Characterizing Forest Degradation and Carbon Biomass Assessment in Tropical Peatlands using Multi-Temporal and Multi-

Polarizations SAR Data

Contributors: Arief Wijaya, Ari Susanti, Oka Karyanto, Wahyu Wardhana, Lou Verchot and Veraldo Liesenberg

36th International Symposium on Remote Sensing of EnvironmentBerlin, 10 – 15 May 2015

Project Background

This work is part larger CIFOR projects

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

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

This study is CIFOR research portfolio to address climate change

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Outline of Presentation

Importance of peatlands for Indonesia

CO2 emissions from peatlands

Test site descriptions

Data and methods

Results

– Peatlands mapping using ALOS PALSAR data

– Above ground biomass assessment

Importance of Peatlands Ecosystem

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 degraded peatlands forests were lost 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

Recent large-scale clearance of peatland forest inside a PT. Riau Andalan Pulp & Paper (PT RAPP) pulpwood concession on Pulau Pedang. © Ulet Ifansasti / Greenpeace.

Test Sites

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Available Satellite Data

Quad polarizations ALOS Palsar (May 2010) – forest degradation discrimination

Quad polarizations ALOS Palsar (April 2007, May 2007, April 2009, April 2010) - biomass modeling

Landsat 5 image (February 2010)

Peatland maps from Wetlands International

Land use/land cover map from Ministry of Forestry (2000 – 2012)

Field Data Collection

Land use Volume (m3/ha)

AGB (Mg/ha)

Carbon stocks (MgC/ha)

Tree height

(m)Basal area

(m2) LAI

Peat swamp forest

592.35 228.25 114.12 16.92 33.19 2.96

Pioneer species (Macaranga sp.)

32.63 7.47 3.74 11.22 9.71 3.09

Mangrove forest 182.16 105.65 52.82 9.53 11.79 2.38Plantation forest 196.33 130.95 65.48 12.57 13.22 1.32Rubber plantation

125.73 113.44 56.72 14.95 51.02 2.06

- In total, 83 sampling plots were collected during dry season in 2010- Circular nested sampling plots within 60 x 60 m2- Size of each sub plot 0.04 ha

Peatlands Mapping Results

SAR Data Preprocessing Data extraction, image registration, corrections and noise filtering

Polarimetric features: entropy, anisotropy, alpha angle, RVOG ratio, span

Supervised classification: Multi-Layer Perceptron Neural Network (MLP-NN) method and Maximum Likelihood Classification (MLC)

Alpha Entropy Plane

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SAR Classification Results

Biomass Modeling Results

Above ground biomass modeling results

IDAcquisition

datePredictor(s) Biomass model coefficients R2 SEE F Sig.

7001 20/5/2007

HH, HV, VH, VV, Alpha, Entropy, Anisotropy

y = 157.38HH - 467.09HV + 405.08VH + 23.4VV - 41.6Alpha + 4913.7Entropy - 1096.4Anisotropy + 175.656

0.278202.21

70.441 0.851

2001 9/4/2009

HH, HV, VH, VV, Alpha, Entropy, Anisotropy

y = 171.07HH - 298.26HV + 264.46VH + 96.1VV + 50.89Alpha + 714.9Entropy + 2189.26Anisotropy - 825.3

0.416181.98

10.813 0.601

1001 12/4/2010

HH, HV, VH, VV, Alpha, Entropy, Anisotropy

y = 191.57HH - 30.7HV + 104.46VH + 31.69VV - 25.19Alpha + 1150.47Entropy + 2598.39Anisotropy + 3248.58

0.670 99.83 5.356 0.015

1001 12/4/2010 HH y = 238.164HH + 2987.913 0.744 91.014 40.733 0.000

Features selection is apparently important for biomass modeling

Seasonal Variability or Land Use Change?

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300

350

400

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Mon

thly

pre

cipi

tatio

n (m

m)

Month

mean = 263 mm

Source: Indonesian National Metereological Agency

ALOS Palsar acquisition (2007, 2009, 2010)

Field work (2010)

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