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Assessment of Large Scale Land Cover
Change Classification and Drivers of
Deforestation in Indonesia
Contributors: Arief Wijaya, Ruandha Agung Sugardiman, Budiharto,
Anna Tosiani, Lou Verchot, Daniel Murdiyarso, Martin Herold, Erika Romijn
36th International Symposium on Remote Sensing of Environment
Berlin, 10 – 15 May 2015
CIFOR Global Comparative Study on REDD+
 GCS Module 3: REDD+ MRV and Carbon Emissions
measurement
– Assessment of major deforestation drivers
– Setting national reference emission levels (RELs)
– Monitoring, reporting, verification (MRV) for REDD+
– Six case study countries: Brazil, Peru, Indonesia,
Vietnam, Tanzania and Cameroon
 Further information: www.cifor.org/gcs/
Outline of Presentation
 Common problems of national forest mapping in Indonesia
 Satellite data classification and approaches
 Comparison of available maps of forest loss/deforestation
 Needs for systematic accuracy assessment
 Drivers of deforestation analysis
One Landsat scene
cover 185 x 185 km
Indonesia is
covered by
218 scenes
Source: Ministry of Forestry of Indonesia
Highly rapid vegetation dynamics in Indonesia
Source: Ministry of Forestry of Indonesia
Satellite data availability and approaches
Source: Ministry of Forestry of Indonesia
Available datasets
 Land cover map of MOF (1990 - 2013)
 WRI Global Forest Watch data/GFW (2000 – 2013)
 Annual primary forest loss map of University of Maryland – from
Margono study (annually, from 2000 - 2012)
 Indonesian National Carbon Accounting System (INCAS), LCCA
project by Indonesian National Aerospace Agency (LAPAN)
(annually, from 2000 – 2012)
Comparison of deforestation/forest loss maps
0
500
1000
1500
2000
2500
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Annualtreecoverloss/deforestation
(000hectare)
GFW (Outside and inside primary forest)
GFW (Inside primary forest)
MOF - CIFOR (Natural forest)
Margono, et.al (Primary forest)
What causes
discrepancies in 2013?
Agreement and
disagreement of
forest loss /
deforestation
during 2000 – 2010
- MOF (orange
polygon)
- Margono (black)
- INCAS (other
colors)
Systematic accuracy assessment exercise
- Fine resolution Google Earth footprints imagery
- Mosaic cloud free Landsat data 2000, 2005, 2010
- Stratified random sampling points of verified forest loss 2000 – 2010
- To verify Margono, INCAS, MOF forest loss data
- Observe maps differences, Why? When?
- Improve forest loss estimate 2000 - 2012
Deforestation estimate across main Islands
Contributions of CO2 Emissions by Islands
Kalimantan and
Sumatera contribute
to ~80% of CO2
deforestation
emissions between
1990 – 2012
CO2 Emissions from Deforestation, Peat
Drainage and Peat Fires in Indonesia
Peatlands contribute to 30 – 50% of total carbon emissions from
forestry sector between 1990 and 2012
Land Use Types Following Forest Conversion
1990-2000
Forest definitions matter!
Distribution of deforestation drivers in Indonesia from 2000 to 2009 based on analysis
of follow-up land cover/land use type
Source: Romijn, et al (2013)
Supporting Donors :

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Assessment of Large Scale Land Cover Change Classification and Drivers of Deforestation in Indonesia

  • 1. Assessment of Large Scale Land Cover Change Classification and Drivers of Deforestation in Indonesia Contributors: Arief Wijaya, Ruandha Agung Sugardiman, Budiharto, Anna Tosiani, Lou Verchot, Daniel Murdiyarso, Martin Herold, Erika Romijn 36th International Symposium on Remote Sensing of Environment Berlin, 10 – 15 May 2015
  • 2. CIFOR Global Comparative Study on REDD+  GCS Module 3: REDD+ MRV and Carbon Emissions measurement – Assessment of major deforestation drivers – Setting national reference emission levels (RELs) – Monitoring, reporting, verification (MRV) for REDD+ – Six case study countries: Brazil, Peru, Indonesia, Vietnam, Tanzania and Cameroon  Further information: www.cifor.org/gcs/
  • 3. Outline of Presentation  Common problems of national forest mapping in Indonesia  Satellite data classification and approaches  Comparison of available maps of forest loss/deforestation  Needs for systematic accuracy assessment  Drivers of deforestation analysis
  • 4. One Landsat scene cover 185 x 185 km Indonesia is covered by 218 scenes Source: Ministry of Forestry of Indonesia
  • 5. Highly rapid vegetation dynamics in Indonesia Source: Ministry of Forestry of Indonesia
  • 6. Satellite data availability and approaches Source: Ministry of Forestry of Indonesia
  • 7. Available datasets  Land cover map of MOF (1990 - 2013)  WRI Global Forest Watch data/GFW (2000 – 2013)  Annual primary forest loss map of University of Maryland – from Margono study (annually, from 2000 - 2012)  Indonesian National Carbon Accounting System (INCAS), LCCA project by Indonesian National Aerospace Agency (LAPAN) (annually, from 2000 – 2012)
  • 8. Comparison of deforestation/forest loss maps 0 500 1000 1500 2000 2500 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Annualtreecoverloss/deforestation (000hectare) GFW (Outside and inside primary forest) GFW (Inside primary forest) MOF - CIFOR (Natural forest) Margono, et.al (Primary forest) What causes discrepancies in 2013?
  • 9. Agreement and disagreement of forest loss / deforestation during 2000 – 2010 - MOF (orange polygon) - Margono (black) - INCAS (other colors)
  • 10. Systematic accuracy assessment exercise - Fine resolution Google Earth footprints imagery - Mosaic cloud free Landsat data 2000, 2005, 2010 - Stratified random sampling points of verified forest loss 2000 – 2010 - To verify Margono, INCAS, MOF forest loss data - Observe maps differences, Why? When? - Improve forest loss estimate 2000 - 2012
  • 12. Contributions of CO2 Emissions by Islands Kalimantan and Sumatera contribute to ~80% of CO2 deforestation emissions between 1990 – 2012
  • 13. CO2 Emissions from Deforestation, Peat Drainage and Peat Fires in Indonesia Peatlands contribute to 30 – 50% of total carbon emissions from forestry sector between 1990 and 2012
  • 14. Land Use Types Following Forest Conversion 1990-2000
  • 15. Forest definitions matter! Distribution of deforestation drivers in Indonesia from 2000 to 2009 based on analysis of follow-up land cover/land use type Source: Romijn, et al (2013)

Editor's Notes

  1. REDD+ Policies examines how REDD+ is unfolding in the national policy arena. REDD+ Subnational Initiatives examines how REDD+ projects can be designed and implemented so that their outcomes are effective, efficient and equitable and they deliver co‑benefits. Measuring Carbon Emissions looks for ways to enable better carbon accounting so that emission reductions can be reliably measured and verified. Mitigation–Adaptation Synergies looks for ways to exploit the synergies between REDD+ and climate change adaptation, to ensure that REDD+ has an impact beyond mitigation and is sustainable in a changing climate. REDD+ Benefit Sharing aims to provide policy options and guidance for the design, development and implementation of REDD+ benefit‑sharing mechanisms