whrc workshop 8-12 nov 2010, mulawarman

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FOREST BIOMASS & CARBON STOCKS MAPPING USING SATELLITE IMAGERIES & ISSUES RELATING TO REDD+ IN MALAYSIA Hamdan Omar GeoInformation Programme Division of Forestry and Environment, FRIM Workshop on Methods for Biomass Estimation and Forest-Cover Mapping Woods Hole Research Center 8-12 October 2010 Center for Climate Change Studies, University of Mulawarman, Indonesia

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FOREST BIOMASS & CARBON STOCKS

MAPPING USING SATELLITE IMAGERIES &

ISSUES RELATING TO REDD+ IN MALAYSIA

Hamdan Omar

GeoInformation ProgrammeDivision of Forestry and Environment, FRIM

Workshop on Methods for Biomass Estimation and Forest-Cover MappingWoods Hole Research Center

8-12 October 2010Center for Climate Change Studies, University of Mulawarman, Indonesia

Presentation Outline

• What have we done

• What are we planning to do

• REDD+: Malaysia‟s perspective

2

Hamdan Omar, Mohd Azahari Faidi & Khali Aziz Hamzah

Proc. STSS 2010 | 1-2 June 2010, MS Garden Kuantan

ALOS PALSAR SATELLITE IMAGE FOR

TROPICAL FOREST CARBON STOCK MAPPING

L-BAND SAR SATELLITE IMAGE FOR TROPICAL

FOREST BIOMASS ESTIMATION

Hamdan Omar, Khali Aziz Hamzah & Abd Rahman Kassim

Journal of Tropical Forest Science (JTFS): Reviewing

1

2

Objective of Study

i) To establish empirical relationship between aboveground carbon stocks and L-band SAR signals,

ii) To determine aboveground biomass and carbon stocks of tropical forest by using L-band SAR data, and

iii) To identify capability of ALOS PALSAR satellite imagery in estimating aboveground biomass and carbon stocks.

Study Area

• Forest Research Institute Malaysia (FRIM) covers some 485.2 ha site in Kepong, Selangor.

• Surrounded by the Bukit Lagong Forest Reserve.

• Most of the forest trees standing in FRIM area are planted forest. Out of the total area of 485.2 ha, 420.11 ha (86.58%) are covered by forest and 379.98 ha (or 90.4%) of them are planted forest and the remaining 40.12 ha is natural forest.

• The age of most of the trees here are about 80 years old, which were planted since year 1929.

Materials & Methodology

Satellite Data

The Japanese Advanced Land Observing Satellite (ALOS), which carries polarimetric Phased Array L-band Synthetic Aperture Radar (PALSAR) satellite data was used in this study.

ALOS PALSAR image that was used in this research was acquired on 3rd October 2009 and has spatial resolution of 12 m.

Field Inventory Data

Field survey was carried out and more than 30 plots of 50 x 50 m size were established within the study area. The plots covered all forest types and various ages.

All the trees with the size of dbh of more than five centimetre (≥ 5 cm) were inventoried.

Design of the plots that were distributed and laid on the ground in the study area.

Plots were laid on the ground and the centre coordinate was recorded.

PLOT CENTER

NW

NE

SW

SE

Distance metric tape

Inventory Equipments

HypsometerLaser range for tree

height and slope measurements

Hand held GPS

Diameter TapeDBH measurement

Ground data collection

Ground data collection

High biomass & carbon concentration

Medium biomass & carbon concentration

Low biomass & carbon concentration

Dominant types of standing

trees that are found in the study area. Most of the

trees are above 25 m height

and reach up to 45 m.

Biomass equations to calculate AGB were based on Kato et al. (1978). The allometric function of trees applied in the calculation of standing biomass can be expressed as

1/H = 1/(2.0*D)+1/61

From the values of D and H, the dry mass values of stem, branches and leaves of the tree are estimated.

Ms = 0.0313*(D2H)0.9733Mb = 0.136*Ms1.0701/Ml = 1/(0.124Ms0.794)+1/125

where;H = total tree heightD = stem diameter at breast height (dbh)Ms, Mb and Ml denote the dry mass of stem, branches and leaves respectively.

Above Ground Biomass

Plot 05

Plot 07

Plot 09

Plot 04

SAR signals at the corresponding plots were sampled

out to generate empirical equation.

