Science and Technology Research Partnership for Sustainable Development“Wild Fire and Carbon Management in Peat-Forest in Indonesia”

Comprehensive MRV System in Tropical Peatland Ecosystem
Kazuyo Hirose1, Mitsuru Osaki1, Toshihisa Honma1, Takashi Hirano1, Hidenori Takahashi1, Gen Inoue2, Wataru Takeuchi3, Heri Andreas4,Hasanuddin Z. Abidin4, Osamu Kashimura5, Hozuma Sekine6, Heryandi Usup7, Gumiri Sulmin7 and Ici P. Kuli7
1Hokkaido University, 2Atmosphere and Ocean Research Institute, University of Tokyo, 3Institute of Industrial Science (IIS), University of Tokyo, 4Bandung Technology Institute (ITB),
5Earth Remote Sensing Data Analysis Center (ERSDAC), 6Mitsubishi Research Institute, 7Palangka Raya University (UNPAR)

E-mail: hirose@census.hokudai.ac.jp, mosaki@chem.agr.hokudai.ac.jp

Reducing Emissions from Deforestation and forest Degradation (REDD-plus) mechanism is expected to generate new incentive with co-benefit totropical peatland ecosystems. Multi-temporal, multi-satellite sensors and multi-methods approach for establishment of reliable MRV system is a keyof successful REDD-plus implementation. The group of Hokkaido University and Indonesian Institutes concluded that eight key elements areessential to establish reliable and comprehensive MRV system based on more ten years-long term ground observation data in peatland of Central
Kalimantan, Indonesia.
[Eight key elements] (1) CO2 concentration, CO2 flux rate, (2) Hotspots detection, (3) Forest degradation and species mapping, (4) Deforestation,
forest biomass changes, (5) Water level and soil moisture, (6) Peat dome detection and peat thickness, (7) Peat-subsidence, and (8) Water solubleorganic carbon (Fig.1). These are obtained by advanced technology of remote sensing sensors loaded in GOSAT, ALOS/PALSAR, TERRA/ASTER,HISUI and others.
(3) Forest Degradation and Species Mapping by HISUI(1) CO2 Concentration Estimation by GOSAT, FES-C, UAV
The Greenhouse Gases Observing Satellite (GOSAT) is theworld's first spacecraft to measure the concentrations of green
house gasses (GHGs) such as carbon dioxide (CO2) andmethane (CH4) in atmosphere. It enables to map the CO2
concentration with data observed by CO2 flux tower andsimulated model on CO2 concentration related with soil
Current ground-based monitoring stations
moisture in peatland.
<200 points
GOSAT flies at an altitude of approximately 666 km andcompletes one revolution in about 100 minutes. The satellite
returns to the same point in space in three days (Figure in nextslide). The observation instrument onboard the satellite is theThermal And Near-infrared Sensor for carbon Observation(TANSO). TANSO is composed of two subunits: the Fourier
Transform Spectrometer (FTS) and the Cloud and Aerosol
56000 points
Imager (CAI).
Specifications of FTS

Ministry of Economy, Trade and Industry (METI), Japan is developing a Hyper-spectral Imager SUIte (HISUI) which will
be launched in 2014. It has 185 bands (57 bands in VNIR, 128 bands in SWIR) with narrow spectral resolutions (1012.5nm). It allows not only to classify forest species and to evaluate forest degradation, but also to estimate water solubleorganic carbon which plays an important role of carbon cycle in tropical peatland.
Japanese cedar
Japanesecedar
Japanesecedar

BilstedCanadian
hemlock

Quercusmyrsinaefolia

Blue Japaneseoak

Up: schematic illustration of how GOSAT
makes observations.
Upper left: locations of ground-based
monitoring stations (source: World Data
Centre for Greenhouse Gases).
Left: GOSAT’s footprint in three days

Spectral libraryof tree canopy

Loblolly pine

BetulagrossaQuercusmyrsinaefolia

Canadian
hemlockBlue JapaneseoakStewartia
monadelphaWhite pine
Stewartia
monadelpha

Zelkova

Sequoia
sempervirens

Quercuscrispula
Cedar
Quercusgilva Blume

Cedar

Sequoia
sempervirens

Zelkova

20m

Site：Tokyo, Japan
Data：CASI (2004/9/1) [413-1053nm, 72bans, 1x1m](http://www.gosat.nies.go.jp/eng/gosat/)

GOSAT (1)Terra & Aqua
MODIS (2)Satellite

Bald cypress

BetulagrossaWhite pine

Bald cypress

Quercuscrispula
Quercusgilva Blume

Loblolly pine

Specification of HISUI
Landsat, SPOT,
TerraSAR,
AVNIR-2, **VHR
Sensors (3), (4)ASTER,ASNARO,
Hisui (2),(3),(4), (8)PALSAR, AMSR-E(4), (5), (6), (7)(http://www.ersdac.or.jp)

