Forest cover map of insular Southeast Asia at 1:5 500 000 : derived from SPOT-Vegetation satellite images.
Date: 2011-07-12
Institutions: Institute for Environment and Sustainability
Subjects: South-East Asia, cartography, forestry research, remote sensing, tropical forest

INSTITUTE FOR ENVIRONMENT AND SUSTAINABILITY 
Global Vegetation Monitoring Unit 

FOREST COVER MAP OF INSULAR 
SOUTHEAST ASIA AT 1:5 500 000 
derived from SPOT-VEGETATION satellite images 

H-J. Stibig, R. Beuchle and P. Janvier 

TREES 
TROPICAL ECOSYSTEM 
ENVIRONMENT OBSERVATIONS 
BY SATELLITES 

TREES Publications Series D: Thematic outputs n° 3 

2002 

EUR 20129 EN 

 
 
 
 
 
 
 
 
 
 
 
INSTITUTE FOR ENVIRONMENT AND SUSTAINABILITY 
Global Vegetation Monitoring Unit 

FOREST COVER MAP OF INSULAR 
SOUTHEAST ASIA AT 1:5 500 000 
derived from SPOT-VEGETATION satellite images 

prepared by 

Hans-Jürgen Stibig  
René Beuchle  
Pascale Janvier 

TREES 
TROPICAL ECOSYSTEM 
ENVIRONMENT OBSERVATIONS 
BY SATELLITES 

TREES Publications Series D: Thematic outputs n° 3 

2002 

EUR 20129 EN 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
LEGAL NOTICE 

Neither the European Commission nor any person 
acting on behalf of the Commission is responsible for the use  
which might be made of the following information 

EUR 20129 EN 
© European Communities, 2002 

Printed in Italy 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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Forest cover map of insular Southeast Asia at 1: 5 500 000 

III 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Foreword 

Pressures of many kinds continue to influence the status and conditions of tropical 
forest ecosystems worldwide. The combined impact of climatic end socio-political 
events has led to much change in the forest cover of Southeast Asia during this last 
decade.  In  large  parts  of  the  region,  the  repeated  occurrence  of  strong  El  Nino 
related droughts has created favourable conditions for wildfires and deforestation 
through burning. The continuing demand for forest land to be converted to other 
forms of production (such as estates and annual crops) and a growing market for 
wood  products  have  furthermore  created  conditions  where,  in  the  span  of  a  few 
years, large tracts of forests have been radically transformed.  

The present assessment reveals that parts of Southeast Asian forests have shown a 
rapid  response  to  external  pressure;  this  makes  it  more  critical  than  ever  to 
maintain  a  continuous  watch  on  the  evolution  of  forest  cover  at  various 
geographical  scales.  The  TREES  project  has  maintained  such  a  system  of 
observation  and  analysis  to  provide  regularly  updated  information  on  forest 
conditions  at  regional  scale.  The  present  booklet  is  part  of  a  series  that  deals 
separately  with  the  tropical  forest  cover  of  the  three  tropical  regions  (South 
America, Africa and Southeast Asia). Through time the project has refined its use 
of remote sensing data, its capacity for validation of the interpretation through the 
use  of  several  data  sources  and  local  networks  of  experts,  and  its  overall 
management of the information collected in the process. The map inserted herein 
must therefore be considered as one layer of an information system underpinning 
the global monitoring exercise.  

The production of any forest cover assessment always leads to new questions with 
respect to the situation portrayed through a map. It is hoped that the quality of the 
analysis which has led to the present assessment will help the readers and experts 
to better evaluate the Southeast Asian situation and to raise new and more pertinent 
questions  related  to  the  future  of  the  ecosystems  described  here.  Relying  on 
adequate  and  relevant  information  is  indeed  a  key  to  the  development  of 
sustainable management practices. The tropical forests of the world are important 
for mankind; in many regions they are seriously threatened.  Monitoring them is 
more than ever a duty.  

Jean-Paul Malingreau, 
Science Strategy Directorate,  
JRC, European Commission 

Forest cover map of insular Southeast Asia at 1: 5 500 000 

IV 

 
 
 
 
 
 
 
 
Table of contents 

An overview of the TREES project ...................................................................... 1 
TREES ........................................................................................................... 1 
TREES II........................................................................................................ 2 

The TREES forest cover map of insular Southeast Asia - characteristics and 
objectives ............................................................................................................ 3 
The mapping method ........................................................................................... 4 
Validation ........................................................................................................... 5 
The TREES legend.............................................................................................. 6 
‘Evergreen montane forest’ ............................................................................. 6 
‘Evergreen lowland forest’ .............................................................................. 6 
‘Mangrove forest’ and ‘Swamp forest’ ............................................................ 7 
‘Thickets, shrubs, grassland and cultivation of perennial crops’........................ 7 
‘Cropland’ ...................................................................................................... 7 
‘Burnt vegetation / Dry vegetation / Sparse vegetation’.................................... 8 
‘Water’ ........................................................................................................... 8 
‘Forests burnt in 1998 with damage 25%-80%’................................................ 8 