Radar band X C L P

Wavelength (cm) 2.4 – 3.75 3.75 – 7.5 15 - 30 30 – 100

Main scatterers Leaves, Twigs

Leaves, Small

branches

Branches, Trunk

Trunk

Response of SAR to the forest structure

Weak signalSmall stands

Strong signalDense standsHigh Biomass

Relationship between biomass and L-Band ALOS PALSAR signal

Results

The results found that the live aboveground woody biomass ranged from 25.9 to 569.3 t ha−1 with the dominant value of 193.6 t ha-1.

All the pixels values were converted into the unit of carbon stocks (t C ha−1) and found that the distribution of aboveground carbon stocks of forest within study area range from 12.45 to 284.65 t C ha−1.

CategoryRange of Biomass

(t/ha)Percentage of Area Coverage

(%)

Small, growing stands 26 - 116 28.2

Mixed small & mature stands 130 - 155 16.9

Mature, dense stands 168 - 414 51.1

Mature & very dense stands 427 - 569 3.9

Hamdan Omar & Khali Aziz Hamzah

Geoinformation Programme, Forestry and Environment Division

Forest Research Institute Malaysia (FRIM)

52109 Kepong, Selangor

ISFFP 2010 | 5-7 October 2010, Legend Hotel, KL

FOREST STAND VOLUME

ESTIMATION USING SATELLITE SAR

IMAGERY

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Relationship Between ALOS Palsar Backscatter & Stem Volume

y = 104160e0.4735x

R2 = 0.865

0

50

100

150

200

250

300

350

400

450

500

-19 -18 -17 -16 -15 -14 -13 -12 -11 -10

Backscatter Coefficient (L-HV, dB)

Me

rch

an

tab

le V

olu

me

(m

^3

/ha

)

Scatter plot that consists of measured stem volume and corresponding SAR signal from PALSAR image.

Forested area

Chengalplot

Kapur

Dip & Non-Dip Arboretum

Kepong Botanic Garden

Geoinformation Programme, Environment and Forestry Division

Forest Research Institute Malaysia (FRIM)

52109 Kepong, Selangor

20-23 April 2010 | FRIM, Kepong

TRAINING ON USE OF REMOTE

SENSING FOR ASSESSING FOREST

BIOMASS & CARBON STOCKS

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Participants listening attentively to the lecture.

Participants brought to the site for field data collection.

Participants learning the field data collection process.

Participants learning image sampling, modelling & mapping processes

A photograph of all participants and organisers.

A photograph of all participants and organisers.

CARBON STOCKS MONITORING ON PEAT

SWAMP FOREST IN PENINSULAR MALAYSIA:

TOWARDS REDD IMPLEMENTATION

Proposed for MOA-ScienceFund26 MEI 2010, FRIM

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i. To update and map the current extents of peat swamp forest in Peninsular Malaysia,

ii. To quantify extents and changes of carbon stocks from year 2000 to 2010 on peat swamp forest,

iii. To generate spatially distributed map of carbon stock on peat swamp forest over Peninsular Malaysia, and

iv. To demonstrate the use of remote sensing techniques in carbon stocks monitoring for the REDD reporting.

Objectives:

Distribution of PSF in Malaysia:

(i) Pahang (200,000 ha), (ii) Selangor (76,000 ha), (iii)Terengganu (13,000 ha), (iv) Johor (13,000 ha).

MethodologyData acquisitions:

A series of SPOT & ALOS PalSAR imagery(2000 & 2010)

Image ClassificationIdentification of PSF extents in both PRF &

Stateland

Image ClassificationIdentification of PSF extents in both years

Map preparation for peat swamp forests extents

(2000 & 2010)

Field inventory

Plot-to-image sampling

Development of carbon stocks model

Carbon stocks monitoring/mapping

Carbon stocks changes assessment

Validation & Verification

Report preparations

Carbon Stocks Mapping- Using carbon stocks equation

derived from inventory data and SAR signal

SPOT image(2000 & 2010)

SAR image(2000 & 2010)

Output Matrix

Objectives Activities Expected Outputs

To update and map the current extents of peat swamp forest in Peninsular Malaysia,

Acquisitions of satellite and ancillary data A Geographic Information System (GIS) database comprise data layers that indicate previous, current, and changes of extents of peat swamps forests in Peninsular Malaysia,

Satellite image pre-processing

Satellite image classification for delineating peat swamp forests

Map preparation for peat swamp forests extents.

