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MAPPING OF CITES-LISTED ENDANGERED TROPICAL PEAT SWAMP MAPPING OF CITES-LISTED ENDANGERED TROPICAL PEAT SWAMP FOREST TREE SPECIES USING AIRBORNE HYPERSPECTRAL FOREST TREE SPECIES USING AIRBORNE HYPERSPECTRAL
SENSORSENSOR
Khali Aziz Hamzah, Mohd Azahari Faidi and Hamdan OmarKhali Aziz Hamzah, Mohd Azahari Faidi and Hamdan OmarForest Research Institute Malaysia (FRIM)Forest Research Institute Malaysia (FRIM)
ASIA GEOSPATIAL FORUM 17 – 19 SEPTEMBER 2012, HANOI, VIETNAMASIA GEOSPATIAL FORUM 17 – 19 SEPTEMBER 2012, HANOI, VIETNAM
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1.1. IntroductionIntroduction
2.2. The ProjectThe Project
3.3. Result and Discussion Result and Discussion
4.4. ConclusionConclusion
PRESENTATION OUTLINEPRESENTATION OUTLINE
MALAYSIA – FOREST AREAMALAYSIA – FOREST AREA
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• Malaysia total land area - about 328,300 km2
• About 59.5% (19.52 million ha) is still under forest cover
Region Land area (mil ha)
Natural Forest Types Plantation forest
Total Forested
land
% of total land Area
Dry inland
Swamp forest
Mangrove forest
Pen. Malaysia
13.16 5.40 0.30 0.10 0.08 5.88 44.7
Sabah 7.37 3.83 0.12 0.34 0.11 4.40 59.7Sarawak 12.30 7.92 1.12 0.14 0.06 9.24 75.1Total (Malaysia)
32.83 17.15 1.54 0.58 0.25 19.52 59.5
South China SeaSouth China Sea
Strait Of Malacca
Strait Of Malacca
Sulu SeaSulu Sea
MALAYSIA – FOREST MAPMALAYSIA – FOREST MAP
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• Ramin (Ramin (Gonystylus bancanusGonystylus bancanus) is an endangered peat ) is an endangered peat swamp forest speciesswamp forest species
• It has been listed in Appendix ll of the Convention on It has been listed in Appendix ll of the Convention on International Trade in Endangered Species of Wild International Trade in Endangered Species of Wild Fauna and Flora (CITES) Fauna and Flora (CITES)
• There is a need to identify the ramin population in the There is a need to identify the ramin population in the natural habitat for management purposesnatural habitat for management purposes
ISSUESISSUES
• Scientific name: Gonystylus bancanus• Family: Thymelaeaceae• Local name: Ramin• Brief description: large tree and can grow up to
40 m in height• Uses: timber for high quality furniture• Ecology: gregarious in peat swamp forests
ABOUT THE SPECIES
fruits
seedling
flower
timberstree
Ramin – Gonystylus bancanus
RESEARCH RESEARCH JUSTIFICATIONJUSTIFICATION
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• To identify and locate ramin trees in a highly To identify and locate ramin trees in a highly mixed peat swamp forest is a challenging mixed peat swamp forest is a challenging task. task.
• The ideal way is to inventories the whole The ideal way is to inventories the whole population, but this will be very expensive to population, but this will be very expensive to implement in the field. implement in the field.
• Opportunities on mapping using Opportunities on mapping using hyperspectral remote sensing technologyhyperspectral remote sensing technology
• Ramin is considered canopy layer treeRamin is considered canopy layer tree• Advantage to use airborne hyperspectral data Advantage to use airborne hyperspectral data
Forest profile of Plot E3: 39, Baccaurea bracteata; 54, Blumeodendron tokbrai; 14, 61, Calophyllum ferrugineum; 27, Calophyllum sclerophyllum; 47, Camnosperma coriaceum; 2, 33, 49, 50, Diospyros lanceifolia; 53, Diospyros maingayi; 18, 32, Durio carinatus; 3,9,17,24,Gonystylus bancanus; 21, 29, 40, Koompassia malaccensis; 15, 30, Licania splendens; 43, 58, Litsea elliptica; 36, 38, 44, 56, 60, Litsea gracilipes; 51, Litsea grandis; 12, 16, 41, Lophopetalum floribundum; 45, Lophopetalum multinervium; 6, 7, 8, 11, 20, 55, 64, Neoscortechinia forbesii; 10, Palaquium ridleyi; 22, 37, 52, Parastemon urophyllus; 23, 48, Polyalthia glauca; 5, Polyalthia hypoleuca; 1, 57, Shorea platycarpa; 13, Syzygium cerinum; 19, 26, 31, 46, Syzygium inophyllum; 34, 62, Syzygium kiahii; 25, 35, Syzygium lineatum; 4, Tetractomia majus; 59, Xantophyllum ellipticum; 28, 42, Xylopia magna.