Potential for estimating forest area and for forest cover monitoring....................... 9 
Map production ................................................................................................. 12 
GIS data layers used...................................................................................... 12 
Protected areas.............................................................................................. 12 

Acknowledgements ........................................................................................... 13 
References......................................................................................................... 14 
Annex 1: ........................................................................................................... 17 

Forest cover map of insular Southeast Asia at 1: 5 500 000 

V 

 
 
 
An overview of the TREES project 
During the last four decades forests faced severe depletion throughout the tropical 
belt. Today tropical forest ecosystems and their biodiversity are widely threatened. 
This was caused by the demands of an increasing population for land and goods, 
by the commercial over-exploitation of the resource ‘forest’, but also by misguided 
forest  and  land  use  policies.  Though  the  negative  impact  of  deforestation  on  the 
overall environmental conditions, on the socio-economic situation of many tropical 
countries and ultimately on the regional and global climate has become obvious, 
the process of deforestation and degradation is still going on.  

Continuous  monitoring  of  tropical  forest  cover  at  regional  and  global  scale  has 
been called for since the 70’s. This is not only in order to obtain a global picture of 
the remaining forest resources but also for better understanding and addressing the 
overall impact of deforestation in the tropics in a larger geographical context. The 
continuous provision of forest resource information at regional and global level is 
important for maintaining the awareness of the international scientific community 
but also as input to international organizations for formulating appropriate forest 
and conservation policies. The European Union gives significant financial support 
for  the  conservation  and  sustainable  management  of  tropical  forests  each  year 
(Shepherd et al. 1998). In such a context the provision of timely and sufficiently 
accurate  data  on  the  tropical  forest  extent  and  its  changes  has  to  be  seen  in  the 
appropriate dimension of importance. 

The TREES project has been set up to help develop techniques for global tropical 
forest cover assessment and for monitoring deforestation using satellite imagery. 

TREES  

The Joint Research Centre of the European Commission initiated a project called 
‘TRopical  Ecosystem  Environment  observations  by  Satellite’  (TREES)  in  1991 
with  the  objective  of  developing  a  system  for  global  monitoring  of  the  extent, 
condition and dynamics of forest cover throughout the moist tropical forest belt.  

The main tasks under the first phase of TREES were:  
- 

to  provide  a  global  tropical  forest  cover  assessment  from  satellite  sensors  of 
coarse spatial resolution; 
to ‘calibrate’ those measurements at local scales based on satellite images of 
higher spatial resolution;  
to  develop  an  information  system,  the  Tropical  Forest  Information  System 
(TFIS), capable of ingesting different types of spatially referenced data and of 
analysing and reporting on the dynamics of tropical forest cover. 

- 

- 

Forest cover map of insular Southeast Asia at 1: 5 500 000 

 1

 
 
 
 
 
 
 
The  first  stage  of  the  TREES  project  was  to  collect  and  process  a  pan-tropical 
satellite data set in order to produce a ‘wall-to-wall’ forest cover map of the humid 
tropical  forest  domain.  This  task  was  completed  in  1993  using  data  from  the 
NOAA  Advanced  Very  High  Resolution  (AVHRR)  sensor  (Malingreau  et  al. 
1995). These maps were validated and calibrated based on a sample of high spatial 
resolution  Landsat  Thematic  Mapper  (TM)  satellite  images  which  were  spread 
across the tropics – a process which enabled the project to furnish statistics on the 
extent  of  forest  cover  in  the  humid  tropics  (Mayaux  et  al.  1998).  Large-scale 
mosaics of ERS-1 SAR (Synthetic Aperture Radar) satellite images were compiled 
for  supporting  mapping  of  specific  forest  types  at  regional  scale  in  Africa  (De 
Grandi et al. 2000). 

TREES II 

TREES  II  (1996-2000)  aimed  at  the  development  of  a  prototype  system  for  the 
operational monitoring of the tropical forest ecosystem.  

The multi-sensor remote sensing approach combined ‘wall-to-wall’ assessment of 
forest  cover  from  satellite  images  of  coarse  spatial  resolution  with  the 
measurement  of  forest  cover  change  during  the  period  1990-1997  from  pairs  of 
satellite images of higher spatial resolution.  