To quantify extents and changes of carbon stocks from year 2000 to 2010 on peat swamp forest,

Field inventory A model, which correlates ground measurement carbon stocks and SAR digital signal number. This model can be a carbon stocks predictor for all peat swamp forests in Malaysia and can be used to update or carbon monitoring in the future,

Plot-to-image sampling

Development of carbon stocks estimation equation

Carbon stocks monitoring

To generate spatially distributed map of carbon stock on peat swamp forest over Peninsular Malaysia, and

Gather information derived from objective (i) and (ii)

Thematic maps that indicate previous, current and changes of stored carbon in peat swamp forests in Peninsular Malaysia, Carbon stocks mapping

To demonstrate the use of remote sensing techniques in carbon stocks monitoring for the REDD reporting.

Carbon stocks changes assessment A project complete report, which will include the readiness for REDD.

Validation & Verification

Report preparations

RESEARCH ON DEVELOPMENT OF FOREST

CARBON MONITORING METHODOLOGIES

FOR REDD+ IN MALAYSIA

A Collaboration between: Forestry And Forest Products Research Institute (FFPRI), Japan

&Malaysian Forestry Research & Development Board (MFRDB): Forest Research Institute Malaysia (FRIM), Malaysia

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The research aims the following outputs;

i. Land-use and land-use change MRV by satellite remote sensing

ii.Forest carbon change MRV by combination of remote sensing and ground measurements

iii.Social and/or economic drivers of deforestation/forest degradation

iv.Guidelines for development of forest carbon change MRV systems for tropical forest countries

Methdology

Series of satellites data (Landsat TM/ETM+, SPOT XS,

PALSAR)

1995 - 2010

Biomass & Carbon stocks measurements from

permanent sampling plots (PSPs)

Changes in forest area of all forest types :

Inland forest

Peat Swamp forest

Mangrove forest

Plantations forest

Changes in averaged stocks of all forest types

Carbon stocks changes

∑ (Forest areai x Averaged carbon stocki) = Total carbon stocks

REDD+ Malaysia’s Perspectives

Malaysia’sView on REDD

Are we Ready?

“Readiness” is normally focused on the following national-level priority issues.

• Preparation of national strategies to reduce emissions through local stakeholder consultations,

• Institutional, technical, human capacity building,• Designing/implementing Monitoring, Reporting, and Verification

(MRV) systems, and national forest carbon accounting systems,• Developing national systems for determining baselines and

Reference Emissions Levels,• Transparent, equitable and accountable benefit sharing

mechanisms,• Developing safeguards and grievance mechanisms to protect

the interests of forest communities and the poor• Clarify national land, forest and carbon tenure rights.

Common threads and difficulties

• Inconsistency between criteria of the different programmes

• Excessive demand coupled with insufficient funds

• Incompatibility with national circumstances• Conditions and eligibility criteria• Calls for commitment to an as-yet undefined

instrument

Issues

It is very important to note that any notion of a cap on deforestation has deep and long-lasting implications for developing countries that:

• Have large and growing populations to feed • May already have converted large forest areas (i.e

to agriculture) for this purpose• Need to convert land for housing, industry and

infrastructure as identified as a priority in the Convention

• Need to eradicate poverty

Changes in forests land between 1980 and 2008 with projections to 2020 (Abdul Rashid et al. 2009)

Outstanding issues

• Degradation – the second „D‟ in REDD

• Regulating the voluntary sector

• Aligning REDD with Adaptation

• Resolving competing claims on forests

• Reforming forest governance

Common activities causing forest degradation in the tropics include (GOFC-GOLD, 2008):

• Selective logging• Large-scale and open forest fires• Over exploited of non-timber forest

products and wood for fuel• Shifting cultivation and mining

Challenge How do we measure forest degradation?

Use of remote sensing in MRV due to the forest degradation: Opportunity or challenge?

(GOFC-GOLD, 2008)

• COP -13 in 2007 in Bali outlined possible alternatives to REDD as climate change measure:i. Role of conservation ii. Sustainable forest management (SFM)iii.Enhancement of carbon stocks in developing

countries• Malaysia is now streamlining efforts and

strategies towards conserving and managing it‟s forest on a sustainable basis.

• Malaysia feels that the definitions of deforestation needs to be broad enough to cover various levels and patterns of forest degradation.

Conclusion

Malaysia welcomes early discussion on REDD, which is widely recognized as a highly cost effective method of emissions reduction.

In this regard, Malaysia would like to urge Parties to adopt a positive attitude in negotiations on this matter and support and facilitate the development of a simple and flexible mechanism that will benefit not only the developing countries but more importantly the global climate system.

REDDLong way to go…

Photo: Hamdan O.

THANK YOU