Module 1.3 Assessing and analyzing drivers of
deforestation and forest degradation
Module developers:
Erika Romijn, Wageningen University
Martin Herold, Wageningen University
Country examples:
National analysis of drivers of
deforestation in
1. Democratic Republic of the
Congo
2. Indonesia
Photo credit: AFP
Module 1.3 Assessing and analyzing drivers of deforestation and forest degradation
REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF
V1, May 2015
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1. Democratic Republic of the Congo (DRC):
National analysis of drivers of deforestation
DRC is actively participating in REDD+ and performed a
national analysis of drivers of deforestation and forest
degradation that included:
 Qualitative assessments
● By civil society
● By UN Environment Programme (UNEP)
 Quantitative assessment
● By Université catholique de Louvain (UCL)
 Synthesis of all studies
Module 1.3 Assessing and analyzing drivers of deforestation and forest degradation
REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF
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Qualitative analysis by civil society
 Extensive literature review
 Interviews with four to seven experts per province, to list the
10 most important direct and indirect drivers per province
 Direct drivers consolidated at national level:
1. Slash-and-burn agriculture practiced by farmers
2. Local wood consumption
3. Charcoal and fuel wood / firewood
 Indirect drivers consolidated at national level:
1. Population growth
2. Poverty of local population (farmers)
3. Administrative deficit
Module 1.3 Assessing and analyzing drivers of deforestation and forest degradation
REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF
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Qualitative analysis by UNEP
 Selection of 40 deforestation sites: literature review, field
observations, and interviews with experts and different actors
 Direct drivers consolidated at national level:
1. Slash-and-burn agriculture
2. Charcoal production
3. Causes related to demographics and phenomena such
as wildfire
 Indirect drivers consolidated at national level:
1. Population fluctuation
2. Institutional aspects (successive wars)
3. Economic aspects (poverty, youth employment)
Module 1.3 Assessing and analyzing drivers of deforestation and forest degradation
REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF
4
Quantitative study on the relation between
direct activities and explanatory variables
 Object-based segmentation combined with
nonsupervised classification of Landsat satellite images
produced land cover maps for 1990, 2000, and 2005
 Analysis of land cover changes for 1990–2000 and
2000–2005
 Thirty-five explanatory variables were grouped into eight
categories of underlying causes: infrastructure,
agriculture, forest exploitation, economic factors,
transport axes, demographic factors, sociopolitical
factors, and biophysical factors
Module 1.3 Assessing and analyzing drivers of deforestation and forest degradation
REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF
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Quantitative study on the relation between
direct activities and explanatory variables
 Linking land-cover changes (deforestation and
degradation) to explanatory factors:
● Univariate statistical analysis to quantify the
influence of the different explanatory variables
during the two different time periods: 1990–2000
and 2000–2005
● Multivariate statistical analysis to create
explanatory models for combinations of underlying
causes of deforestation
Module 1.3 Assessing and analyzing drivers of deforestation and forest degradation
REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF
6
Direct drivers, explanatory factors, and
underlying causes of deforestation
1
2
3
Direct drivers
Slash-and-burn
agriculture
Local wood consumption
Explanatory variables
Biophysical factors:
degraded forests
Biophysical factors:
fragmentation
4
Charcoal and fuel wood / Agriculture: rural
firewood
complex
Mining
Transport roads
5
Bushfire
Indirect drivers
Population growth
Institutional aspects
(political decisions,
mismanagement,
civil wars)
Infrastructure and
urbanization
Economic aspects:
economic crisis,
unemployment,
poverty
Demographic factors:
population growth
Module 1.3 Assessing and analyzing drivers of deforestation and forest degradation
REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF
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2. Indonesia: Drivers of deforestation
analysis using national data
How to derive quantitative driver
information based on land cover maps?
Module 1.3 Assessing and analyzing drivers of deforestation and forest degradation
REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF
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Step 1. Starting point: time series
of land-cover maps
Module 1.3 Assessing and analyzing drivers of deforestation and forest degradation
REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF
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Land-cover classification
Primary forest
1 Primary upland forest
2 Primary mangrove forest
3 Primary swamp forest
Degraded forest
4 Secondary upland forest
5 Secondary mangrove forest
6 Secondary swamp forest
7 Forest plantation (i.e., Eucalypt, Acacia,
Teak)
8 Bushes / shrubland
9 Bushy swamp
Nonforest
10 Plantation (oil palm)
11 Savanna
12 Upland agriculture
13 Upland agriculture mixed
with bush
14 Rice field
15 Cultured fisheries / fishpond
16 Settlement / developed land
17 Transmigration
18 Open land
19 Mining / mines
20 Water body
21 Swamp
22 Airport
Using the FAO forest definition:
• Forest > 0.5 ha
• Tree canopy cover > 10%
• Tree height > 5m
• forest being the predominant land use in the area
Module 1.3 Assessing and analyzing drivers of deforestation and forest degradation
REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF
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Step 2. Map deforestation areas for
subsequent time periods
● Forest, defined following the FAO forest definition
● Deforestation, degradation, reforestation/regeneration:
degradation
Primary
Forest
Degraded
Forest
Nonforest
Classes
Module 1.3 Assessing and analyzing drivers of deforestation and forest degradation
REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF
Forest
Nonforest
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Deforestation and forest degradation in
Indonesia between 2000 and 2009
Module 1.3 Assessing and analyzing drivers of deforestation and forest degradation
REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF
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Step 3. Link deforested areas to postforest land use
Mapping direct drivers: land cover following deforestation
Postforest land use
Commercial agriculture
Subsistence agriculture
Urban and
Infrastructure
Mining
Aquaculture
Open land
Land cover class
Plantation (oil palm)
Upland agriculture
Rice field
Upland agriculture mixed with bush
Settlement / developed land
Transmigration
Airport / harbor
Mining / mines
Cultured fisheries / fish pond
Open land
Module 1.3 Assessing and analyzing drivers of deforestation and forest degradation
REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF
13
Drivers of deforestation 2000–2009:
Postforest land use per the FAO forest definition
Module 1.3 Assessing and analyzing drivers of deforestation and forest degradation
REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF
14
Step 4. Quantify the different drivers of
deforestation (for the time period 2000–2009)
Distribution of different drivers in terms of area change
Driver
Commercial
agriculture
Subsistence
agriculture
Urban and
infrastructure
Mining
Aquaculture
Open land
Area (km2)
19301.63
16398.55
252.18
769.72
1090.94
8788.51
Source: MOFOR 2011.
Module 1.3 Assessing and analyzing drivers of deforestation and forest degradation
REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF
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Step 5. Possibility of linking different
drivers to GHG emissions
 Reporting of carbon and other GHG emissions for each
driver is encouraged
 Following information required:
● Carbon density (emission factor) for each different
forest type, to quantify total emissions
(= area of deforestation X emission factor) (See
modules 2.3 and 2.5.)
● Additional emissions related to specific drivers,
these may occur after the deforestation and depend
on the type of driver
Module 1.3 Assessing and analyzing drivers of deforestation and forest degradation
REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF
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Recommended modules as follow up
 Module 2.1 to proceed with REDD+ measuring and monitoring
and focus on monitoring activity data for forests using remote
sensing
 Modules 3.1 to 3.3 to learn more about REDD+ assessment
and reporting
Module 1.3 Assessing and analyzing drivers of deforestation and forest degradation
REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF
17
References

