, livestock, and forest components.
This improvement could be achieved by drawing on several models, such as the IIAsAWorld Agriculture Model (Fischer et al. 1988), FORENA (Solomon 1986), the IIASA
Global Forest Trade Model (Kallio et al. 1987), CENTURY (Parton et al. 1987; Parton
et al. 1988), EPIC (Williams et a/. 1984), FLIPSIM (Richardson and Nixon 1986), IMAGE
2.0 (Alcamo 1994), and others appropriate for data or relationships between driving
forces and land-use/cover change. In addition, they can be extended in theirrepresentation of production processes to include important physical and biochemical
aspects, such as soil erosion and soil nutrient balance calculations. This work could
also link to Focus Activity 3.4 (below) for the development of improved ways ofinterfacing with the full range of economic and biophysical process models.
Some progress has been made in developing and linking regional land-use models(sometimes called Land Use Allocation Models, or LUAMs). They have examined thesensitivity of regional land use and changes to (globally-driven) commodity prices and(globally-agreed) trade practices (e.g., Parry et al. 1996). A range of such models should
be used to explore the possibility of developing a hierarchy of models that more
effectively captures the regional effects of global driving forces.
Considerable progress has been made in reconstructing the history of land-use/coverchange over the past 100 to 150 years (Richards 1990; WilIiams 1989). This work has
made it possible to estimate the roles of past factors influencing the pace and rate ofdifferent changes, but more work is needed to characterise these roles in detail and toprovide an empirical basis for model construction. It should focus on the period 1960
to present (but 1900 to present would be useful as well).
It is important to define more precisely the relationship between land-use change andthe vegetation/ cover attributes that play a major role in surface energy budgets,
through their impact on surface resistance and albedo, and in greenhouse gas fluxes.
Is the replacement of long fallows (forest or bush) by perennial plantation crops, or
paddy rice by wheat important? Similar questions arise with regard to changes in land
management practices, such as the shift from ploughing to minimal tillage without
any change in the cropping pattern. Such conclusions may have an important bearing
on the level of detail or projection preciSion to be aimed for in the development of the
new models. The task is to use empirical analysis or semi-analytical models todetermine the significance of the relationships between land-use/cover change andvegetation attributes, and if they are found to be important given the overall objectivesof the science/research plan, to parameterise them for use in Activity 3.2 andfollowing.
Land-use/ cover change data compiled from international sources, national
institutions, or case studies must be compatible. At the moment, however, there areseveral land-cover and land-use classifications in operation, leading to serious
inconsistencies between datasets (v. Young 1994; Mucher et al. 1993). Several UN
agencies and international institutions, in particular UNEP and FAO, have beenworking on this problem and seem close to agreement as to the classification systems
to be adopted (UNEP /GEMS 1994). Focus 3 should not attempt to construct its own
classification but should use these forthcoming classifications for the fast-track
approach (understanding that the development-track approach must couple with
Integrating Activity 1 on data and classification, described in Section 8).
82

Considering the above, provisional long-term projections of land-use/ cover change
could be developed. They should focus on changes over the next 50-100 years, estimate
possible biophysical and biogeochemical impacts arising from land-use/ cover change,
and improve understanding of the dynamics of land-use/ cover change as a result of
the main driving forces. This effort should also apply sensitivity analysis anddetermine priority areas for: (i) the activities undertaking the development of a newmodel structure, and (ii) the relation to other LUCC Foci. Finally, Focus Activity 3.1
should produce results within a 3-5 year time frame of implementation.
Focus Activity 3.2. Creating a new structure for modelling land-use and land-cover.
changeThe longer-term aim of Focus 3 is to create a new structure for LUCC models
possessing flexibility and a sound theoretical basis and the ability to integrate a variety
of approaches. There is evidence that, worldwide and in most regions, land-use/ coverchange is taking place increaSingly under the influence of the market and willcontinue to do so over the longer term. It is justifiable, therefore, to start from a model
based on economic theory. It is equally clear, however, that many forces distort orattenuate the price signals to which land and water resource users respond and thatsome of these users are socially or physically isolated from such market signals. These
conditions must find their way into the model structure.
Either the normative or the descriptive approach can be used to model humanbehaviour. The normative approach solves a welfare programme that maximises aweighted sum of agents' welfare subject to technological constraints. The welfare
programme is decentralised to the greatest extent possible under the given model
specification. Under decentralisation, all agents individually solve an inter-temporalmaximisation problem (e.g., utility maximisation for consumers, profit maximisation
for firms, subject to political intervention, as well as technological, social, cultural, andenvironmental constraints). If markets are competitive, then agents take prices asgiven, and prices are the only variables that affect them. There may be many othervariables that individual agents have to take as given, however, such as taxes or thelevel of provision of collective consumption. Prices can be obtained on competitivemarkets, if these exist. Other controls in the welfare programme have to be set
optimally by a government or some other higher level authority, taking thepreferences of the individuals into account. The normative approach is helpful at theconceptual level in showing socially desirable and economically efficient courses ofaction. It disregards the lack of information that individuals and even governments
face in practice, however, and it also neglects the fact that governments and otherorganisations often pursue other interests than the maximisation of social welfare.
The descriptive approach to economic modelling takes an empirical view of the
behaviour of individuals and governments and specifies functional relationships thatare estimated statistically and assume limited foresight. It permits the development ofmodels that can more easily be validated on past observations and used for short- to
medium-term policy simulations. Scenarios can be formulated that show how
specified changes of critical parameters will affect outcomes. Applied models of several
types are available that could be extended to include natural resources in a more
explicit way. The number of possible variations in the behavioural part may beprohibitive, however, and scenarios will not be optimal in any sense, nor can the83distance of a simulated solution from an optimal solution be assessed. Hence, as thetime horizon of the issues under investigation is long, it would seem unwise to rely
only on such descriptive models.

new databases for regional- to global-scale studies could be SOTER (van Engelen andTing-tiang 1993), land cover by the IGBP-DIS (Townshend, 1992), and, possibly in thenear future, the Global Terrestrial Observing System (GTOS; Heal et aI., 1993).

Moreover, given that most increased crop and livestock production is projected tocome fr?~ use intensification, models should be sensitive to technological change.
Most eXI~ting land-use/ cover change models treat this change with simple exogenous
assumptIOns. The new structure should seek to embody endogenous technological
growth and price formation, and use suitable approaches to include risk, uncertainty,
and any major non-market or institutional features of the driving forces that may be
identified through Focus 1. Finally, given the great spatial heterogeneity in both thequality and quantity of land resources and in the driving forces, the new structure
should make the land-use/cover change projections geographically explicit.

The situation is quite different for socio-economic datasets, in part because. of HOP-DIS
remains in its developmental stage. Those relevant and required for analysing LUCC
processes as proposed here, from national to village and household level data. Thereis a wealth of socio-economic databases available at the national level. A number ofthem, mainly economic data, are summarised in Yohe and Segerson (1992). The mostappropriate datasets for this project/programme are from (i) the UN: Demographic
Yearbook, National Accounts Statistics, Statistical Yearbook, World Economic Survey,
Energy Statistics Yearbook; (ii) the FAO: Production Yearbook, Trade Yearbook,Yearbook of Forest Products, Yearbook of Fishery Statistics, Fertiliser Yearbook,
AGROSTAT-PC (FAO 1993b); (iii) the ILO: Yearbook of Labour Statistics, (iv) UNEP:
UNEP Environment Data Report, (v) the World Bank: World Tables, World
Development Report; (vi) the IMF: International Financial Statistics, Balance ofPayments Statistics Yearbook, Government Finance Statistics Yearbook, Direction ofTrade Statistics Yearbook; (vii) OECD: Annual National Accounts, OECD Economic
Surveys, OECD Financial Statistics; and (viii) World Resources Institute: World
Resources reports. Compilations of these datasets are produced regularly in annual orbiennial cycles.

Both the driving forces of land-use/ cover change and their consequences in terms ofaltered use and cover have varying expressions at different scales. It is therefore
necessary to develop models that capture adequately the different interactions at (andbetween) regional, national, and global levels. Regional and national models need to
be based on detailed georeferenced bases of information relating to land-use potential.
These models should be receptive to variable input costs (e.g., fuel, fertiliser, feeds),
variable demand (reflecting demography, affluence level, and so forth), variable
production conditions (e.g., technology, ciimate), and variable prices (reflecting global
demand-supply functions). An interactive linked system of both regional and national.
models would then comprise a set of global land-use and land-cover models.
This facet of Focus 3, therefore, seeks to build on the strengths of existing models andrecent theoretical or conceptual advances to give (i) a more fully integrated
representation of the driving forces for land-use/cover change, and (ii) a more
complete and more dynamic and geographically explicit representation of these?riving forces, their interactions, and their impacts. This effort raises some major
Issues.
The LUCC research theme spans a multitude of different systems and processes, eachWith its characteristic scale and dimensions, data availability, and nature. Current
databases can be divided into two major classes: biophysical and socio-economic.
The biophysical a~d environmental attributes of land cover, such as soil, topography,
vegetatIOn, and clImate, are generally characterised by continuous changes over thesurface of the earth and have been expressed in a geographically explicit way using GIS
technolOgies. There are a number of GIS datasets on which to draw, and so the task
may be more of catalysing gap-filling activities than of taking the lead.
Th~ biophysical datasets are georeferenced and globally available on a grid or polygon

baSIS. The most relevant databases for this project/programme include: FAO/UNESCO
Soil Map of the World (FAO/UNESCO 1974; FAO/UNESCO 1988; FAO 1993c), climatic
data (Leemans and Cramer 1991; Chadwyck-Healey 1992), GLASOD: World Map of the
Status of Human-Induced Soil Degradation (ISRIC/UNEP 1991), United Nations list ofnational parks and protected areas (ruCN 1990; WCMC 1992), and various othercompilations of relevant data such as topography and vegetation (Kineman andOhrenschail 1992). Several international organisations (UNEP-GRID; UNEP-GEMS;
FAO; ISRIC) and research programmes such as IGBP, WCRP, and HOP are currently
also developing and compiling global datasets. As with land-use classification, theobjective should be to draw on and not duplicate other activities. The most promising84