On  the  coarse  resolution  side,  regional  forest  cover  maps  were  produced  for  the 
tropical areas of central Africa and Latin America (Mayaux et al. 1997, Eva et al.  
1999).  The  range  of  satellite  data  used  for  regional  forest  cover  mapping  has 
extended  since  then  from  the  AVHRR  images  to  new  ATSR  (Along  Track 
Scanning Radiometer) and SPOT4-VEGETATION images. These sensors provide 
a  significant  improvement  in  terms  of  their  spectral,  spatial  and  geometric 
qualities, thus resulting in higher mapping accuracy. 

The forest cover change assessment was based on a statistically selected sample of 
more  than  100  study  sites  spread  across  the  moist  tropical  belt.  A  stratification 
procedure was applied making use of the TREES regional forest cover maps and of 
information  on  areas  of  rapid  forest  change,  which  was  compiled  as  a 
‘Deforestation Hot Spot’ layer from regional expertise (Achard et al. 1998). As a 
result the majority of the sample could be focused on fast changing forested areas 
(Richards et al. 2000). Forest cover change was measured within the sample units 
from Landsat TM or SPOT satellite images by a number of co-operating regional 
and national forest research institutions in all three continents. 

Extensive databases were compiled for selected sites across the tropics and stored 
in the TFIS so as to carry out local deforestation case studies.  

Forest cover map of insular Southeast Asia at 1: 5 500 000 

 2

 
 
 
 
 
 
 
 
The TREES forest cover map of insular Southeast 
Asia - characteristics and objectives 
The TREES forest cover map of insular Southeast Asia documents the extent and 
spatial distribution of tropical forest cover of the sub-region at the beginning of the 
new  millennium.  The  map  covers  the  tropical  countries  of Malaysia, Singapore, 
Indonesia, Brunei, the Philippines and Papua New Guinea. 

The  mapping  approach  was  based  on  the  capabilities  of  recent  satellite  sensor 
technology  of  coarse  spatial  resolution.  The  map  reflects  therefore  in  terms  of 
thematic  and  spatial  accuracy  the  possibilities  of  forest  cover  classification  from 
these  satellite  images.  The  definition  of  forest  and  land  cover  classes  is  mainly 
confined to the information obtainable from these sensors rather than to terrestrial 
forest inventory data.  

The objective of the map is to provide   

- 

- 

- 

an  up–to–date  view  on  forest  cover  of  the  sub-region,  uniform  and 
compatible across country boundaries, 
a higher spatial accuracy and precision than many existing conventional 
maps at regional scales, 
a  reference  for  monitoring  and  documenting  large  and  long-term forest 
cover changes at sub-regional scale. 

It  is  hoped  that  the  TREES  forest  cover  map  can  provide  a  baseline  reference, 
useful as input for forest policies and strategies at the sub-regional level. The map 
could serve as a starting point for further stratification and for focusing on areas of 
particular  interest.  Depending  on  the  application  and  accuracy  requirements  the 
map  could  provide  valuable  input  also  at  national  scales.  However,  the  map  is 
neither  expected  to  meet  the  accuracy  and  information  needs  required  for  local 
forest  management  or  planning  nor  to  replace  detailed  forest  mapping  at  local 
scales. 

In the past, consistent mapping of forest cover from satellite images proved to be 
almost impossible in insular Southeast Asia due to the persistent presence of clouds 
and  haze.  The  operational  provision  of  almost  daily  SPOT4-VEGETATION 
satellite-images  offered  new  possibilities  for  mapping  forest  cover  in  this  sub-
region. Even so, it was only by using image acquisitions from more than two years 
that  an  acceptable  baseline  mosaic  could  be  created.  The  quality  of  the  satellite 
image mosaic was judged to be satisfactory for forest cover mapping for the vast 
majority  of  the  sub  region.  For  a  few  parts of limited area extent in the Western 
and Gulf provinces of Papua New Guinea the impact of remaining haze and cloud 
shadow  could  not  be  fully  assessed  and  may  have  resulted  in  a  decrease  of  the 
mapping quality. 

Forest cover map of insular Southeast Asia at 1: 5 500 000 

 3

 
 
 
 
  
The  map  is  available  in  digital  format  and  can  be  readily  integrated  into 
Geographic Information Systems and easily updated with new information coming 
from different sensors. 

The mapping method 
The images used were recorded from the ‘VEGETATION’ sensor on the SPOT 4 
satellite.  The  VEGETATION  sensor  delivers  acquisitions  with  a  swath  width  of 
2200km and a spatial resolution of about one kilometre. The four reflective bands 
are located in the blue  (0.43µm  - 0.47µm), the red (0.61µm  - 0.68µm), the near -
infrared (NIR, 0.78µm  - 0.89µm) and in the short-wave infrared (SWIR, 1.58µm - 
1.75µm) range of the spectrum (VEGETATION User Guide 1998). 

