Deforestation drivers, carbon emission estimate and setting forest reference levels

Deforestation drivers, carbon emission estimate and setting

forest reference levels

Arief Wijaya1, Lou Verchot1, 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

THINKING beyond the canopy


Background

CIFOR Global Comparative Study (GCS) on REDD+ Component 3: MRV and reference levels

• Monitoring, reporting, verification (MRV) for REDD+

• Setting national reference emission levels (RELs)

• 6 case study countries: Indonesia, Vietnam, Tanzania, Cameroon, Brazil, Peru


Specific objectives

To detect areas and activities (drivers) of deforestation To calculate carbon emissions and sequestration of

deforested and degraded regions To explore the concepts for developing RELs at national

and sub-national levels


Stepwise approach for RELs

(Herold, et.al, 2011)


Carbon biomass estimation approach

Field data (e.g. National forest inventory) Direct remote sensing measurement

• Empirical models where RS data is calibrate to field estimates (Baccini et al. 2004, 2008, Saatchi et al. 2007, Blackard et al. 2008)

Stratify and Multiply (SM) method

• Assign an average biomass value to land cover/vegetation type map (Asner et al. 2010)

Combine and Assign approach

• Extension of SM, GIS and multi-layers information (Gibbs et al. 2007)

Ecological Models approach

• RS data to parameterize the biomass model (Hurtt et al. 2004)


Mosaic Landsat GLS Data

Source: USGS downloaded from ArcGIS server


NDVI change 1990 - 2000

Source: USGS downloaded from ArcGIS server


Direct remote sensing measurement

Biomass map based on study by Baccini et al. (2012) including LIDAR shots data obtained during Biomass mapping training at BIG


Available national biomass map


Available national biomass map


Stratify and Multiply Method

Landuse/cover classification of Indonesia for the years 2000, 2003, 2006 and 2009Data source: LANDSAT satellite data (30 m resolution) (MOF, 2009)

No Classification

1 Primary Upland Forest2 Secondary Upland Forest/Logged Forest3 Primary Swamp Forest4 Secondary Swamp Forest/Logged Area5 Primary Mangrove Forest6 Secondary Mangrove Forest/Logged7 Crop Forest8 Oil Palm and Estate Crops9 Bushes/Shrubland10 Swampy Bush11 Savanna12 Upland Farming

No Classification

13 Upland Farming Mixed with Bush 14 Rice field15 Cultured Fisheries/Fishpond16 Settlement/Developed Land17 Transmigration18 Open Land19 Mining/mines20 Water Body21 Swamp22 Cloud 23 Airport/Harbor


Deforestation 2000-2009

IslandArea of deforestation (×1000 ha) Area of degradation (×1000 ha)2000-2003 2003-2006 2006-2009 2000-2003 2003-2006 2006-2009

Sumatera 278.95 709.89 1063.01 0.00 5.02 101.66Java 0.27 51.05 2.92 9.08 64.32 0.00Bali & Nusa Tenggara 45.10 38.52 3.74 3.25 3.31 54.08Kalimantan 367.24 963.60 705.48 825.38 304.11 74.57Sulawesi 200.25 283.48 49.62 230.07 1655.13 52.95Maluku 24.24 24.30 18.09 8.48 10.67 0.22Papua 79.15 186.78 728.10 298.20 634.66 777.24Total 995.20 2257.62 2570.96 1374.46 2677.22 1060.72

Annual deforestation 647 thousand ha/year vs FRA FAO Report (2010) 498 thousand ha/year


Deforestation based on forest typeTh

ousa

nd h

ecta

re

Deforestation Forest degradation


Deforestation drivers


Carbon emission estimate

(Sugardiman, 2011 modified from the IPCC report)


Carbon density by landcover type

Forest classes carbon (ton/ha) SD (ton/ha)Primary dry forest (PF 2001) 179.9 16.9Secondary dry/logged over forest (SF 2002) 173.7 15.2Primary Swamp Forest (PSF 2005) 155.5 19.2Secondary swamp forest(SSF 20051) 143.8 19.7Primary mangrove forest (PMF 2004) 87.4 13.4Secondary mangrove forest (SMF 20041) 62.6 8.9Crop forest (CF 2006) 111.4 17.0

Non-forest classes (vegetated) carbon (ton/ha) SD (ton/ha)Oil Palm and estate crops (PG 2010) 95.6 19.9Bushes/Shrubland (B2007) 123.9 13.7Swampy bush (SB 20071) 77.6 14.1Savanna (S 3000) 63.1 11.3Upland farming (UF 20091) 79.9 14.5Upland farming mixed with bushes (Pc 20092) 115.2 17.2Rice field (Sw 20093) 62.8 12.0


Carbon stocks change 2000 - 2009

Based on Multiply and Stratify approach. The figure shows only C stocks above ground excluding on peat soils.

Biomass map based on study by Saatchi (2011) and land cover map from the Ministry of Forestry (2009)

2000



2009



2009


Landcover and carbon density

Landcover 2000 Landcover 2009

(a) (b)

(c) (d)


Why one map policy is important?

Land cover/land use map Biomass/C stocks map


Deforestation rates (official data MOF)


Comparison of different studies

1990-2000

2000-2001

2001-2002

2002-2003

2003-2004

2004-2005

2005-2006

2006-2007

2007-2008

2008-2009

2009-20100

100

200

300

400

500

600

700

800

900

1000

Indonesia MOFOR Indonesia Hansen

Indonesia JRC Indonesia Mean

Annu

al D

efor

esta

tion

(x 1

000

ha)


Cumulative LUCF carbon emissions

SourceCumulative Emission from

LUCF 2000 -2009(in Gg CO2e)*

Methods Remarks

FAOStat 3,140,033 FRA country report(EF = 138 ton C/ha) Net forest conversion

MoE - Second National Communication to UNFCCC 7,443,064 IPCC Guidelines 2006 Net forest conversion

Winrock International (Harris, 2012) 3,468,150 Carbon Bookkeping model

(RS + Field) Gross deforestation

MOF (official) 1,760,000 Approach 1 + NFI(Tier 1 or 2)

Net forest conversion (peat?) - carbon emissions potential

MOF + Saatchi (CIFOR) 1,811,396 Approach 1 + Global EF(Tier 1 or 2) Net forest conversion

Mean 3,524,529

* does not include peat emissions and peat fire


Annual LUCF Carbon emissions

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 20110

100000

200000

300000

400000

500000

600000

700000

800000

900000

1000000

1100000

1200000

1300000

1400000

FAOStat

LUCF - Second NatCom MoE

MOF + Saatchi (CIFOR)

Annu

al C

arbo

n Em

issio

ns f

rom

LU

CF (i

n Pg

CO

2e)


Combining socio-economic data

Population density

Family ratio below poverty levelAgriculture family ratio


Combined with forest transition curve?

(Angelsen, 2008)


Concluding remarks

Stepwise approach is useful to handle data uncertainty and data quality variations in estimating RELs

Carbon density estimated at different land cover types can cause combined errors

Indonesia has capability to implement Tier 3 (or 2.5??) of the REL estimation (given the availability of reliable forest inventory data and spatially explicit datasets)


www.cifor.cgiar.orgwww.cifor.cgiar.org