In addition, there are relevant national level data provided by FAO in five- or ten-year
intervals. The FAO Forest Resources Assessment (FAO 1993d; UN-ECE/FAO 1992)
surveys forest cover every ten years. The World Census of Agriculture (FAO 1985"89;
FAO 1986; FAO 1992), carried out every ten years, is the major source of international
statistics on agricultural land use. Information on food supply and consumption is
published in FAO Food balance sheets (FAO 1991). Comprehensive datasets providing
national (for 141 countries) and broad regional time-series data regarding economic,
agricultural growth, performance, production and trade indicators are published by
USDA (USDA 1993). Finally, CIESIN (US) has begun to develop various data setsavailable in digital form, particularly that on population.
The listing above illustrates that many global and regional databases have beendeveloped and can be suitable for the LUCC activities. The data should be evaluatedon criteria such as quality, comprehensiveness, scale and resolution, time-span andcoverage, relevance, and compatibility with internationally accepted standards. With
respect to the last, methods should be developed to translate national standards (e.g.,soil classifications) into those internationally used.
National-level data are not sufficient for the needs of Focus 3, however. They are
seldom available in a GIS form, but are usually supplied aggregated in a tabular format
by economic or political entities, such as districts. National and, less often, provincial
boundaries have been digitised (although both change). For many of the other datasets .
relevant to the socio-economic driving forces, the situation is much less favourable.
Either the data are not available at the sub-national level, or they are so out of date as
to be of little value. The task here may therefore be more proactive, including thedevelopment of proxy measures and the preparation of guidelines on data characteristics and formats. ComprehenSive modelling of land-use decisions requires a
description of economic activities at the sub-national scale, including relationships
between economic sectors, and, in particular, data on production conditions, requirements, and multiple functions of major land-using activities, such as agriculture and85

~orestry. The g~ograp~ic units of the integrated model system will need to be describedm .terms of sacral attributes, econom.ic data, I~nd properties (e.g., topography, climate,soIi:,~ water, e~ol0!lY)' resource use Information, land management, infrastructure andpolItical orgarnsati~n (e.g., FAO 1994c). Such georeferenced databases with globalco".erage do not eXist, although relevant portions have been compiled in several
national-level studies (e.g., Himiyama 1992; FAO/IIASA 1993).
O~e of the ,:,ethodological innovations required in this project/programme is tobrld~~ the different characteristics of data. An obvious link is to create a geographically

explIcit database for the location and extent of the selected economic or political units
For I~nd-use studies~ however, it is often inappropriate, especially for larger units lik~
prOVInces or countrIes, to assume that the environmental or soda-economic
properties of these units are distributed homogeneously. Most often, the environmental properties are obtained. at a much higher spatial resolution. Many current
global ?atabases have a resolutIon of 10 to 50 km, whereas satellite images can havere:,ol.utlOns as low. as I? m. The heterogeneity of biophysical and environmental datawlthm an economic urnt can be used to study historic and current land-use patterns
and to develop models to analyse future patterns.
The comp~ex and multi-dimensional driving forces must be carefully structured andparametensed for Implementation in regional or global models of land-use and landc~v~r ch~nge. Type: spatial characteristics, and temporal scale of a driver must be
distingUIshed. For mstance, it may be possible to describe the driver's influence interms ~f objectives ?f land owners, of constraints to human activity and land use, or as
dyn~lc accumulation.and degradation processes that affect physical land-use
conditIons and constramts or change the policy focus and value system.
A hiera~chical d~c~ion stru~ture is needed that links producers reflecting a range of
productIon conditions (e.g., mtroduced as prototypical fanns, ranches, and forest
enterprI~~s) t~ consumers, ~ifferentiated by income class, location (i.e., rural or urban),and poslt~on m the processmg, marketing, and final demand chain, and to governments acting urnla.terally or multilaterally. A decentralised representation of a large
nu:nb~r of agents m the model syst~m m~y be most appropriate to support the overallobj~~tives of F~~ 3. It ~llows for I,!,posmg structure at the higher levels of social and
polItIcal orgarns.ation by Implementing market clearing conditions, national or
regIOnal constramn: on commodity and resource flows, and budget constraints; but it
also allows for a falf amount of flexibility to include geographic socio-economic andcultural specificities of different regions.
',
For eac~ .group of actors: m?delling the key behavioural responses in terms of their
ge?-p.olIti.cal/ ~ltural obje~tives and constraints is required. This calls for innovative
thmkmg In conjunction. With Focus 1 and Focus 2 on the application of decision
theory, welfare economiCS, and spatial statistical analysis.
Technology is .use.d here to embrace all innovative processes that enable land, inwhate.ver app.lIcation, t? meet the demands placed on it at socially acceptable costs.
Such mn?~atlOn may mvolve movement along existing production levels exploiting
opporturnties for :actor substitution (e.g., capital for land and labour), or movementfrom one pr?~uctlon surface to another, with implications for resource use efficiency
and profitabilIty, land-cover attributes and material balances. In many models
technological change has been treated as exogenous to the economic system. But
much work has focused on the evolution of technologies as pressures on land mount86(e.g., Boserup 1981). This work suggests that technological shifts are, more often thannot, endogenous to the particular system. Mechanisms for endogenising technologicalchange will be inserted into models used for long-range projections. They will draw onestablished theoretical concepts and empirical findings on induced innovation andintensification and the effect of population pressure and market development ontechnological change (e.g., Hayami and Ruttan 1985; Pingaii, Bigot and Binswanger
1987; Kates, Hyden and Turner 1993; Tiffen and Mortimore 1993).

The actors in the social and economic systems (e.g., producers, consumers, andgovernments) act with more or less foresight, depending on the severity of individual
short-term constraints, amount of infonnation available to them, and prevailingnorms and value systems. In a realistic assessment, dealing with uncertainty is
unavoidable. Uncertainty is relevant in relation to land resources, not only because of
the variability of weather conditions, but also because of uncertainty about processes ofenvironmental degradation, future costs and benefits of investments, production
functions, and availability of resources.

Focus Activity 3.3. Extending the horizontal linkages
Ultimately, the aim of LUCC models is to employ a more fine-tuned matrix or fabric ofland uses and cover to project change. To do so requlres LUCC models to account more
fully for the spatial variability and dynamics of land-use sectors, including enterprises
and interactions within each sector. Predominantly market-driven and non-marketdriven enterprises of a sector, multiple sectors, or both, for example, commonly coexist within a region. Many parts of the developing world contain market-driven
logging along with subsistence cultivation, the two interacting through particular local
dynamics that lead to land-use and land-cover outcomes that would differ considerably
if one or the other sector were not present or were driven by different forces (e.g.,
Kummer 1991; Kummer and Turner 1994). In addition, the differentiations andinteractions between urban and rural sectors must be elaborated. Urbanisation is a
global phenomenon (e.g., Simpson 1993), and urban demands increasingly influencerural land use. This influence is a given in developed economies, and urbanhinterland use models have a long tradition (e.g., Chisholm 1962), even identifying
global cores and hinterlands (e.g., Wallerstein 1974). Similar dynamics are now
influencing the peripheries of less developed economies (e.g., Mortimore 1993), andthey could be incorporated into land-use/cover models.
Economic models usually organise production activities in terms of economic sectors.
At the highest aggregation level, the following sectors are often distinguished:agriculture, forestry, energy, and other non-agriculture. Sectors with a strong relation
to land use must be further subdivided; in particular, agriculture and forestry. In eachsector a variety of production conditions will need to be distinguished. For example,
agricultural production in a geographical unit can be described as cumulative output
from a collection of representative farms. Such differentiation should refied majordifferences in production conditions (agro-ecology, fann resources, infrastructJlfe, andso forth) and, for the purpose of the land-use and land-cover change theme, relate to
the dominance of various driving forces (i.e., prototypical situations or constellationsof driving forces). To be empirically founded, this requlres appropriate georeferenced
datasets and advanced methods of spatial statistical analysis, and needs to build on
infonnation derived from Focus 1 and Focus, 2 activities.
87Models must devise suitable mechanisms for distinguishing between urban and rural
demands, possibly by differentiating spatially and economically between urban andrura~ se~tors. The increasing urbanisation of the world population has triggered major
qualItative and quantitative changes in pressures on land use and land cover that must
be modelled through a .more complete representation of the non-agricultural
economy. The mechanIsms should be related to urbanisation and rural-urban income
differentials, in part to capture land-cover change for human settlements andinfrastru~ture: but more imp~rtantly because of the push-pull factors underlying ruralurba:, mIgratIOn. These are lIkely to reduce pressures for marginal land development
and mcrease pressures for the intensification of production and the consolidation ofsmall land holdings stemming from labour shortages or higher wage rates.

(e.g., Japan and Korea), and complex real price and income effects that need to be
separated. Third, major headway needs to be made on data collection and empiricalanalysis of the effect of urbanisation on the demand for livestock products, and in turnon the structure of livestock production and imports. It has major implications for

Focus Activity 3.4. Refining the vertical linkages

To project land-use changes into the second half of the next century, it will be necessary
to describe resource accumulation processes and feedbacks and non-linearities ofLand us~s are !nfI,;enced by the nature of consumption-production relationships andby the bIOphysIcal Impacts and feedbacks following from the use (Leemans 1992;
Solomon et al. 199~). These vertical linkages must be more fully incorporated into
LUCC ,:,?dels. It IS apparent that the links between consumption and production are
mo:e crItIcal to land-use/cover cha,;ge than previously recognised in global or evennational models. In the long term, mcome growth, rapid urbanisation, education, andexposure to other cultures will all have major impacts on demand patterns and henceon land-use/cover change, biogeochemical cycles, and other aspects of global change.
For example, there may be a significant global shift from rice to wheat (Crosson andAnders.on. 1992), witi.' important implications for pressures on wetlands, greenhousegas emISSIOns, and nItrogen cycles. The demand patterns of high income groups in acountry a:e.currently.a reasonable indicator of what the rest of the popuiation will do
w~en thel! mcomes rIse (FAO 199~a! Parikh 1994), but the long-term validity of thisclaIm .ne~ds to be tested. Most eXIsting land-use/cover change-oriented models makeonly lImIted allowance for urbanisation effects on demand patterns for both food andfuel; yet they can be substantial, leading to important impacts on land use and cover.
Thus the structure and dynamics of demand patterns and their implications for landuse change need further analysis.

impacts on land productivity. Here, the terms "resource" and lIaccumulation" areused in a general sense. They include human resources (e.g., population number,