- 

The main advantages of these satellite images are:  
-  Daily  acquisitions  are  available  for  the  whole  continent  of  Southeast  Asia 
offering  improved  spectral,  spatial  and  geometrical  qualities  compared  to 
former coarse resolution satellite images. 
Standard  10-day  (S10)  composites  are  delivered  in  an  operational  way, 
combining  ten  subsequent  daily  images  in  one  mosaic.  The  pixels  of  these 
composites are selected from the daily images by the maximum value of the 
Normalized Difference Vegetation Index (NDVI) found during ten days. This 
standard  procedure  minimizes already to a certain extent the impact of haze 
and clouds. Using S10 products instead of the daily images allows handling of 
a  series  of  data  sets  of  an  extended  time  period  at  affordable  effort.  This 
proved to be a prerequisite for extracting reasonably cloud and haze free pixels 
in the cloud contaminated region of insular Southeast Asia.  

The  approach  chosen  made  use  of  all  S10  composites  from  April  to  September 
1998, from March to November 1999 and for few still haze-influenced spots also 
from January to March 2000 (Stibig et al. 2001).  A ‘haze and cloud free’ image 
mosaic  was  established  by  first  thresholding  the  ‘blue’  and  the  ‘SWIR’  bands  of 
the  S10  composites.  Monthly  mosaics  where  then  created  selecting  pixels  by  the 
minimum  values  in  the  SWIR.  Annual  and  bi-annual  mosaics  were  produced  by 
pixel  selection  from  the  monthly  composites  by  the  minimum  value  in  the  near-
infrared band (NIR). Remaining cloud-shadow pixels were filtered using digitally 
produced masks for the monthly and annual products for all areas with elevations 
below 1000 meters. 

Selecting the pixels for the annual mosaics by the minimum in the near infrared 
band would give preference to dry and leafless stages of any seasonal vegetation 
present.  Stages  of  bare  soil  occurring  in  the  context of agricultural management 
would be selected and areas burnt during the observation period would be retained 

Forest cover map of insular Southeast Asia at 1: 5 500 000 

 4

 
 
 
 
 
  
 
as such. The approach appeared to be feasible for extracting evergreen forest cover, 
which  represents  the  vast  majority  of  the  forests  in  the  sub-region,  however  also 
the few moist monsoon forests present could be captured.  

The vegetation cover classes were mapped by digital classification (unsupervised 
clustering and maximum likelihood algorithm) creating 61 initial spectral clusters 
that were labelled and then re-grouped to ultimately eight thematic classes (Stibig 
et al., submitted).  

Grouping to the final classes was supported by the use of two stratification layers. 

(1) The Global Digital Elevation Model GTOPO30 of the United States Geological 

Survey (USGS) was used for 
-  the application of cloud-shadow masks  
-  the definition of an elevation threshold for mountain forests (>1000m), and 
-  for the correction of ‘forest’ pixels misclassified as ‘water’ in shadowed parts 

of high mountains (slope > 0º).   

 (2)  The  forest  map  of  the  World  Conservation  Monitoring  Centre  (WCMC) 
(Iremonger  et  al.  1997)  served  for  improving  the  mapping  consistency  of 
mangrove  and  swamp  forests  by  assigning  ‘forest’  pixels  to  these  subclasses  if 
indicated as such on the WCMC map. 

Isolated, single pixels were removed in the final product by simple spatial filtering. 
The application of a 3 by 3 majority filter would, at the pixel level, compensate to a 
certain extent for the remaining artefacts caused by cloud shadow, as far as these 
artefacts were retained due to the mosaic procedure applied. 

Validation 
The  map  has  been  validated  by  comparing  to  mapping  results  obtained  from 
conventional Landsat TM satellite images of a spatial resolution of 30 meters and 
at  a  scale  of  approximately  1:100  000  (Stibig  et  al.,  submitted).  These  data  sets 
were  available  for  19  sites  distributed  over  insular  Southeast  Asia.  Ten  data  sets 
correspond to full TM frames (~185km x 180km), the remaining nine to quarter 
TM frames (~90km x 90 km). The satellite images have been acquired close to the 
year 1997. Landsat TM images are used widely for conventional forest mapping in 
the countries covered and form therefore a valid base of reference. 

The  correlation  for  the  forest  cover  estimates  for  the  19  sites  proved  to  be  very 
high  with a  r2  of 0.96.  The  total area of the sample amounted to more than 255 
thousand  square  kilometres.  For  the  whole  sample  forest  cover  was  estimated  at 

Forest cover map of insular Southeast Asia at 1: 5 500 000 

 5

 
 
 
 
 
 
 
 
 
 
60% from the present TREES map (1km spatial resolution) and at 62% from the 
Landsat TM data sets (30 m spatial resolution), resulting in a discrepancy in forest 
cover of only two percent. 

