This roundtable discussion, first delivered in Jakarta, shares research into Indonesia's national deforestation estimate, with the objective of sharing approaches and ultimately improve the reliability of the estimate.

1. Recent Study on National Deforestation
Estimate
Roundtable Discussion UKP4
Jakarta, 3 July 2015
Arief Wijaya1, Lou Verchot1, Daniel Murdiyarso1, Martin
Herold2, Arild Angelsen3, Erika Romijn2 and John-Herbert
Ainembabazi3
1 Forest and Environment Programme, Center for International Forestry
Research (CIFOR), Bogor, Indonesia
2 Center for Geo-Information Science, Wageningen University, Wageningen,
The Netherlands
3 Department of Plants and Environmental Sciences, Norwegian University of
Life Sciences (UMB), Oslo, Norway

2. Purpose of the study
 Estimation of future carbon emissions from LULUCF sector
is yet challenging for Indonesia
 Opportunity: Indonesia has several spatially explicit
deforestation maps/estimates
 Objective of the talk: to share our approach to improve the
reliability of national deforestation estimate

3. Materials
 Land cover map of MOF (2000-2012)
 Annual deforestation map of University of Maryland (2000-2010)
 Land cover change map of CRISP (2000-2010)
 Stratified sample of land cover change map of EU-JRC (2000-2010)

4. Forest definitions
Source: Romijn, et.al, (2013)

5. Statistics of deforestation and forest
degradation
Source: Romijn, et.al, (2013)

6. Forest definitions matter!
Distribution of deforestation drivers in Indonesia from 2000 to 2009 based on analysis
of follow-up land cover/land use type

7. Comparison of deforestation estimate
0
100
200
300
400
500
600
700
800
900
1000
AnnualDeforestation(x1000ha)
Indonesia MOFOR Indonesia Hansen
Indonesia JRC Indonesia Mean

8. Validation of deforestation maps of Indonesia
Source: Wijaya, et.al, (In prep)

9. Deforestation data and forest definitions
Source Resolution
MMU
Forest definition
MOFOR
Official
(Landsat)
6.25 ha Vegetation with canopy cover of more than 30% with minimum area
of 0.25 ha and tree height above 5 meter. Plantation forests (e.g.
Acacia, Eucalyptus, Teak, etc.) are considered as a forest
MOFOR
FAO
(Landsat)
6.25 ha Forest is defined by the FAO as land spanning more than 0.5 ha with
more than 10% tree canopy cover and trees higher than 5 m (or
having the potential to reach a height of 5 m).
CRISP
(MODIS)
25 ha Not defined
Hansen
(Landsat)
0.09 ha
0.36 ha
Forest tree cover was defined as greater than 25% canopy cover and
change was measured without regard to forest land use. All tree cover
assemblages that met the 25% threshold, including intact forests,
plantations, and forest regrowth, were defined as forests.
EU-JRC
(Landsat)
5 ha More than 5 m height, forest prop. In polygon (FP)>70, canopy cover
(CC)>10

10. Semi-automatic classification and visual
observation? Or different forest definitions?
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
00-03 03-06 06-09 09-11 11-12
Annualgrossdeforestation/treecoverloss(km2)
Ministry of Forestry gross deforestation Hansen tree cover loss

11. Working definition of different maps
Source Minimum
Mapping Unit
(MMU)
Forest Definition Image Classification
Approach
Indonesian Ministry
of Forestry (MOF)
62,500 m2 Canopy cover > 30%, Total area > 0.25 ha, tree
height above 5 meter. Plantation forests (e.g.
Acacia, Eucalyptus, Teak, etc.) are included
Visual observation of
satellite images, polygon
based classification
Hansen, et.al. 900 m2 Canopy cover > 25%, change measured
disregard to forest land use. Tree cover
assemblages the 25% threshold, including
intact forests, plantations, and forest
regrowth, were defined as forests
Semi-automatic
approach, pixel based
classification

12. Observations so far…
 Forest definition matters
 Selection of minimum mapping unit is important to
determine the smallest size of deforested areas
 Different methods to classify satellite images may result in
different deforestation figures
 Uncertainty of pixel- vs polygon-based classification

13. Thank you!