Likewise, the biophysical impacts of land uses and their ultimate feedbacks on the uses
nee.d careful ~onsideration, not only because they are inadequately considered in mostsOClo-e.cono!,;,c models, but because their nature and significance are contested. Soiland soIl nutrIent losses, degradation of grasslands, and depletion of aquifers affect theland uses that gave rise to them. The time scales of such losses must be addressed aswell because of their implications for sustained land use, about which many assessments may be overIy pessimistic (e.g., Bie 1990; Nelson 1988; UNEP 1992). Attention
mus.t also be paid to improvements in the biophysical condition of the land by and forparticular uses.
At least three aspe~ts of t~e ,:,odels need attention. First, further analysis is required of
the factors underlymg ShIfts m cereal demand - for example, from rice, maize, or root
crops to wheat (Ingco 1990; Mitchell 1991). Such shifts may have few implications forland-cover change per se, or for some aspects of land use in that the vegetation attributes.of many cereals are broadly the same, but they may be important for biogeoche:nIcal cycles. Se~ond, food-demand analysis needs to be expanded over longer time
penods. Most detaIle? anal~ses have covered periods of only 10-15 years; nonethelessthey show strong national dIfferences, even between culturally similar countries
88land~cover c~ange (i.e." conversion or reversion of range or more intensive manage·

ment of grazmg land VIa the demand for feed grains of domestic or international
origin), but has not been adequately analysed. This work should be closely allied to thelinking of the key actors/agents of land-use/cover change (Focus Activity 3.2); to thedevelopment of enterprise models, which will include different forms of livestock
production (Focus Activity 3.3); and to the research on rural-urban linkages (Focus
Activity 3.3), because it is strongly related to questions of rural-urban income
differentials and altered lifestyles.

distribution, age structure, migration flows, fertility, skill level), renewable and nonrenewable natural resources (e.g., soils, minerals, water, -air), biological resources(e.g., biodiversity), and economic resources (e.g., capital stocks and machinery).
Accumulation also includes various degradation processes, physical (e.g., soil erosion,
degradation of soil structure, groundwater depletion) and chemical (e.g., acldification,salinisation, and toxification of soils, depletion of the ozone layer, nitrification ofgroundwater).
There are two main possible approaches. One is to use separate economic andbiophysical mode.ls and link th.em so that the output of the former becomes an input
for the latter or VIce versa. ThIS approach has the advantage of relative functional
simpliclty and transparency, perhaps at the expense of theoretical rigour. The altema?ve is to find so:,,"e practical way of introducing selected biological processes directly
mto the economIC model. Both approaches need to be explored. Given the large
uncertalnties in the dynamics of many biological processes, however, it may be best toconcentrate on the former or try for a hybrid approach that only uses the more complex
approach where its theoretical and empirical foundations are well established.
A complicating factor is the different time and space scales at which these processes
operate.
Focus Activity 3.5. Introducing water into the land-use/cover change projections
I:, ,:,any areas of t~e w.o.rld, water usage has approached or will soon approach thelImIts of water avaIlabIlIty (Falkenmark 1989; Gleick 1993; Kulshreshtha 1993).
Agriculture has been and continues to be the principal conSumer of water worldwide
and.the s~~rce.of major ~quifer d.epletion (e.g., PosteI1993). Many analysts expect thatthe mtenslfIcatlOn of agrIculture m the future will centre on the expanded and~tensified use of irrigation (e.g., FAO 1993a). It is of critical importance, therefore, toImprove our understanding of how, in the long term, competition for water, its
distribution mechanisms and price, and water-related policies may affect land-use andland-cover change, and conversely, how land-use/cover change may influence thewater cycle and water supply. This effort requires the introduction of the price, policy,

89ii

and institutions of irrigation water into the crop production function. It also requires
the modelling of various environmental aspects of water use, such as soil salinisationand toxification and consequently crop productivity decline.
To provide information on future availability of water reso,:,rces, a hydrologic. .
modelling system needs to be developed. Several hydrological models of vary~ng
complexity and sophistication have been used to investigate the effects of predictedclimatic change on water resources (e.g., Bultot et al. 1988; Kite 1993; Strzepek et al.
1994; WMO 1987). The importance of feedback mechanisms that operate between acontinental surface and the overlying atmosphere have been demonstrated for West
Africa (Savenije and Hall, 1994). Modelling the impact of land-use/ cover change onwater supply requires improved datasets and understandi~g of complex biosphericmechanisms to capture indirect effects as well, such as the Impact of change m upperbasin watersheds on lower basin vulnerability.
The amount and intra-annual variation of water supply depend not only on theabundance and reliability of water resources but also on the development andmanagement of a water resource infrastructure consisting of dams/reservoirs, pumps,
canals, pipelines, and wastewater treatment facilities. These factors could be modelled
through a water development sector that is price- as well as policy- and institutiondriven. Where pOSSible, modelling should refer to georeferenced water stocks permitting the representation of major river basins (Winpenny 1994). In addition,. it isclear that water infrastructure is an important aspect of national development m terms
not only of water supply but also of flood protection and its relation to land use andcover.
Land use, population, and lifestyles are the driving forces behind water demand.
Agriculture is the primary water user globally. Changes. in land use c.ould havedramatic impacts on water demand. Demand for water IS also much mfluenced byeconomic and technological factors. Water use is not fixed per unit of land but
depends on the crop being grown and the agricultural/irrigation technology andmanagement used. In many cases, therefore, it may be more econom~cal to ~djust
water demand through increasing efficiency of water use rather than mcreasmg watersupply. Yet changes in agricultural technology require capital, creating competition
with other sectors of the economy for scarce investment funds. Of equal importance towater supply and demand are legal and institutional factors (FAO 19~4a) and. politicalarrangements, such as international agreements in the case of large mternationalrivers. Successful modelling of water demand and distribution will require theassembly of improved national data on water use by sector, including prices andsubsidies (e.g., FAO 1994b).
Water supply is measured not only in terms of water quantity, but also in terms ofwater quality. In the context of land-use/cover change, water quality is a cruciai
attribute to model (Novotny and Olem 1994). Depending on use, water demand isbased on certain levels of water quality. Different land uses can significantly change
downstream water quality: agriculture through chemical application and non-point
source pollution, industry through point source pollution, cities through non-point
source and municipal wastewater pollution. Hence, a simplified simulation of water
quality in receiving streams, lakes, and reservoirs and in ground water is required in
the LUCC modelling effort (e.g., Somlyody et al. 1994).

90.

To model the environmental risks of water use in agriculture, two major components
are needed: (i) modelling the process of non-point pollution generation fromagricultural production and irrigation (Zannetti .1993); (ii) mode~li~g the qu~lity ofstreams, lakes/reservoirs, and groundwater aqUIfers that are reCIpients of thiS
pollution (Thomann and Mueller 1986).
Modelling the generation of agricultural pollution loads requires data on soil types,
slope steepness, land use and management, cropping patterns and yields and amountof fertilisers and pesticides applied, as well as coefficients of chemical runoff.
A number of detailed process-oriented models of this class are available. AGNPS,
CREAMS (Knisel 1980) and SWRRB, SWAT (Arnold 1994) have been extensively
applied at the field level and for national assessments. The use or modification ofthese models would be recommended.
Modelling the quality of streams, lakes/reservoirs, and ground~ater aqUifers that ~rerecipients of agricultural pollution requires the inclusion of pomt and vector data m
the spatial framework of the model. In addition, the topology of lan? u.se and the
network of water bodies must be specifically modelled as water-quahty Impacts arefrom upstream to downstream. Decay and dilution pr?cesses m~ke the dist~nce fromthe source of pollution important. Surface water-qualIty modellmg sh~uld mclude. asa minimum the oxygen, phosphorus, and ~itrogen cycles. Where possible, mod.ellIngof non-traditional pollutants, such as orgamc substances and heavy metals, for riverwater and sediment is suggested. Groundwater-quality modelling should include as aminimum the nitrogen cycle, and possibly the phosphorus cycle, organic substances,and heavy metals.
In addition, particularly severe environmental consequences have bee;, documented
in relation to large-scale irrigation (Postel 1992). By far the largest environmental
risks of irrigation relate to water logging and salinisation. Irrigated agricultural production also poses the risk of water and soil toxification. Finally, unsustainable overpumping of water sources in semi-arid regions has led to major drops in water tables
and surface water and to large-scale environmental degradation (e.g., Kotlyakov 1991;
Micklin 1989).
Focus Activity 3.6. Model validation and sensitivity analysis
The usefulness of a quantitative model for prognostic purposes depends to aconsiderable degree on its descriptive accuracy. This is particularly so for an integrated
model system in which several components are interdependent, and where even the
directions of the responses are often not predictable from qualitative arguments alone.
Therefore, the models must be subjected to sensitivity analysis and validation, to test
how well the models describe the continent/region as it is. The difficulty of evaluatinglarge model systems has often been pOinted out (e.g., Lewandowski 1981; Chow andCorsi 1982). There is a wide variety of methods that are applied (K1eijnen 1992). Except
for certain classes of models where statistical tests can be applied (e.g., Challen and
Hagger, 1983), however, validation procedures are often not formalised, and include
subjective judgement for evaluation.
The task of model and data validation will be facilitated by establishing reliabledatabases and specifying the model system on a solid theoretical basis. Apart fromtheoretical consistency and rigour in model specification, and, of course, verification of91

8. Integrating Activity 1:
Data and Classification

model implementation, testing the influence of unusual data points, testing formisspecification, and testing for alternative specifications, stability of parameters, andpast tracking ability will be of importance. The project/programme should attempt toformalise the validation procedure as much as possible.
The sensitivity of model results to changes in critical model variables and assumptions
should also be tested. Small differences in the initial constellation of key parameters
could lead to major differences in the long-term development paths because of thecomplexity of feedbacks and cumulative processes that characterise both the socioeconomic and the natural resource components of the system. Different methodologies are used to assess the sensitivity of large system models (e.g., Klepper andHendrix 1994; Leemans 1992; Swartzman and Kaluzny 1987) but new techniques must
be developed to deal with the complexity of such global integrated models.
Focus Activity 3.7. Scenario specification and simulation
Given the large uncertainties regarding the long-term evolution of key driving forces,
such as population growth/ distribution and per capita income growth, it is importantto establish a number of well-defined scenarios over a plausible range of pathways forsocio-economic development and policies to help delineating the possibilities for longterm land-use/cover change and its biophysical impacts. Also, scenarios related tolong-term global environmental changes are required that would indicate thesensitivity of land use and land cover to, for example, greenhouse-gas induced climatechange.
Scenarios should cover both historically important driving forces as identified in Focus
Activity 3.1 and new potentially emerging factors. The complexity of the issues
analysed and the large number of possible assumptions on key driving factors
conceivable in a spatially explicit model of land-use and land-cover change call for
careful selection and methodological innovations in scenario design.