The TREES legend 
‘Evergreen montane forest’ 

Evergreen montane forests were mapped at elevations of more than 1000 meters.  
Montane tropical forests differ from the lowland forests in species composition and 
are characterized also by a lower canopy height, smaller crowns and smaller stem 
diameters  with  increasing  elevation.  The  composition  includes  for  example 
deciduous  trees  as  of  the  genus  Nothofagus,  Lithocarpus  and  Castanopsis  and 
coniferous 
the  genus  Araucaria,  Papuacedrus,  Phyllocladus, 
Dacrycarpus or Podocarpus (Saunders 1993). Endemic occurrences of pine stands 
(Pinus kesiya and Pinus merkusii) can be found for example in the montane forests 
of Sumatra and the Philippines (Whitmore 1984a). 

trees  as  of 

On non sun-exposed slopes the spectral signature of this class was partly affected 
by mountain shadow. Most of these spectral clusters could be recognized as forest. 
For  some  parts  of  steep  slopes  where  shadow  was  dominating  the  cover  was 
assumed to be ‘montane forest’ as well. 

‘Evergreen lowland forest’  

Evergreen lowland forests were mapped at elevations below 1000 meters. The vast 
majority  of  these  forests  are  dominated  by  species  of  the  Dipterocarp  family, 
containing  most  valuable  species  for  example  of  the  genus  Shorea  ,  Hopea  , 
Parashorea  ,  Pentacme  and  Dipterocarpus.  The  lowland  forests  also  contain 
extensive areas of heath forests, particularly on Borneo, with characteristic species 
such as of the genus Aghatis or Tristania. Closed forest plantations, e.g. of Acacia 
magnium are included as well.  

The few seasonal monsoon forests in the south of Sulawesi and Papua New Guinea 
and in the western part of the Philippines were not mapped separately but are also 
included  in  this  class.  These  forests  display  neither  strong  seasonality  nor 
significant  spectral  difference  on  the  image  mosaic  used.  Seasonal  forests  were 
reported  to  have  undergone  more  serious  depletion  in  the  past  than  evergreen 
forests and may now often be in the transition to woodlands or mosaics of forest 
and  non-forest  (Whitmore  1984b).  Particularly  in  the  far  south  of  Papua  New 

Forest cover map of insular Southeast Asia at 1: 5 500 000 

 6

 
 
 
 
 
 
 
 
Guinea  some  dry  deciduous  forest  formations  may  be  included  in  the  non-forest 
vegetation classes. 

‘Mangrove forest’ and ‘Swamp forest’ 

The mangrove forests are located along the coastlines and the estuaries of rivers. 
Typical tree species are of the genus Sonneratia, Rhizophora and Bruguiera while 
Nipa  palms  can  be  found  further  upstream  along  the  riverbanks.  The  mangrove 
forests  suffered  major  depletion  within  the  last  decades  and  many  of  them  are 
heavily degraded. 

The class ‘swamp forest’ contains peat swamp and fresh water swamp forests.  
Peat  swamp  forests  grow  on  a  peat  layer  between  0.5  and  20  meters  thick  and 
cover large areas along the coastline of Sumatra and Borneo. Characterized by a 
typical  concentric  zoning,  the  outer  fringe  is  similar  to  the  surrounding  lowland 
Dipterocarp  forests,  the  intermediate  zone  could  be  dominated  by Shorea  albida 
while the inner zone is usually covered by stunted trees (Lambrecht 1989).  
Extensive areas of fresh water swamp forests can be found in the lowlands of New 
Guinea and are described as ‘a very diverse assemblage of forest types flooded by 
river water’ (Whitmore 1990).  

Though  substantial  parts  of  the  mangrove  and  swamp  forests  could  be  mapped 
based  on  the  spectral  properties,  the  image  mosaic  did  not  allow  a  consistent 
distinction either between these types  or from the other lowland forests across the 
sub-region. Mapping was therefore improved by the support of the WCMC forest 
cover  map  as  a  stratification  layer:  as  ‘forest’  classified  pixels  were  assigned  to 
‘mangrove  forest’  or  ‘swamp  forest’  respectively  in  the  case  of  coincidence with 
these classes on the WCMC map.  

‘Thickets, shrubs, grassland and cultivation of perennial crops’  

The  class  contains  all  non-forest vegetation cover with a more or less evergreen 
appearance  during  the  two  years  of  observation.  This  may  include  natural 
vegetation  cover  but  also  mature  plantations  of  coconut,  oil  palm  or  rubber.  The 
class may contain some forest remnants as well.  

‘Cropland’ 

The class ‘cropland ’ describes more intensively cultivated areas. Parts of this class 
display  stages  of  bare  soil.  Tree  crop  plantations  may  be  included  when  in  the 
phase of ground preparation or in premature stages. 