Parameter

Requirement

Resolution, Swath

30 m and 30 km

SpectralSpecifications of CAI

Bands

185 (VNIR:57 SWIR:128)

Range

VNIR:0.4-0.97 μm
SWIR:0.9-2.5 μm

Resolution

10 nm (VNIR), 12.5 nm (SWIR)

Dynamic Range
Pointing Capability

Airborne/***UAV

UAV(1), (3)Lateral CO2 Flux(2) Wildfire detection &Hotspot(3) Forest degradation &Species mapping

GroundChamber(1)(4) Deforestation &Forest biomass change*FES-C (1)

DGPS(7)

DGPS(7)(6)Peat dome detection& Peat thickness

Example of DOC using ALI
image acquired on 14, July 2002
(After Kutser et al., 2005)(5)Water Table,& Soil moistureDrilling(6)*FES-C : Fiber Etalon Solar measurement of CO2**VHR : Very High Resolution Remote Sensing Data≈ ±3 ° (±30 km)

Dissolved Organic Carbon (DOC) is identified as the mostsignificant form of carbon export from peatlands, and it has beenfound to be between 51 to 88% of fluvial carbon export (e.g.
Hope et al., 1997; Dawson et al., 2002). Thus, monitoring DOC isan essential process to estimate dynamic carbon flux in a peatland
ecosystem. As concentrations of colored dissolved organic matter(CDOM) and DOC are strongly correlated (Tranvik 1990;
Kortelainen 1993; Kallio 1999), CDOC enables to estimate DOC
values from the satellite data (Kutser et al.,2005).

(1) CO2 Flux &Concentration

Vertical CO2 Flux

12bit(8) Water soluble organic carbon
estimation by HISUI

LiDAR (4), (6), (7)Combination with FES-C (fully automated observation of CO2)

Tower(1)CedarZelkova
Blue Japanese oak
Sequoia sempervirens
BilstedWhite pine
Loblolly pine
Quercus gilva Blume
Bald cypress
Quercus myrsinaefolia
Stewartia monadelpha
Canadian hemlock
Betula grossa
Quercus crispula

BilstedWaterGauge(5)(7)Peat subsidence(8)Water soluble organiccarbon***UAV: Unmanned Aerial Vehicle

Fig.1 Key Elements of comprehensive MRV system in peatland

Red: Instrument
Black: Target
CDOM: absorption coefficients at 420nm(m-1), DOC: mg/L-1 calculated by CDOM
GPS investigation point(5) Ground Water Table (GWT) and Soil Moisture Estimation(7) Peatland Subsidence Monitoring by PALSAR Interferometry with Differential GPS Survey

SAR Interferometry (InSAR)

Flowchart of GWT estimation using drought index (Dr.Takeuchi)

SAR 1
SAR 2

subsidence

Example of InSAR subsidence
monitoring in Jakarta (Hiroseet al., 2001)h = H － r × cos θGPS monitoring point in peatland

GPS reference point (Granite)
BM:BTAL

BM:BTAL

TGT3
TGT1

GPS reference point

GPS monitoring point in peatland GPS monitoring point in peatland(mKBDI is calibrated suitable for peatland measurement, NDFI is used to map inundated peatland)

TGT4Precipitation (mm)TGT3GPS monitoring point
TGT1
TGT4ModelSpecial Equipment “ Floating GPS Bench Mark”
for Peatland Subsidence Monitoring”

GPS Data Processing
Characteristics of Baseline<10 kmBaseline Length12
Number of Baseline~1 day hr
Observation Length
Epoch Interval
Elevation Mask
GPS Data

Note
Radial from 3 reference station
Linear combination was used

Result of Peatland Subsidence derived from GPS Data
(Nov. 2010 – July 2011: 8 months)

30 seco15

NoGPS Station

H ellipsoid (m)Nov 2010(Wet Season)

1

TGT1

51.2958

51.2863-0.0095

L1 and L2

H ellipsoid (m)July 2011(Dry Season)

Subsidence(m)GPS Biases and Errors

Reduction Strategy

Ephemeris

Differencing and Precise Ephemeris

Ionosphere

Differencing and Estimated

2

TGT2

50.792550.7951

0.0026

Troposphere

Differencing and Estimated

3

TGT3

50.6332

50.5993-0.0339

Cycle Ambiguity

Quasy Ionospheric Free Method

GPS Biases and Errors

Reduction Strategy

4

TGT4

49.7986

49.7901-0.0085

ERSDAC

Blue: GWT(measured)Green: GWT(model)

Ground Water Table (cm)TGT2Center for Sustainability Science (CENSUS) , Hokkaido University
Address: N-9 W-8, Kita-ku , Sapporo, 060-0809, JAPANTEL: 011-706-4531, FAX: 011-706-4534, E-mail: jst-jica@census.hokudai.ac.jp
Homepage : www.census.hokudai.ac.jp

st
1 Open Seminar, REDD Research and Development Center, Forestry and Forest Products Research Institute, 13-14 October 2011