Introduction
Data for a land-use/ cover change programme will come from a variety of physical andsocial science sources. This interdisciplinary programme will require close cooperation
between the IGBP and HOP Data and Information Systems Offices. Some of therequired datasets can be defined now, and these have been described in the sections
below; most, however, cannot, so the issue at hand is the development of the process
by which these datasets can be defined and acquired.
The first step will be to cultivate collaborative working relations between HOP-DIS and
IGBP-DIS. Many of the datasets being developed now by IGBP-DIS will be important
for the LUCC programme. The scientific rationale for these datasets, however, hasbeen defined largely by physical and biological requirements; for these datasets to be
fully useful, some integration and augmentation with social science data will be
required.
The integration of social-science datasets with physical-science datasets is seen as a
crucial step in the development of data for LUCC. For instance, in the sections below,
the need is articulated for a land-use datase!. This kind of data could possibly be
developed using the A VHRR 1 km dataset being developed by IGBP-DIS, but it will
also be necessary to integrate with the remote-sensing data other sources of
information on land tenure, land management and other factors which will define
land use as opposed to land cover. Moreover, it is likely that sharing of data between
IGBP-DIS and HOP-DIS will be necessary. The implementation of some formal
mechanism for data exchange and collaboration in the development of datasets istherefore necessary.
In the sections below the data requirements are divided into two broad categories.
The first relates to the development of land-use and land-cover classifications for the
LUCC programme. It is essential that these classifications lead to a refined stratification
scheme, in order for the development of typologies and models (Foci 1 and 2, 3
respectively) to begin. The second relates to the development of datasets themselves the acquisition and organisation of data from new and existing sources, related to bothsocial and physical science.

Oassification
LUCC studies will require a global approach to land-use and land-cover classification.
While it is understood that there is no such thing as a universal classification scheme,
appropriate classifications will need to consider the different dimensions of land use
and cover. A sound classification requires the following characteristics:

92

93

•

It must be comprehensive•

The criteria must be based on inherent dimensions of land use and cover; in thisway the land-use and land-cover classification will complement otherclassifications (e.g., of soils, vegetation, and farming systems)

•

•

•

•

The diagnostic criteria for the classification of land use should be those associatedwith the land use over the long term (e.g., burning is one of the consistentcharacteristics of shifting cultivation, even though the action takes place in a few
hours or in a few days)

The dynamiCS or evolution of land use and related cover, as expressed in two
fundamental ways: input intensification (increased inputs of matter and energy intime and space) and disintensification (reduced inputs ending in a return to seminatural vegetation).

For the intent or purpose meaning of land use, the key attributes that allow linkages
between the behaviour (decision making) of the land manager and the biophysicalmanipulations employed must include at least the fOllowing:• The specific structure of the inventory managed (e.g., regrowth forest, beef or dairy
cattle, maniac or cassava)

The basic unit of land cover must be a geographically explicit unit (i.e., a unit ofbiophysical management). For instance, the field/parcel/plot is not a useful unit
whereas any unit of biophysical management can be applied to a range of land use.
To the basic unit of land cover corresponds the unit of socio-economic management, which may be geographically different because it sometimes includes nonland-use activities or non-geographically explicit units such as the household• The major landesque capital requirements for the management (e.g., irrigation,

The diagnostic criteria, independent of the level in the classification, must be
differentiating characteristics at the "field" or land-user level, similar to the use ofdiagnostic horizons in soil classification• The dynamics of output intensification and disintensification as expressed in two•

Unlike the basic unit of analysis, which is scale-dependent, the land-use
classification as such must be scale-neutral, meaning that the classes at all levels of
the classifications should be applicable at any scale or level of detail•

The land-use classification must be a multi-categorical system, with only a few
diagnostic criteria and classes at the highest level; at lower levels, the number ofdiagnostic criteria increases, as does the number of classes; diagnostic criteria usedat one level of the classification should not be used again at a lower level.

The higher levels of a global land-use/ cover classification should be accepted worldwide. At lower levels, classes can be included or left out depending on the region andthe purpose of a study, but these classes also need quantitative boundaries to makesome comparison possible. For the biophysical-manipulation meaning of land use, thekey attributes for global change research must relate to land cover, and include at least
the following:•

The effects of vegetation structure, phenology, and composition•

The effects on physical, chemical, and optical properties of soil and rocks•

Patterns of distribution of biophysical management (or technc-managerial
strategies) in space and time•

A quantification of the effects of changes in cover resulting from land use on
future potential uses (feedback effects)

94

terraces, modern crop varieties, fertilisers, tillers)•

The kind of economi~ production in which the management unit is engaged(e.g., private ownershIp, rent/lease, sharecrop, cooperative tenure)fundamental ways: yields (output per harvest) and land productivity (output perunit area and time).
Modern information technology, in particular through storage, analYSiS, and retrieval
in thematic and geographical databases, has weakened the need for a rigid global landuse classification. There remains strong agreement within and outside the globalchange commumty, however, on the need for a clear and standardised approach toland-use classification and terminology.
Integrating Activity 1.1. Developing land-use and land-cover classification systems
It is uniikely that one classification system can serve the needs of the LUCC project/programme, given their interest in both biophysical and human use as well as cover.
The plan favours the development of a systematic approach to land-use/cover inwhich the attribut,:s for the three dimensions (biophysical manipulation, purpose, andenVl!onrnental setting) of land use are clearly defined and for which standardised data
can be collected and reconfigured for multiple uses. This activity, therefore, will:(i) determine a minimum set of descriptors to identify and classify land use and related
cover; (ii) define a .c?mmon terminology on land-use/cover definitions for globalchange purposes; (m) develop and implement a fiexible, multi-dimensional databaseformat on global land use and related cover that will be able to handle the various
dimensions of land use and cover, based on improved statistical techniques; (iv) design
the structure of a standard global reference classification of land use and related coverin cooperation with FAO and other programmes undertaking such efforts; and (v)develop a commOn procedure of land-use mapping in the context of global change.

95

Data
The classification and analysis of LUCC will require a significant amount of new andreformulated data. These data involve land cover, land use, social and biophysicaldrivers, and proximate activities or land management with the aim of providing .
resolution from -1 km to the subnational, depending on the variable. For the mostpart, data on land cover and various biophysical variables have been more thoroughly
assessed in terms of needs and collection format than have those on land cover andsocial variables. This reflects, in part, the efforts of IGBP-DIS to address land cover.
HOP-DIS is in the process of initiating an assessment of the needs for land-use andsocial variables.
Integrating Activity 1.2. Land-cover mappingThis activity will promote the continued development of high resolution land-cover
mapping by: (i) providing a classification scheme suitable for the three LUCC researchfoci; (ii) developing regional! global land-cover classification maps at 2 km resolution
as well as (Hi) regional! global land-cover parameter maps at the same resolution; and(iv) coordinating the above with the IGBP-DIS 1 km Land Cover project.
The current distribution of land cover worldwide is not well known (Leemans, Cramer
and van Minnen 1995). Regional stratification of vegetation and land-cover types isrequired for most global change models. A land-cover dataset at a spatial resolutionof -2 km would enable the assignment of variables such as biomass, combustion
efficiencies and the like, and would provide a framework for integrating the biophysical aspects of land use mentioned above. These kinds of data do not now exist,
but programmes such as the IGBP-DIS Land Cover initiative are under way to develop
them. It would be prudent for LUCC to coordinate its requirements through theseongoing activities rather than initiating new activities.
Beyond the classification or stratification of land cover, it is important to have acomprehensive assessment of vegetation arid land cover as it relates to the seasonalpatterns of greenness and vegetation phenology. A characterisation of growing season
length would be valuable for further elaboration of the biophysical regime in which
land-use and land-cover conversion is taking place, and for developing the feedbacks
on land-use processes from the physical setting (see Focus 1).
This kind of information is also important for the development of improved globalchange models, such as those focused on issues of Net Primary Production (NPP),
ecosystem metabolism, and carbon cycling. To facilitate the integration of LUCC
processes with these models so as to better develop coupled global models, it isimportant to have coordinated development of such databases. For instance, it will be
important to couple net fluxes of greenhouse gases derived from anthropogenic
impacts with gross exchanges of gases between the atmosphere and the biota to closethe carbon budget in real time. Studies which pull together the exchanges of carbon
from deforestation, fossil fuel burning, oceanic uptake, and biotic metabolic exchanges
during the period of the last 20 years when these atmospheric measurements havebeen taken can be important contributions to our understanding of the carbon cycle,
and hence one critical facet of global change.

96

Further, the development of climate-sensitive, process-based ecosystem models which
treat the geographical and seasonal variation in phenology, NPP, and gas exchange canbe used in the development of climate response analyses. These analyses would
support the IPCC process, as well as vulnerability assessments (e.g., IPCC WG m. Suchanalyse:, of clim.ate-fo;ced land-cover change would provide a basis for mitigation andadaptation studies. Fmally, the feedback between anthropogenic land-cover change
from climate change could be explored.
A premise of this Integrating Activity is that satellite remote sensing is the only viableapproach to developing global land-cover information. Synthesis of existing maps
cannot provide a globally consistent and up-to-date database for the purposes of thisprogramme (Townshend et al. 1991). An activity driven by remote sensing is obliged
to address several technical issues, such as a need for agreement on the land-coverclassification schemes for carbon modelling. Such an agreement is currently beingsou?~t by the IGBP-DIS Global Land Cover Working Group. The proposed Integrating
ActiVity would pursue close involvement with this international activity.
A useful distinction can be made between land-cover characterisation in natural andanthropogenic systems as a function of the spatial scale of land cover. In general,coarse resolutIOn sensors can be used for rnapping natural systems; however, the highspatial variability of agricultural systems requires the use of high resolution data.
Automated approaches are preferred for high temporal resolution data, whereas
manual, automated and hybrid approaches are used for analysis of high spatial
resolution data. It should be noted, though, that the impact of seasonality on theinterpretation of high resolution data is sufficiently problematic that a combination ofcoa;se. and hig~ resolu.tion data may be needed to address anthropogenic systems.
A slImlar mulmesoluhon approach may be needed to characterise wetlands animportant ecosystem with respect to methane emission.
I

As mentioned above, it will be important to build on existing programmes where
possible. There are several ongoing activities through which a LUCC programme
could coordinate its data requirements for land cover:• An improved global land-cover map is being generated in the US using the global
1 km AVHRR IGBP dataset which has been compiled through National
Aeronautics and Space Administration (NASA) funding in cooperation with the
National Oceanic and Atmospheric Administration (NOAA) and the European
Space Agency (ESA), extending the research presented by Loveland and colleagues(1991).
.

•

A global sample of land-cover test sites is being developed through the NASA EOS
Landsat Pathfinder programme. The sites are being selected as a basis forvalidating satellite-derived global land-cover distributions. The sample datasets
are representative of a range of global land-cover types and, where possible, arelocated where there are ongoing field-based monitoring programmes.