Forest cover map of insular Southeast Asia at 1: 5 500 000 

 7

 
 
 
 
 
 
 
 
 
 
‘Burnt vegetation / Dry vegetation / Sparse vegetation’ 

On Sumatra and Borneo this mixed class represents mostly burnt vegetation cover 
and was therefore considered important to retain as a separate category. Included 
are the formerly forested areas burnt during the fires in 1997 and 1998, however 
the spectral information alone was not sufficient for concluding on the presence of 
still standing but damaged or dead tree cover. 

The class also contains dry stages of vegetation, such as for example of grassland 
or cereal crops after harvesting.  

Finally, this class comprises also areas covered by sparse vegetation, such as alpine 
grassland or sparsely vegetated rocks at higher elevations of Irian Jaya and Papua 
New Guinea.  

‘Water’  

Ocean  and  inland  water  bodies  were  classified  from  the  SPOT-VEGETATION 
mosaic and supplemented by the ArcWorld 1:3 M data set. 

‘Forests burnt in 1998 with damage 25%-80%’ 

The information on damaged but still standing forest biomass in the burnt areas of 
Eastern  Kalimantan  was  extracted  from  an  external  data  set  obtained  from  the 
Indonesian-German  ‘Integrated  Forest  Fire  Management  and  Sustainable  Forest 
Management Promotion’ project on Kalimantan (Hoffmann et al. 1999). This data 
set  contained  a  pre-fire forest cover map and a fire damage map. The additional 
layer created should indicate areas where some forest remnants can still be found. 
The  damage  class  displayed  relates  to  the  estimated  proportion  of  dead  trees, 
ranging from 25 to 80 percent. However, for a major part of these areas the damage 
was estimated to be at the high end of the range, between 50 and 80 percent.  

Forest cover map of insular Southeast Asia at 1: 5 500 000 

 8

 
 
 
 
 
 
 
Potential for estimating forest area and for forest 
cover monitoring 
The  map  reflects  in  terms  of  spatial  accuracy  the  possibilities  of  forest  cover 
classification  from  SPOT4-VEGETATION  coarse  resolution  satellite  images. 
Forest  area  figures  derived  from  this  data  set  are  therefore  considered  to  be 
baseline estimates aiming mainly at the sub-regional level.  

The following aspects need to be taken into account: 

- 

- 

Forest cover estimates from this map refer to the actual ‘forest cover’, not to 
‘forest land’. 
Forest  cover  on  this  map  includes  stages  of  degraded  forests  and  partly  also 
stages  of  forest  regrowth,  resulting  in  a  tendency  to  rather  overestimate  the 
area of ‘intact’ forest cover. 

-  Mapping discrepancies at the local level can be caused by the coarse spatial 
resolution of 1km by 1 km, where a ‘forest’ pixel may include a ‘non-forest’ 
proportion  or  vice  versa.  This  may  become  noticeable  for  areas  with  small 
forest blocks and fragmented forests.  
It can be expected that the spectral signal used as the basis for distinguishing 
vegetation  cover  classes  did  not  always  permit  a  highly  accurate 
differentiation of forest and non-forest cover in cases of gradual transitions or 
when the reflectance in hilly terrain was affected by shadow. 

- 

These  aspects  need  to  be  taken  into  consideration  particularly  for  applications at 
local and national scales. 

The  potential  of  the  data  set  is  seen  primarily  in  obtaining  an  up-to-date  and 
uniform  forest  cover  estimate  at  the  sub-regional  level.  At  this  level  forest  area 
estimates compare quite well with existing figures compiled by FAO (2001) from 
the countries: the difference for the sub-region is less than one percent.  

Forest area estimates at sub-regional scale 

VGT 2000 
million 
hectares 

FAO 2000 
million 
hectares 

Difference 

million 
hectares 

%** 

Insular 
Southeast Asia* 

162,0 

161,6 

0,4 

0.3 

*    including  Papua New Guinea 
** difference in relation to the FAO Forest Resources Assessment 2000 

Forest cover map of insular Southeast Asia at 1: 5 500 000 

 9

 
 
 
 
 
 
 
 
 
 
The present forest cover map offers furthermore a possibility for documenting and 
monitoring  long-term  forest  cover  change  in  the  sub-regional  context  when 
referring to historical maps.  

The  magnitude  of  the  forest  change  on  Sumatra  and  Borneo  is  apparent  when 
comparing  the  forest  distribution  in  the  middle  of  the  1980’s  (Iremonger  et  al. 
1997)  to  the  forest  extent  on  the  TREES  map  at  the  beginning  of  the  new 
millennium  (see  next  page).  The  change  was  caused  over  the  years  by  a 
combination  of  various  and  still  ongoing  deforestation  processes,  including  for 
example (a) the over-exploitation of the forest resource for timber, plywood, pulp 
and paper, (b) the forest conversion to rubber and oil palm plantations, (c) trans-
migration and (d) agricultural expansion.  