Defourny, P., C. Delhage, J-P. Kibambe Lubamba. 2011. Analyse quantitative des causes de la
deforestation et de la degradation des forets en République Démocratique du Congo. Kinshasa: FAORDC Coordination nationale REDD N°UNJP/DRC /041/01/2009. http://www.unredd.org/Newsletter35/DRC_Drivers_of_Deforestation/tabid/105802/Default.aspx.

Mahonghol, Denis. 2012. Analyse qualitative des causes et agents de la déforestation et de la
dégradation des terres forestières dans une RDC post-conflit. Evaluation environnementale post-conflict
(EEPC). Kinshasa : Division Post-Conflit et Gestion des Désastres Programme Pays de la RDC.
http://www.un-redd.org/Newsletter35/DRC_Drivers_of_Deforestation/tabid/105802/Default.aspx.

MECNT (Ministère de l’Environnement, Conservation de la Nature et Tourisme). 2012a. Étude qualitative
sur les causes de la déforestation et de la dégradation des forêts en République Démocratique du
Congo. Kinshasa: Groupe de Travail Climat REDD. http://www.unredd.org/Newsletter35/DRC_Drivers_of_Deforestation/tabid/105802/Default.aspx.

MECNT. 2012b. Synthèse des études sur les causes de la déforestation et de la dégradation des forêts
en République Démocratique du Congo. Kinshasa. http://www.unredd.org/Newsletter35/DRC_Drivers_of_Deforestation/tabid/105802/Default.aspx.
Module 1.3 Assessing and analyzing drivers of deforestation and forest degradation
REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF
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
Ministry of Forestry (MOFOR), 2011. Digital Land Cover Map 2009. Ministry of Forestry, Jakarta,
Indonesia (unpublished).

Romijn E., J. H. Ainembabazi, A. Wijaya, M. Herold, A. Angelsen, L. Verchot, and D. Murdiyarso. 2013.
“Exploring Different Forest Definitions and Their Impact on developing REDD+ Reference Emission
Levels: A Case Study for Indonesia. Environmental Science and Policy 33: 246–259.
Module 1.3 Assessing and analyzing drivers of deforestation and forest degradation
REDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF
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