•

A good example of a regional! continental scale land-cover mapping study is there<;ently completed USFS/USGS US Forest Cover Map. This map was produced
usmg the 1 km A VHRR dataset generated by Loveland (1992). A similar effort isbeing undertaken by the US Forest Service for Mexico with the help of in-country
collaborators. An Interagency Multi-Resolution Land Cover Characterization

97

(MRLC) project, implemented by the United States Geological Survey (USGS) on
behalf of a number of federal agencies including the Environmental Protection
Administration (EPA), is generating land-cover datasets for the conterminous US.
These datasets include products from coarse and high spatial resolution satellite~
sensors.
••

An example of land-use intensity mapping is a study involving interpretation ofLandsat imagery performed by uses for the United States Agency for International
Development (USAID), covering several countries in Southern Africa.
There are several international projects, for example: the Corinne Project of theECE, which has generated land-cover information for Western Europe; theproposed Africover Project of the UN/FAO, which will provide high resolution
satellite derived land-cover data for Africa; and the TREES Project of the ECE,
which is providing comprehensive forest-cover mapping of the entire tropical belt.

Integrating Activity 1.3. Land-cover change mappingThis Integrating Activity will: (i) define critical land covers and geographic regions;(ii) develop datasets of land-cover change in each cover type for the past 20 years;(iii) develop datasets of land-use/cover change from tabular statistics for the past
100 years; and (iv) coordinate with IGBP-DIS High Resolution data and other relevant
projects. While global land-cover stratification I class~fication can be achiev:d at ~he
1-2 km resolution, precise measurement of.changes In land-cover converSIOn WIllrequire information of a much higher resolution. Thus, the activity emphasises highresolution remote sensing of land-cover conversion. It would provide comprehensive
data on land-cover conversion over very large regions, building on existing programmes through continuation of ongoing efforts coupled to new efforts in importantregions not heretofore covered under existing activities. One emphasis sho,:,ld be on
obtaining quantitative and geographically-referenced datasets on the dynamiCS ofdeforestation and reforestation (secondary growth).

effort would define where and how much land-cover change exists in a region;
thereafter, the stratification of forest types and critical regions could be enhanced by theuse of coarse resolution information from Activity 1.2 above.
Acquisition of Landsat imagery can be coordinated regularly every 3-5 years to obtainclou~-:r:e coverage systematically throughout the regions of interest defined by theacq';'lsltion plan. The bes~ way to achieve this is to rely heavily on the foreign groundstations. These geographically-referenced measurements can directly support the IPCC
process, whic~ is being establishe? to make in~entories at intervals of approximately
five year~. This accurate and preClse deforestation data would be an important
contribution to the IPCC methodology concerned with biotic carbon dioxide emissions.
To ensure that a uniform, consistent, a:,d m';ltually agreed-upon method is employed,
It w,:uld be necessary to convene a senes of mternational workshops under the
auspices of the OECD methodology-development activities.
To ob:ain annu~l estimates of deforestation and land-use change, a very efficient
stratified samplmg scheme could be employed to define deforestation rates between thecompl~te in.ventory I census years, spaced 3-5 years apart. The stratified sampling could
be accomplIshed usmg the last complete inventory I census, since this dataset would
map the locations of deforestation. The assumption is that deforestation would bespatially persistent over the 3-5 year interval until the next complete inventory.
To conduct this data acquisition effort, it will be important to coordinate it with thedevelopment of empirical models mentioned in Focus 2. These models could havehighly predictive capabilities in regions of persistent patterns and rates of land-coverconversion.
The complete-coverage analyses to be made every 3-5 years could oniy provide
inventories of the various land-cover dasses (e.g., deforested land, secondary growth);
they would not provide annual land-cover transition sequences, such as the change
from forest to pasture to secondary growth and back to pasture. To do this it will benecessary to anchor a series of test sites, each the size of a single Landsat or SPOT scene,in which annual acquisitions are made. Co-'registered scenes could be compared todetermine the various land cover transition probabilities.

The activity should begin with a careful definition of science requirements, key regionsof study being targeted with the intent of making specific and direct contributions to
global change research, national goals, or international policy. Next, it would be
important to develop a well-designed data plan or acquisition strategy. Because it will
not be possible to get global coverage from Landsat alone until the launch of Landsat 7
later in this decade, a multi-sensor acquisition model is the only feasible approach for
global coverage. This involves the development of internati?nal cooperatio~ wi:hother satellite operators. Some of the important programmatic groundwork IS bemg
laid through the IGBP ICEOS High Resolution Data Exchange Project. Still, technicalwork must be done to develop an efficient acquisition scheme involving several
sensors that differ in coverage, resolution, formats, repeat times, and other characteristics. With Landsat alone, coverage can only be obtained where there are groundstations. Acquiring data through purchase agreements with ground stations is difficult
and time-consuming. A careful acquisition plan for high resolution data must be
made based on scientific and technical priorities.

eXlstmg land-cover change momtormg efforts, particularly for new regions outside thetropics, seasonal forests in the tropics, savannas, and other land-cover types. The
methodological iss';les !ndude the development of classification techniques, Objective
bou:,da:y I dass defmltions, b,:st means for change detection, registration and orbit
na':lgation, a:,d sce~e processmg. The specific method employed may vary fromreg~on to :eglOn. It IS necessary, therefore, to define appropriate methods for eachregion of m terest.

Forest monitoring using high resolution data such as that provided by Landsat or
SPOT could provide wall-to-wall mapping for an entire region. An initial mapping

The technical research and development should be linked to the programmatic
mfrastructure so a umform method can be utilised in IPCC and FCCC activities.

98

Th~se test sites w?uld also be used for a field validation and accuracy assessment effort
which would defm,: and track the. measurement variance and error. This component
WIll need to determme accuracy WIth respect to: (a) variance due to positional accuracy(i.e., the mapping precision); and (b) variance associated with image interpretation.

There is great promise that remote sensing techniques can be applied globally, but

m?r~ research is needed to deve!op .the techniques and approaches employed by99

A workshop series developed through the OECD could be a useful starting point for
defining a common methodological framework which could be integrated into theexisting OECD/IPCC methodology.
The degradation of forests is becoming an important issue, yet more research needs tobe done before it will be possible to incorporate this approach into remote sensing
techniques. It is feasible that satellite data can be used to quantify the areas of forest
which have been degraded for selective logging.
As biomass burning is an important cause of land-cover conversion and an importantland-use practice, data should be acquired on the rate and area affected by biomassburning. Different methodological approaches have been developed in different
vegetation systems as a function of the longevity of the bum scar features and their
spatial scale. The use of active fires provides direct information on the timing andlocation of fire activity, but is an intermediate step in determining area burned. Bothcoarse and high' resolution satellite data are used in the existing approaches tomonitoring and calibrating burned area; a global satellite data acquisition strategy isneeded to support this research.
The development of global fire and burned-area products is an important issue.
The current regional approaches must be evaluated and refined in the context ofdeveloping a global monitoring system. It is likewise essential that an assessmentof the accuracy of the areal estimates be provided for each technique.
The programme should develop direct links to, and integration with, international
efforts with the following programmatic infrastructure: governmental global change(through IAI, APN, ENRICH); non-governmental global change (IGBP, START, HDP,
WCRP); observational/monitoring programmes (GTOS), coordination and acquisitionof data (IGBP-DIS, HDP-DIS, CEOS, LGSWOG), and assessments and in-country
programmes (FAO/TFAP).
An effort focused on establishing in-country cooperation will be necessary. Suchcooperation fulfils several ancillary but vital objectives: (a) it builds a process ofnational acceptance of the methods and results through active involvement;(b) it provides a mechanism for technology transfer and training for eventual
implementation of national inventories based on remote sensing; (c) it facilitateslogistical coordination of the field component; (d) it provides direct cooperation at
various foreign ground stations; and (e) it enables cooperation with national andregional experts in the interpretation of imagery.

To develop in-country collaboration, the programme should be linked to the emerging
network of governmental and non-governmental activities. At one level (nongovernmental), the programme could target activities that would contribute to the
START regional efforts, such as that in Southeast Asia through which several LUCC
projects/programmes have already been mounted; data collection efforts; and casestudies. At another level it could support and participate in the governmental
activities running parallel to START, such as the Asia Pacific Network (for Southeast
Asia), ENRICH (for Africa, Eastern Europe, and Central Asia), and Inter American
Institute (for North and South America). These networks are likely to be a goodconnection to an international consortium of funding from the USA, EU, and Japan.

100

Another approach would be to couple historical reconstruction of land-coverconversion derived from tabular documents with remote sensing. Tabular data,
national censuses, or historical documents in which data are reported geographically(e.g., by administrative district) could be mapped in a geographic information system.
Remote sensing provides direct observations of land-cover change, while historicalreconstruction generally relies on indirect estimation from changes in various humanuse categories. Nonetheless, the coupling of these two approaches provides a way to"calibrate" the historical assessment, since the historical trend should overlap withremotely sensed data - both in magnitude and space - during the years for which both
historical and remotely-sensed data exist.
This approach relies on the availability of historical documents such as revenue
records, gazetteers, land assessments, or forestry reports. In most cases, records of land

use or agricultural area are more readily available than records of vegetation and land
cover directly. Thus, estimates of land-cover change are indirectly derived from dataon changes in agricultural area. A baseline delineation of natural land cover isestablished, and these areas are reduced in proportion to the increase in agriculturalarea.

Changes in the area of cultivated land can be used to approximate land-coverconversion rates, since the most important form of land-cover conversion has
historically been agricultural expansion (Richards 1990, Tucker and Richards 1983).
This assumption is generally accurate, but it must be noted that in some instances theomission of logging and other non-agricultural causes of land-cover conversion could
be significant. Certain areas in the tropics, such as Ivory Coast, Nigeria, Malaysia, andThailand, have experienced large-scale losses of forest in this way (Lanly 1982, WRI
1990; 1994Y. This approach is necessarily limited in the absence of direct observations ofland cover. For instance, sparse sampling in space and time can result in a variety ofpossible time series in a single dataset, which may result in different histories of carbon
flux when the data is coupled to a numerical model (Houghton 1986). To reduce thistype of data aliasing, sampling at a finer temporal resolution would be required.
Also, data from the same source may vary considerably from year to year due tochanges in methodology or terminology. Time-series derived from later editions of
the FAO Production Yearbooks, an important source of this kind of data for recent
history, are different from the same time-series derived from earlier editions.
It must also be noted that historical reconstruction does not actually document land-

cover transformations, such as closed forest to woodland, due to human intervention.
Instead, they provide estimates of land-cover replacement by agriculture, or land-coverconversion. Moreover, land-cover conversion estimates obtained this way are basedon ne! c~anges in :he amount of agricultural land. Since they are based on net change
only, It IS not pOSSIble to know how much abandonment there is at any point in time.
For analyses of net fluxes of carbon, for instance, this could be important, since a large
amount of abandonment would result in lower net releases to the atmosphere.
Historical reconstructions use tabular data only. There is no inherent spatial organisation to the data. One way to develop digital maps of historical land-cover conversion
is to use geographic information systems (GIS). The GIS approach permits accurate
sl?atial representation of data on agricultural areas, which can then be merged withdIgItal maps of land cover to estimate conversion rates by land-cover type. It also
101

makes it possible to integrate a wide variety of other data, such as roads and otherhuman-use features, hydrology, soils, and the like, and to link historical data to remotesensing data.
There are several existing programmes upon which to build a land-cover change data
Integrating Activity. For example:•

NASA's Landsat Pathfinder Humid Tropical Forest Inventory Project (HTFIP) is ahigh resolution satellite remote sensing dataset being developed to provide "waUto-wall" coverage of the closed tropical forests of the world with Landsat MSS and
TM at three points in time from the 1970s to the mid 1990s.