In  addition,  the  magnitude  of  single,  large-area  change  events  can  be  fully 
perceived when displayed in the larger geographical context. The fires in Indonesia 
in 1997 and 1998 (UNCHS 2000) have left their footprints particularly in eastern 
Kalimantan,  where  apart  from  the  ongoing  deforestation  processes  about  3.6 
million hectares of forest were destroyed by the extensive fires in 1998 (Hoffmann 
et al. 1999, Siegert et al. 2001).  

Forest cover map of insular Southeast Asia at 1: 5 500 000 

 10

 
 
 
 
Forest cover change on Sumatra and Borneo 

WCMC: Status in the middle of the 1980’s 

 TREES: Status in the beginning of 2000  

Forest cover map of insular Southeast Asia at 1: 5 500 000 

 11

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Map production 
The mapping scale of 1:5 500 000 was determined by the methods adopted (low 
resolution  satellite  data  analysis)  and  by  the  technicalities  of  regional  map 
presentation.  The  paper  map  is  presented  in  a  Mercator  projection  using  the 
WGS84 spheroid, with the central meridian at 100 degrees eastern longitude and a 
latitude of true scale on the equator.  

GIS data layers used 

The  GTOPO30  Global  Terrain  Model  of  the  United  States  Geological  Survey 
(USGS  1996)  and  the  forest  cover  map  of  the  World  Conservation  Monitoring 
Centre  (Iremonger  et  al.  1997)  were  used  as  stratification layers for introducing 
elevation thresholds and for assigning ‘forest’ pixels to forest sub classes.  

The data set provided by the Indonesian-German IFFM/SFMP (Integrated Forest 
Fire  Management  /  Promotion  of  Sustainable  Forest  Management)  technical 
cooperation project (Hoffman et al. 1999) on burnt forests in Eastern Kalimantan 
was used for the display of some remaining but heavily damaged tree cover. 

Roads and international boundaries were derived from the ESRI (Environmental 
Systems Research Institute) ArcWorld 3M data set at a scale of 1:3 million (ESRI 
1992) and from the Nelles Map series (Nelles 1997). Rivers were also taken from 
the  ESRI  ArcWorld  3M  and  the  Global  Insight  Plus  data  sets  (Europa 
Technologies  1999).  State  capitals  and  major  cities  are  named  in  local  language 
according  to  the  data  sources  of  the  ‘Commission  de  Toponymie’  (IGN  1997), 
updated from the Atlas Mondial Encarta (Microsoft  2001). 

Protected areas 

The protected areas were added from the WCMC database (Iremonger et al. 1997) 
using the IUCN categories I and II. The parks drawn on the map are those larger 
than 50’000 hectares belonging to the first two IUCN categories: 

- IUCN category I: Strict Nature Reserve and Wilderness Area: mainly for 

scientific purposes and wilderness protection. 

- IUCN category II: National Park and Provincial Parks: managed mainly for 

ecosystem protection and recreation.  

A list of those areas shown on the map is given in Annex 1.   

Forest cover map of insular Southeast Asia at 1: 5 500 000 

 12

 
 
 
 
 
 
 
 
 
Acknowledgements 
The  TREES  project  would  like  to  acknowledge  the  support  of  the  Global  and 
International Affairs unit of the EC Directorate for Environment.  

The World Conservation Monitoring Centre is thanked for providing us with the 
WCMC forest cover data set and the Protected Areas database. The authors would 
like  to  thank  also  the  Indonesian-German  IFFM/SFMP  (Integrated  Forest  Fire 
Management  /  Promotion  of  Sustainable  Forest  Management)  technical  co-
operation project for providing the map set of fire damages in East Kalimantan. 

The contribution of regional partners and institutions for performing field survey 
and detailed visual interpretation of Landsat TM images was essential for the map 
validation.  Partners  were:  BIOTROP  (Southeast  Asian  Regional  Centre  for 
Tropical  Biology)  /  IPB  (Agricultural  University),  Bogor  /  Indonesia;  CIFOR 
(Centre for International Forestry Research), Bogor / Indonesia; FOMISS (Forest 
Management  Information  System  Sarawak),  Kuching  /  Malaysia;  IFFM  Project, 
Samarinda / Indonesia and Max Plank Institute, Germany; PUSPICS (Centre for 
Remote Sensing and Integrated Surveys), Gadjah Mada University-Bakosurtanal, 
Yogyakarta  /  Indonesia;  RSS  (Remote  Sensing  Solutions),  München  /  Germany; 
UNITECH  (Papua  New  Guinea  University  of  Technology),  Lae  /  Papua  New 
Guinea.  

