Joint GFOI/GOFC-GOLD Expert Workshop 2: Approaches to monitoring forest degradation for REDD+

Characterizing Forest Degradation and Carbon Biomass Assessment in Tropical Peatlands

using Multi Remote Sensing Approaches

Arief WijayaCenter for International Forestry Research (CIFOR), Indonesia

Contributors: Ari Susanti, Oka Karyanto, Wahyu Wardhana, Lou Verchot, Daniel Murdiyarso, Richard Gloaguen, Martin Herold, Ruandha Sugardiman, Budiharto,

Anna Tosiani, Prashanth Reddy Marpu and Veraldo Liesenberg

Wageningen, The Netherlands1-3 October, 2014

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Project Background• This work is part of CIFOR projects

– Global Comparative Study on REDD+ (GCS REDD) – work in 6 countries

– Sustainable Wetlands Adaptation and Mitigation Project (SWAMP) – work in > 20 countries

• CIFOR is an international research organization working based on three pillars – research, capacity building and media outreach

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Background• The presentation focuses on mapping of

tropical peatlands in Indonesia using SAR and optical sensors

• Tested various classification approaches and SAR features combined with reflectance of optical data to improve image classification

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Importance of Peatlands Ecosystem• The GoI is preparing FREL submission to

UNFCCC – emissions from deforestation, peat decomposition and peat fires

• Indonesia covers >80% (~20 Mha in 1990 out of 24 Mha) of tropical peatlands in SE Asia

• 1.1 Mha of intact peat swamp forests and 6.8 Mha of secondary peatlands forest were deforested from 1990 – 2012

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Carbon emission from Peatlands

Source: MOF and CIFOR analysis

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National Forest Degradation Mapping• Most likely based on national land cover

change map from 1990 – 2013• 23 land cover types – primary and secondary

forests• Degradation is change of primary to secondary

forests – upland, mangrove, peat swamp ecosystems

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Land Cover Classification SystemLanduse/cover classification of Indonesia for the years 1990, 1996, 2000, 2003, 2006, 2009, 2011, 2012 and 2013. Data source: LANDSAT satellite data (30 m resolution) (MOF, 2014)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

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• Characteristics: maps based on visual interpretation of Landsat data, MMU 6.25 ha, need to assess the consistency

• Not yet included in any national reporting – FREL submissions to UNFCCC during COP in Lima – issues of FD definition, REDD activity degradation/carbon stock enhancement

National Forest Degradation Mapping

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Deforestation Drivers Analysis

What about drivers of forest degradation?

Saatchi biomass map

Baccini biomass map

Adjusted RS biomass measurement

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

Carbon density by landcover typeForest 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.

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Carbon stocks change 2000 - 2009

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Landcover and carbon densityLandcover 2000 Landcover 2009

(a) (b)

(c) (d)

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Degradation Mapping Exercise

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Data• Dual-polarimetry TerraSAR X data (2008)• PLR data of ALOS Palsar (2007-2009)• Landsat data• Peatland maps from Wetland International • Land use/land cover map from MoF

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Peatlands under studyClass label Peat types Peat

thicknessProportions

(%)Bulk density

(gram/cc)Carbon

contents (%)Land

cover type

Mangrove forest (MF)

- - - - - Mangrove forest

Deep peat in primary swamp forest (PDP)

Hermists/fibrists (H3a)

2 – 4m (deep) 60/40 Hermists: 0.23Fibrists: 0.13

Hermists: 36%Fibrists: 43%Mineral: 31%

Primary forest

Shallow peat in primary swamp forest (PSP)

Hermists/fibrists/mineral (H1b)

0.5 – 1m (shallow)

50/30/20 Hermists: 0.23Fibrists: 0.13Mineral: 0.32

Primary forest

Very shallow peat in sparse forest (PVSp)

Hermists/mineral (H1i)

<0.5m (very shallow)

20/80 Hermists: 0.23Mineral: 0.32

Sparse forest

Shallow peat in secondary swamp forest (PSS)

Hermists/fibrists/mineral (H1b)

0.5–1m (shallow)

50/30/20 Hermists: 0.23Fibrists: 0.13Mineral: 0.32

Secondary forest

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SAR Data Decomposition

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SAR Backscatter Responses

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Alpha Entropy Plane

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Land Cover Map

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PLR SAR Features

Polarimetric features: alpha angle (a), entropy (b) and anisotropy (c). Two additional polarimetric features were also calculated, PolSAR random volume over ground volume ratio (RVOG_mv) based on polarimetric data inversion and accumulation of polarimetric backscatter (span in decibel / span_db)

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Alpha Entropy Plane

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Initial SAR Classification

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Technical Challenges/Opportunities• Needs to upgrade technical competence in the

country – ground station is available• Access to data might not be major concern –

various donors/bilateral cooperations continuously comes – JICA, EU, USAID, Norway

• Methods for merging SAR and optical need good knowledge of RS data pre-processing

• Relatively good IT infrastructure and facilities

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R&D Challenge/Opportunity• More difficult to accept modeling approach• Proposed methods should fit in with existing

national capacity• Multi-stakeholders discussion and

involvement in various meetings• Inform country about international

guidelines/standards/conventions which can be applied