•

The Commission of the European Communities TREES project is compiling a
1 km tropical forest dataset in an effort to map the global distribution of tropicalevergreen and seasonal forests. This dataset is being made available as raw dataand high-level products, such as GIS-based forest maps, in an information system.

•

•

•

•

NASA is developing an acquisition plan for a global series of test sites using
Landsat TM data. These data are to be used to calibrate global analyses from coarse
resolution data such as A \'HRR, and for development of site-specific models of
ecolOgical processes in places where detailed in situ measurements have been .
made in conjunction with the satellite acquisitions. In a related effort, NASA IS
also compiling the Landsat Global Change Catalogue, which is a worldwide
catalogue of Landsat data acquired in and outside the tropics for global change
research. The data are available to the global change commuruty at the cost of
reproduction.
The High Resolution Data Exchange Project is a joint project of the Committee on
Earth Observation Satellites (an international affiliation of space agencies) and
IGBP. This project is aimed at testing the utility of multi-sensor data acquisition
and a multi-agency international coordinated system of remote sensing
observations. It is building a dataset containing several hundred SPOT, MOS,
JERS-OPS, ERS-l, and IRS data at selected global change study sites around theworld.
Regional Activities have been initiated in recent years which could be coupled tothe programme outlined here for in-country work. Within .the IGB~ ~~stem fo~
Analysis, Research and Training (START), a number of reponal activlt1es focusmg
on the land-cover change question have begun. Most notable is. the Sout~eas:Asian regional activity which is directly linked to the EPA Pathfmder project mthat region, as well as the aforementioned IGBP-LUCC and High Resolution Data
Exchange projects. START/Southeast Asia has initiated a Land-Use and LandCover Change (LUCC) programme consisting of two components: (a) a complete
region-wide analysis of deforestation trends in the region, and (b) specific case .
studies established in four participating countries: Thailand, Malaysia, indoneSIa,
and the Philippines.
In particular reference to the question of biomass b:,rning data, th~ IGB.P-DIS 1 km
A VHRR data product could be a useful starting pomt for developmg blOmass
102burning maps globally. In addition, the Biomass Burning Experiment (BIBEX) of
the IGBP International Global Atmospheric Chemistry (IGAC) core project isdirectly relevant, as are various other programmes of the IGBP.
Integrating Activity 1.4. Land-use and land-use change mapping
As noted above, it is doubtful that a single land-use classification system, even if it ishierarchical, can serve the varied needs of the user community. This science/researchplan calls for two meanings - biophysical manipulation and intent/purpose - either
one of which requires very different kinds of data. The aim of this activity, therefore,should be identify the data needs for either meaning, including common measures,and direct the larger community to collect these data in systematic ways that permit
their flexible use.
Biophysical manipulation will require information on the techno-managerial inputs
and strategies for major kinds of land use. Some of these inputs or their attributes canbe detected from satellite imagery, such as the frequency of biomass burning in
swidden cultivation and pasture/grassland management, terracing, and paddy systems.
Most of the inputs cannot be observed in this manner and will require case-study
sampling. Such inputs include irrigation, fertiliser use, movement of livestock,pesticide use, and so forth.
Intent/purpose data links directly with the behaviour of the land manager, and save insome special cases, such as large-scale tree plantations or centre-pivot irrigation inwhich the spatial form can be matched rather uniformly with intent/purpose for
known regions, these data must be obtained from ground-based techniques andsources. The basic data needed relate to management aims as noted in the section
above on classification. Several efforts are underway to develop land-use
classifications and maps for the world.
1;'

Integrating Activity 1.5. Developing socio-economic datase!s
The human dimensions datasets have not been well defined by the social science
global change research community. At the earliest possible opportunity, it will benecessary to define the research requirements for data. This process shouid involve a
collaboration between the Human Dimensions Data and Information Systems Office(HDP-DIS) and the IGBP-DIS Office. A workshop following the open science meetingshould be the venue to engage the research community to define specific datasets; therole of the open meeting would be to define the science questions and specify topicalareas which will need supporting data. These will certainly include economic,
political/institutional, demographic, and policy data. Some of the obvious data are
population density, patterns and level of consumption, land tenure, functioning of themarket, and the like.
It is important to recognise here, however, that the data will be required at different
scales of resolution. Typically, economic data are collected at the level of the state or
country, while population data are collected at sub-country levels. For land-use
analysis, finer spatial resolution is preferable. Much political/institution and policy
data are systematically collected, but must be drawn from individual case studies in the
short run.
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It is also likely that to develop LUCC datasets there will be a large amount of overlap
and integration of social-science and physical-science datasets. For instance, analyses offorest regrowth offer new insights into the dynamics and implications of forest use.
Patterns of regrowth and the conversion of secondary forest back to agriculture reflect
important social processes. Regrowth may be the result of the abandonment of
pastures and agricultural plots, or the result of deliberate resource management
strategies. Simultaneous acquisition of the ~hysical and social variables a:>dmeasurements is necessary to understand thIs process. Another example IS that oflandscape fragmentation, where the degre~ of fragmentation is largely a function of theland-use patterns associated with different economic activities. The history of land
occupation can also be an important factor.·
One additional point must be made: satellite observations alone cannot explain thesocio-economic and political factors that are the cause of land-cover change, nor canthey identify the factors that influence regional trends or local dynamics. It is only
possible to address these iss~es by also using d~mog:aphic ce;'Sus data and othersources of relevant social SCIence data. The socIal sCIence varIables should be merged
spatially and temporally with the physical science data on land-cover change, alongwith other variables such as soil type, hydrography, kilometres of roads constructed,
and distance to markets.
Finally, there should be serious recognition of the useful role of field-based data. The
objective of field research would be to elicit infonnation fro,:" l?nd managers an.d.
other land-use decision makers in order to understand the mdlvldual-level deCISIon
processes that produce the land-use/ cover changes.

9. Integrating Activity 2: Scalar Dynamics

Introduction
Any analysis of land-use/ cover change must come to grips with scale issues because
the units of analysis and processes within them have scale-related properties,
including threshold effects. An integration of Foci 1, 2, and 3 as proposed in thisscience/research plan requires that LUCC dynamics found at the micro-scale be linked
to those at higher scales, ultimately in global models, and more generally that the units
and processes found operative at the various scales of analysis be linked in a rigorous
way that permits scalar coupling and decoupling. Integrative approaches among allthese research foci will be required to ensure the robustness of these linkages.
Integrating Activity 2.1. Developing a scalar framework
This Integrating Activity seeks to design a hierarchical typology of broad clusters
and/or specific driving forces of land-use/cover change according to the scales at which
they typically operate. It aims to provide guidelines for the kinds of causes expected forthe scale at which the question is posed or the analysis undertaken. Its analogue is thespace/time matrices developed for the physical dimensions of environmental change(McDowell, Webb and Bartlein 1990; Allen and Hoekstra 1990) as well as some of theproximate sources of change in general (Clark 1987).
An estimate of the grain and extent of scales is essential to define particular phenomena. Representing scale in a space/time matrix often portrays the range of scales
over which a phenomenon occurs (Clark 1985), but an alternate representation is toshow average grain and average extent for the phenomenon (Holling 1992). For
example, villages are made up of households, so village-level processes would range
from household size (grain) to village size (extent). The representation of scale differs~th the question: if gender roles were at issue, then the grain of the study would be
fmer than the household, but the extent could remain the same.
A key, therefore, is to develop a strategy of data development that allows the data to beaggregated on at least three different scales (real-world, empirical, and model; see
Section 3, Scalar Dynamics). Various data should be organised and matched as closely
as possible according to their spatial attributes. This matching may require theconstruction of artificial scales based on grid aggregations.
An objective method for the identification of scales must be developed in concert withFoci 1 and 2. Existing methods of scale identification (e.g., dominant frequencies
revealed by Fourier analysis for temporal scales, Andres et al. 1994; discontinuities infractal dimension for spatial scales, Krummel et al. 1987) should be extended andrefined, and new methods explored (e.g., univariate clump analysiS, Holling 1992).
Such methods should be applied consistently to available datasets, first to fineresolution, remotely-sensed data, and then to socio-economic data from Focus 3 andcase-study data from Focus 1.

104

105

ii

Scalar discontinuities can also be identified by the failure of prediction and extrapolation when extended spatially or temporally. For example, deforestation in the
Amazon basin could be predicted fairly accurately from 1978 to 1988 based on a simple
Markov model, but these predictions became inaccurate when extended past 1988,
because exogenous economic and political factors operating on different time scales
began to define a new period (Skole, personal communication). If unpredictability andsurprise characterise scale transitions, then measures of unpredictability or variancemight be used to mark critical thresholds and to define limits to extrapolation (Turner
et al. 1989).
A wealth of LUCC case studies at varying spatial and temporal scales have been
undertaken. Similarly, a large set of models of land-cover dynamics and a smaller setof models of land-use and land-cover conversion have been developed. Systematic
assessments of their data requirements and outcomes as they pertain to the issues ofspatial and temporal dynamics have been lacking, however, and should be undertakenwith the goal of deriving a trial space/time matrix for the human causes of LUCC.
A typology of driving forces must be developed and applied to the case study a~dmodelling literature. Three sets of scales should be addressed: those for real-world
mechanisms (Focus I), empirical measurements (Focus 2), and prognostic models(Focus 3).

a~d imJ?ortance, even at a single spatial and temporal scale, may show their effect ind~scontl~uous, non-lInear ways. Uncovering the coupling mechanisms withinhlerar<;lues of systems and processes and describing their strength over time isessential.
Complementing these mechanisms, the" confidence limits" in the structure and theoutputs of various models should be described, thus defining the conditions underwhich extrapolation is and is not appropriate. Traditional statistical confidence limits
place bounds on the certainty of estimation' and prediction. Here we seek the level ofth~t uncertainty as a functi?n of the strength of the mechanisms that couple hierarchIcal levels together. Making the evolution of thresholds and surprises truly
endogenous to the model is a longer-term goal.
Spatial heterogeneity in both land use and land cover may affect the outcome ofchan~es in driving forces in both the biophysical and social realm, but perhaps only at
certa~n ~cale:. Te~poral.heterogeneity in land use interacts with temporal hetero-genelty In bIOphysIcal dnvIng forces (for example, seasons) in a non-linear fashion.
Temporal heterogeneity in driving forces may be expected to affect the strategies ofland users in their adaptation to and mitigation of risk and uncertainty. The use ofvariance ra~her than means in models may capture some of the role of system
heterogeneIty, but further methods should be developed, applied, and refined.