Dr.  Upik  R.  Wasrin  from  the University of Bogor is thanked for the translations 
into the Indonesian language. 

Finally the authors would like to thank their colleagues from the GVM unit of JRC 
for their advice and help in producing the map.  

Forest cover map of insular Southeast Asia at 1: 5 500 000 

 13

 
 
 
 
 
References 
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STIBIG, H-J., 1998, Identification of deforestation hot spot areas in the humid 
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Forest cover map of insular Southeast Asia at 1: 5 500 000 

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Annex 1: 
A list of the UNEP WCMC protected areas printed on the map is provided along 
with  a  reference  map.  This  data  was  provided  by  the  WCMC,  Cambridge,  UK. 
Note that only those parks larger than 50,000ha with IUCN category I or II were 
included. 

Name 
Berbak 

Country or 

Cat 

Island  Designation 
National Park 

II  Sumatra 

Bukit Baka - Bukit Raya 
Bukit Barisan Selatan 
Crocker Range 
Gunung Bentuang 

II  Kalimantan  National Park 
National Park 
II  Sumatra 
II  Sabah 
National Park 
II  Kalimantan  National Park 

Gunung Leuser 
Gunung Lorentz 
Gunung Palung 
Keluk Kupang 

Kep. Aru Tenggara 
Kepulauan Togian 
Kerinci Seblat 
Kinabalu 

Komodo 
Kutai 
Laut Cenderawasih 
Lore Lindu 

Manusela 
Marine Bunaken Manado Tua 
Marine Kepuluan Take Bone 
Rate 

Misool Selatan 
Morowali 
Mount Apo 
Mounts Iglit-Baco 

Muara Kaman Sedulang 
Peg. Peruhumpenai 
Pulau Waigeo 
Rawa Opa Watumohai 

Gulung Mulu 

Irian Jaya 

National Park 
Nature Reserve 

II  Sumatra 
I 
II  Kalimantan  National Park 
I 

Indonesia  Marine Nature Reserve 
Indonesia  Marine Nature Reserve 
Indonesia  Marine Nature Reserve 

I 
I 
II  Sumatra 
II  Sabah 

National Park 
National Park 

Indonesia 

National Park 
II 
II  Kalimantan  National Park 
National Park 
II 
Irian Jaya 
National Park 
II  Sulawesi 

II  Seram 
II  Sulawesi 

National Park 
National Park 

I 

Indonesia  Marine Nature Reserve 

Nature Reserve 
Nature Reserve 

Indonesia 
I 
I  Sulawesi 
II  Philippines  National Park 
II  Philippines  National Park 

I  Kalimantan  Nature Reserve 
Nature Reserve 
I  Sulawesi 
Nature Reserve 
I 
Indonesia 
National Park 
II  Sulawesi 

II  Sarawak 

National Park 

Map 
No 
1 

2 
3 
4 
5 

6 
7 
8 
9 
10 
11 
12 
13 

14 
15 
16 
17 

18 
19 

20 

21 
22 
23 
24 

25 
26 
27 
28 

29 

Forest cover map of insular Southeast Asia at 1: 5 500 000 

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Salawati Utara 
Siberut 
Sungai Kayan / Sungai 
Mentarang 
Taman Negara 
Tanjung Putting 

Teluk Maumere 
Wasur 
Way Kambas 
Yapen Tengah 

Irian Jaya 

I 
II  Sumatra 

Nature Reserve 
National Park 

I  Kalimantan  Nature Reserve 

II  Malaysia 
National Park 
II  Kalimantan  National Park 

Indonesia  Marine Nature Reserve 
Irian Jaya 

I 
II 
II  Sumatra 
I 

Irian Jaya 

National Park 
National Park 
Nature Reserve 

30 
31 

32 

33 
34 

35 
36 
37 
38 

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Forest cover map of insular Southeast Asia at 1: 5 500 000 

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European Commission 

EUR 20129 EN – Forest cover map of insular Southeast Asia at 1: 5 500 000 

Hans-Jürgen Stibig, René Beuchle and Pascale Janvier 

2002 25pp. –14.8 x 21 cm 

A forest cover map of insular Southeast Asia has been produced at 
a scale of 1: 5 500 000 based on SPOT4-VEGETATION satellite 
data of low spatial resolution. The map highlights the spatial 
distribution and extent of tropical forest cover in insular Southeast 
Asia at the beginning of the new millennium. Thematic classes as 
well as spatial accuracy reflect the possibilities and limitations of 
vegetation classification from coarse resolution satellite images, 
permitting a general overview on forest cover at the sub-regional 
level. 

Forest cover map of insular Southeast Asia at 1: 5 500 000 

 20