Case studies of land use (Focus I) should be multi-scale in a given locale (Turner et al.,1989), where possible, and nested within regions of particular attention (as in Focus 2).
Thus linkages must be made from the household and high resolution «1 km) to theregion and from months to decades up and more. These linkages might be refined byexamining the results of Foci 1, 2, and 3.
Integrating Activity 2.2. Developing rules for crossing and linking spatial scales
Simply analysing data and modelling at multiple scales is a way of addressing scales
without crossing them; as such, cross-scale dynamics are treated as a black box. Simple
aggregation strategies which deserve attention may be treated as a methodological(observational) issue only. An overarching aim of the LUCC enterprise is to couple
qualitative models at the scale of case studies (from Focus I) with regional thematic
models (Focus 2) and to couple regional models of change with global models (Focus
3). This coupling and decoupling must adequately account for the processual dynamics
of the forcing functions found at each scale. For example, global agricultural markets
may operate as demand on a region's land use, but its path to land use may be filtered,augmented, or radically changed by regional resource institutions, politics, and othersuch factors. In turn, these regional factors cannot be situated independent of the
global market. Getting the scalar dynamic right, therefore, is central to improving
regional and global models. This observation can be extended to the sub-regional level
as it applies to the case studies of Focus 1.
Simple notions of hierarchy theory imply that broad-scale driving forces effectively
constrain smaller-scale, immediate variables which, in turn, affect higher hierarchicallevels as an average. If systems are vertically coupled but in a loose manner (Pattee
1973), then it makes sense to model scales separately. But when different hierarchies
are joined (as in the land-use/land-cover linkage), this sort of hierarchy may not apply.
In addition, land-use systems are evolutionary even on short time scales, so that
hierarchies are dynamic. Thus, constraining variables progressively in their weight
106

107

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122

123

Appendix 1

Appendix 2

ScienceIResearch Plan for
Land-Use and Land-Cover Change
Outline of Research Foci and Summary of Activities

LDCC Meetings and Participants

1. CPPCIRPPC-LUCC, Barcelona, Spain, May 13-15, 1993
Focus 1:Land-Use Dynamics - Comparative Case Study Analysis

Focus Activity 1.1
Focus Activity 1.2
Focus Activity 1.3
Focus Activity 1.4
Focus Activity 1.5
Focus 2:Developing a global sampling and study framework.
Id~ntification, description, and qualitative modelling of the role of key
dnVID& forces of land-use maintenance and change,
Assessmg the dynamics of change and stability in systems of land use

Detennining important Iand-cover changes and regions of consideration

Direct measurement of regional and global land cover and land use

Focus Activity 2.4

Direct observations of land-cover change dynamics
Analysing the spatial relations of land-cover change

Focus Activity 2.5
Focus Activity 2.6

Observing the proximate causes of Iand-cover change
Developing empirical diagnostic models

Focus 3:

Synopsis: The first meeting of the CPPC/RPPC LUCC considered the IGBP-HDP
mandate (Section 2) and developed an over arching conceptualisation of a LUCC
programme consistent with that mandate. The initial formulation ident~fie? a casestudy approach and an integrative-modelling approach for the LUCC objectives.

Analysing land-cover consequences

Theoretical work: model building and prediction

Land-Cover Dynamics - Direct Observation and Diagnostic Models

Focus Activity 2.1
Focus Activity 2.2
Focus Activity 2.3

Host: HOP Secretariat

Participants:
G. Fischer
L Fresco
D. Graetz
T. Kitamura
R. Leemans
L Martinelli
E. Milanova
R. Moss

D. Norse
M. Parry
C. Poole
S. Sanderson
D. Skole
B.L. Turner
1. Yanhua

Regional and Global Models - Framework for Integrative Assessments
2.

Focus Activity 3.1
Focus Activity 3.2
Focus Activity 3.3
Focus Activity 3.4
Focus Activity 3.5
Focus Activity 3.6

Exploring existing regional and global models projecting land use andland cover.
Creating a new structure for modelling land-use and land-cover change
Extending the horizontal linkages
Refining the vertical linkages
Introducing water into the land-use and land-cover change projections
Model validation and sensitivity analysis

Integrating Activity 1:

Data and Classification

Integrating Activity 1.1
Integrating Activity 1.2
Integrating Activity 1.3
Integrating Activity 1.4

Land-cover mapping

Integrating Activity 2:

Scalar Dynamics

Integrating Activity 2.1
Integrating Activity 2.2

Developing rules for crossing and linking spatial scales

Developing land-use and land-cover classification systems
Land-cover conversion mapping
Developing sodo-economic datasets

Developing a scalar framework

124

CPPORPPC-LUCC, New York, US, July 29-31, 1993

Host: Social Science Research Council
Synopsis: The committee and invited experts examine? .t~~ stren~th~ and weakI;essesof integrated regional and global models, and the pOSSIbIlities of Imkmg them .WIthdetailed case studies. The group conduded that issues involved in the modelll."g andthe linkages were sufficiently large that they required the developme~t of a senes ofbackground papers, to be reviewed in a workshop by experts engaged m bothmodelling and case-study approaches.
Participants:

D. Bromley
J. Bruinsma
J. Eddy
G. Fischer
1. Fresco
D. Graetz
T. Kitamura

R. Leemans
D. Major
1. Martinelli
E. Milanova
D. Norse
H. Okoth-Ogendo
M. Parry125

C. Padoch
1. Pritchard
C. Rosenzweig
S. Sanderson
D. Skole
B.L. Turner

3. LUCC Workshop, Woodstock, England, November 16-19, 1993
Host: Environmental Change Unit, University of Oxford
Synopsis: Some 25 experts on land-use/cover modelling and change from around theworld were invited to join members of the CPPC/RPPC LUCC to explore and identify
how integrative models could realistically be improved with regard to LUCC, and how
the case-study community and the modelling community might merge their research
efforts. In intensive break-out sessions, the participants worked on developing
research foci and their required basic activities. The workshop resulted in the
rudiments of Foci 1 and 3 and served to bring advocates of the case-study approach andthe modelling approach closer together. The CPPC/RPPC LUCC set the goal ofcompleting a full draft of a LUCC science/research plan to be reviewed at its next
meeting.

Participants:

5. Meeting on Land-Use and Land-,:over Change of the IGBP-H~: ~~~onalCommittee, National Science Councll-Japan, Kyoto, Japan, June ,Host: National Science Council, Japan.

Participants:

H. Brookfield
G. Clarke

G. Fischer
L. Fresco
D. Graetz
A. Gupta
J. Imbernon
J. Ingram
G. Leach
J.-P. Malingreau

M. Mortimore
R. Munton
D. Norse
H.W.O. Okoth-Ogendo
L. Olsson
M. Parry
P. Pingali
L. Pritchard
P. Richards
S. Sanderson

x. Singh
V. Stolbovoy
K. Strzepek
R. Suprapto
B.L. Turner
Y. Van Frausum
M. Williams
A. Young

4. CPPC/RPPC LUCC Mini-Workshop, Moriyama, Japan, June 16-18,1994
Hosts: Centre for Global Environmental Research, National Institute for theEnvironment, Japan; Laboratory for Regional Planning, Kyoto University; City of
Moriyama; IGBP-HDP National Committee, National Science Council, Japan
Synopsis: The committee and invited experts were asked to review the draft
science/research plan and propose changes. Foci 1 and 3 were fine-tuned and a third
focus (Focus 2) was added .. This addition recognised that a major approach tounderstanding LUCC is through direct observation of land-cover change dynamiCS,
primarily using remotely-sensed imagery, and that this approach is fully capable ofdeveloping empirical LUCC models of cover change. Focus 2, therefore, emerged as acomplement to Focus 1 and 3, bridging the use dynamics of the case-study approachwith the regional -global mOdelling approach. The CPPC/RPPC LUCC set as its next
goal the completion of a further draft of the science/research plan, to be vetted by thecommittee and various emerging complementary activities. Completion date for thedraft was set for October, after which the plan would be submitted to the IGBP-HDP in
the late Fall of 1994.

D. Skole
R. Suprapto
N. Swanberg
B.L. Turner
T. Veldkamp
E. Wiegandt

E. Milanova
K. Otsubo
M. Parry
L. Pri tchard
S. Sanderson
Y. Satoh

G. Fischer
Y. Himiyama
I. Kayane
T. Kitamura
R. Leemans
L. Martinellibf the CPPC/RPPC LUCC discussed the issues involved in~~~~~::!~l1::la~~-~se/ cover change and ho~ thes~ issues relate t~e p:Ob;~:: ofinterest to various Japanese efforts hunderb~.o~s~~~~~~e~~te~:~teri~s~o dateparticipants offered comments on t e pu IS e(e.g., IGBP Report No. 24/HDP Report No. 5).
Participants:
M. Akiyama
M. Araragi
Y. Ashinaga
A. Biloj. Chitose
G. Fischer
T. Fujii
M. Fukuhara
H. Harasawa
K. Hashimoto
H. Hlrata
y. Himiyama
S. Ikeda
K. Jitsu
R. KadaY. Kaida

H. Kaji
1. Kayane
M. Kimura
T. Kitamura
T. Kosaki
E. Milanova
K. Mizuno
Y. Murayama
M. NakanoS. Nishioka
K. Otsubo
R. Pritchard
R. Suprapto
D. Skole
S. Sanderson
Y. Sato

6. BP Workshop on Land-Use and Land-Cover Change, Bangkok, Thailand,
August 5-6, 1994
Host: Asian Institute of Technology.
'bl oordination between the
Synopsis: In a workshop held to dISCUSS POSSI e c .
. S utheast Asia and the
IGBP /START Land- Use and Land-Cover Change Project III 0 RPPC LUCC members
proposed IGBP-LUCC core project/research programn;~hCi~~c science/research plan,
representing Foci 1, 2, and 3 presented an overVIew 0
e
127

126

1. Seko
K. Takeuchi
T. Totokoro
H. Tsutsui
B. Turner
S. Uchida
T. Usui
T. Veldkamp
M. Yamamoto
K. Yamazaki
K. YanoM. Yazawa
M Yoshino
Y. YuiAppendix 3

and were given a review of current research projects in Southeast Asia which related
to LUCC research. It was agreed that START would cooperate with a future LUCC core
project/research programme.

IGBP Reports

Participants:
J.
G.
B.
Y.
K.
S.

Boonjawat
Fischer
Goh
Honda
Kajiwara
Lertlum

S. Murai
M.Omakupt
T. Pijakarcham
W.SalasS. Sanderson
R. Shibasaki

O. Siriratpiriya
D. Skole
R. Suprapto
M. Takagi
S. Vibulsresth

7. IGBP-DIS High Resolution Data Meeting, Paris, France, September 7-9, 1994
Host: CNES
Synopsis: Representatives of national space agencies and data providers met withrepresentatives of IGBP-DIS and the CPPC/RPPC LUCC to discuss the establishment ofpoliCies and procedures for obtaining remotely-sensed high resolution data, essential
for research described in Focus 2.
Participants:
P. Backlund
B. BertoIini
H.-J. BoIle
S. Gotoh
J.-P. Malingreau
Y. Muranaka

K. R S. Murthi
T. Phulpin
I. Rasool
A. Ratier
W.SalasD. Skole

W.Steffen
Y. Suga
J. Townshend
M. Usui
A. van de Griend

8. Land Use and Land Cover Project, International Institute of Applied Systems
Analysis, Laxenburg, Austria, October 24-25, 1994
Host IIASA
Synopsis: CPPC/RPPC LUCC members discussed the IIASA project with its Steering
Committee in terms of the kinds of understanding of land-use/ cover change that haveemerged from the CPPC/RPPC deliberations. Particularly emphasised were potential
parallels and contributions of IIASA to regional and global LUCC models as informedby comparative case studies. The HASA project focuses on mid- and high-latitude
Eurasia, particularly Russia and China.
Participants:
P. de Janosi
G. Fischer

J. Jagger
T. Kitamura

V. Kotlyakov
M. Parry
C. Rosenzweig
W. Tims

128

B.L. Turner
L. Yanhua

Reports marked with an * are no longer available.

No. 12The International Geosphere-Biosphere Programme: A Study of Global
Change (JGBP). The Initial Core Projects. (1990)

No. 13

Terrestrial Biosphere Perspective of the IGAC Project: Companion to the
Doolde Report. Edited by P.A. Matson and 0.5. Ojima. (1990)

No. 14

Coast Ocean F1uxes and Resources. Edited by P.M. Holligan. (1990)

No. 15Global Change System for Analysis, Research and Training (START).
Report of the BeIlagio Meeting. Edited by J.A. Eddy, T.F. Malone,
J.J. McCarthy and T. Rosswall. (1991)

No. 16

Report of the IGBP Regional Workshop for South America. (1991)

No. 17

Plant-Water Interactions in Large-Scale Hydrological ModeIling. (1991)

No.18.1

Recommendations of the Asian Workshop. Edited by RR Daniel. (1991)

No. 18.2* Proceedings of the Asian Workshop. Edited by RR Daniel and B. Babuji.
(1992)
No. 19 * The PAGES Project: Proposed Implementation Plans for Research Activities.
Edited by J.A. Eddy. (1992)
No. 20' Improved Global Data for Land Applications: A Proposal for a New High
Resolution Data Set. Report of the Land Cover working Group of IGBP-DIS.
Edited by J.R.G. Townshend. (1992)
No. 21

Global Change and Terrestrial Ecosystems: The Operational Plan.
Edited by W.L. Steffen, B.H. Walker, J.S.L Ingram and GW. Koch. (1992)

No. 22

Report from the START Regional Meeting for Southeast Asia. (1992)

No. 23

Joint Global Ocean Flux Study: Implementation Plan.
Published jointly with SCOR (1992)

No. 24

Relating Land Use and Global Land Cover Change. Edited by B.L. Turner H,
RH. Moss and D.L. Skole. Also HDP /Report No. 5. (1993)

No. 25Land-Ocean Interactions in the Coastal Zone: Science Plan.
Edited by P.M. Holligan and H. de Boois. (1993)
129No. 26

Appendix 4

Towards a Global Terrestrial Observing System (GTOS): detecting andmonitoring change in terrestrial ecosystems. (Report of Fontainbleau
Workshop). Edited by O.W. Heal, J.-e. Menaut and W.L. Steffen.
Also UNESCO/MAB Digest. (1993)

No. 27

Biospherics Aspects of the Hydrological Cycle: The Operational Plan. (1993)

No. 28IGBP In Action: Work Plan 1994 - 1998. (1994)

No. 29Africa and Global Change. Report from a Meeting at Niamey, Niger,
23-27 November, 1992. (1994)

No. 30IGBP Global Modelling and Data Activities 1994 -1998. (1994)

No. 31African Savannas and the Global Atmosphere: Research Agenda.
Edited by e. Justice, RJ. Scholes and P.G.H. Frost. (1994)

Acronyms and Abbreviations

AET
AGE
AGNPS
APN
AVHRR

No. 32

International Global Atmospheric Chemistry (IGAC) Project:
The Operational Plan. (1994)

No. 33Land-Ocean Interactions in the Coastal Zone: Implementation Plan.
Edited by J.e. Pemetta and J.D. Milliman. (1995)

No. 34

BAHC-IGAC-GCTE Science Task Team: Report of First Meeting. (1995)

No. 35Land-Use and Land-Cover Change (LUCC): Science/Research Plan.
B.L. Turner n, D. Skole, S. Sanderson, G. Fischer, L. Fresco and
R Leemans. (1995)

No. 36The IGBP Terrestrial Transects: Science Plan. Edited by G.W. Koch,
RJ. Scholes, W.L. Steffen, P.M. Vitousek and B.H. Walker. (1995)

BABC
BIBEX
CEC
CENTURYCEOS
CIESlNCPPCCREAMSDISECEENSOENRICH
EPA
EPIC
ERS-l
ESA
ESCAPEEU
FAO
FCCC
FLIPSIMFORENA
GAIM
GCTE
GEMS
GJS
GLASOD
GRID

GTOS·
HDP
HMSO

IDFIP
lA!

IBSNAT
ICSU
IGAC
IGBP
IIASA
lLO
IMAGE
IMF

lPCC
lRS

JSRlC
JSSC

130

Actual Evapotranspiration

Applied General Equilibrium
Agricultural Nonpoint Source Pollution Model
Asia-Pacific Network (START)Advanced Very High Resolution Radiometer
Biospheric Aspects of the Hydrological Cycle (IGBP)
Biomass Burning Experiment (IGAC)
Commission of the European Community

Not an acronym - simply indicative of the long time-scale of the modelCommittee on Earth Observations Satellites

Consortium for International Earth Science Information Network (USA)Core Project Planning Committee (IGBP)
Chemicals, Runoff and Erosion from Agricultural Management Systems
Data and Information System (IGBP)
United Nations Economic Commission Europe (UN)El Nino - Southern Oscillation

European Network for Research in Global Change (CEC)
Environmental Protection Administration
Erosion Productivity hnpact Calculator

European Space Agency Remote Sensing Satellite
European Space Agency
The Evaluation of Strategies to address Climate change by Adapting to andPreventing Errunissions
European Union
Food and Agriculture Organization (UN)
Framework Convention on Climate Change
Firm Level Income and Policy Simulator Model
Forests of Eastern North America
Global Analysis, Interpretation and Modelling (IGBP)
Global Change and Terrestrial Ecosystems (IGBP)
Global Environmental Monitoring System (UNEP)
Geographic Information System
Global Assessment of Soil Degradation (UNEP /lSRlC)
Global Resource Information Database (UNEP)
Global Terrestrial Observation System
Human Dimensions of Global Environmental Change Programme (ISSC)
Her Majesty's Stationary Office
Humid Tropical Forest Inventory ProjectInter-American Institute for Global Change Research (START)International Benchmark Sites Network for Technology Transfer
International Council of Scientific Unions
International Global Atmospheric Chemistry Project (IGBP)International Geosphere-Biosphere Programme (ICSU)International Institute for Applied Systems Analysis
International Labour Organisation (Geneva)
Integrated Model to Assess the Greenhouse EffectInternational Monetary Fund (Washington, D.e)
Intergovernmental Panel on Climate Change (WMO/UNEP)
Indian Remote Sensing Satellite
International Soil Reference and Infonnation Centre
International Social Science Council
131

!UCN
JERS-OPS
Landsat
LGSOWG
LOICZ
LUAM
LUCC
MAB
MOS
MRLC

MSS
NASA
NOAA

NPP
OECD
OIES
PAGES
PAT
RPPC
SAVANNASARCS
SARUM
SC-HDP
SC-IGBP
SOTER
SPOT
SSRC
START
SWAT
SWRRB
TFAP
TM
TREES
UCAR
UN
UNEP
UNESCO
UNFPA
USAID
USDA
USFS
USGS
WCIRP
WCMC
WCRP
WMO
WRI

International Union for the Conservation of Nature
Japanese Earth Resources Satellite - OPS Sensor
Land Remote-Sensing Satellite (USA)Landsat Ground Station Operators Working Group
Land-Ocean Interactions in the Coastal Zone (IGBP)
Land Use Allocation Model
Land-Use and Land-Cover Change (IGBP /HDP)
Man and the Biosphere Program (UNESCO)
Marine Observational Satellite (Japan)
lnteragency Multi-Resolution Land Cover Characterization
Multispectral Scanner System
National Aeronautics and Space Administration (USA)National Oceanic and Atmospheric Administration (USA)Net Primary Production
Organization for Economic Cooperation and Development
Office of Interdisciplinary Earth Studies
Past Global Changes (IGBP)
Population, Affluence, and Technology
Research Programme Planning Conunittee (HDP)

No acronym. A process-oriented model of pastoral ecosystems
Southeast Asia Regional Committee for START
Systems Analysis Research Unit Model
Steering Committee of the HDP.
Scientific Committee of the IGBP
Global and National Soils and Terrain Digital Database
Systeme pour l'Observation de la Terre (France)
Social Science Research Council (US)Global Change System for Analysis, Research and Training
Soil and Water Assessment Tool
Simulator for Water Resources in Rural Basins
Tropical Forest Action Plans
Thematic Mapper (satellite sensor)
Tropical Ecosystem Environment Observation by Satellite
University Corporation for Atmospheric Research
United Nations
United Nations Environment Programme
United Nations Educational, Scientific and Cultural Organization
United Nations Population Fund
United States Agency for International Development
United States Department of Agriculture
United States Forestry Service
United States Geological Survey
World Climate Impacts and Response Programme
World Conservation Monitoring Centre
World Oimate Research Programme (ICSU/WMO/IOC)
World Meteorological Organisation (UN)World Resources Institute132