RAMIN IN THE FOREST
THE PROJECT
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Objective:Objective:• To generate spatial distribution maps of To generate spatial distribution maps of
ramin in peat swamp forest using ramin in peat swamp forest using hyperspectral technology.hyperspectral technology.
Expected Output:Expected Output:• Spectral library, spatial distribution maps Spectral library, spatial distribution maps
and spatial database for raminand spatial database for ramin
Peat Swamp Forest, Pekan,
PahangMALAYSIA
PROJECT AREA
PEAT SWAMP FOREST DURING DRY SEASON
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PEAT SWAMP FOREST DURING WET SEASON
THE METHODOLOGY
Spectral Library
Field Survey
Ramin Distribution Map
Yes
No
Airborne Data Acquisition
Data Pre-Processing
Data Classification
Discriminating Ramin
Vectorisation
Accuracy Assessment
• X,Y location
• height
• DBH (>20cm)
• crown width
SPECTRORADIOMETER DATA COLLECTION
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Spectral RangeSpectral Range 350 nm to 1050 nm350 nm to 1050 nm
Bandwidth intervalBandwidth interval 1.5 nm1.5 nm
Technical Specifications:Technical Specifications:
AIRBORNE HYPERSPECTRAL DATA
- - Sensor : HySpex VNIR-1600Sensor : HySpex VNIR-1600- Spatial resolution, 0.5m Spatial resolution, 0.5m - - Number of bands, 160Number of bands, 160
- Spectral Range : - Spectral Range : 0.4-1μm - Swath width,1km- Swath width,1km
AIRBORNE HYPERSPECTRAL DATA
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Acquiring of airborne hyperspectral data in the study areaAcquiring of airborne hyperspectral data in the study area
HySpex V-NIR 1600HySpex V-NIR 1600Hyperspectral system installationsHyperspectral system installations
Aircraft (9M - PIH)Aircraft (9M - PIH)
RESULT & DISCUSSION
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Statistic Gonystylus bancanus
(%)
Calopyllum ferrugineum
(%)
Minimum 2.2 6.2
Maximum 57.9 59.6
Mean 26.9 31.7
SPECTRAL LIBRARY
RESULT & DISCUSSION
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AIRBORNE HYPERSPECTRAL DATA
Spectral Spectral dimensiondimension
Spatial Spatial dimensiondimension
PixelPixel
RESULT & DISCUSSION
• HySpex VNIR data cubeHySpex VNIR data cubeRamin spectral signatureRamin spectral signature Meranti Paya spectral signatureMeranti Paya spectral signature
Understory spectral signatureUnderstory spectral signature
Bintangor spectral signatureBintangor spectral signature
RESULT & DISCUSSION
• Spectral signature of selected features in hyperspectral Spectral signature of selected features in hyperspectral imagesimages
RESULT & DISCUSSION
• Correlation (ramin reflectance) between hyperspectral Correlation (ramin reflectance) between hyperspectral data and spectroradiometer measurementdata and spectroradiometer measurement
RESULT & DISCUSSION
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o Using Spectral Angle Mapper (SAM) classification technique the hyperspectral data can be used to map ramin distributions
o It was found that the It was found that the distribution of distribution of ramin ramin within within the study area is about 21 the study area is about 21 tree per ha, tree per ha,
o Mapping accuracy of 86% Mapping accuracy of 86%
RESULT & DISCUSSION
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Virgin Forest :Virgin Forest : Ramin – 491/25ha (19.64/ha)Ramin – 491/25ha (19.64/ha) Bintangor – 353/25ha (14.12/ha)Bintangor – 353/25ha (14.12/ha)
Logged Over Forest:Logged Over Forest: Ramin – 179/30ha (5.97/ha)Ramin – 179/30ha (5.97/ha) Bintangor – 50/30ha (1.67/ha)Bintangor – 50/30ha (1.67/ha)
RaminRamin - Mean height, 34.70m- Mean height, 34.70m - DBH, 21.6 – 83.5cm- DBH, 21.6 – 83.5cm
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CONCLUSION
• Spectral library of the Ramin trees has been Spectral library of the Ramin trees has been developed and can be used as reference spectral developed and can be used as reference spectral library for the future research project.library for the future research project.
• Ramin trees can be identified using hyperspectral Ramin trees can be identified using hyperspectral data with acceptable mapping accuracy (86%). data with acceptable mapping accuracy (86%).
• Inventory of Ramin can be carried out faster.Inventory of Ramin can be carried out faster.
• The availability of accurate information on ramin The availability of accurate information on ramin population from this study can be used to assist in population from this study can be used to assist in designing rehabilitation and conservation programs designing rehabilitation and conservation programs in order to conserve and sustainably manage this in order to conserve and sustainably manage this species in line with the CITES requirements.species in line with the CITES requirements.
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This work was made possible by a grant from ITTO under its collaborative program with CITES and Malaysia This work was made possible by a grant from ITTO under its collaborative program with CITES and Malaysia to build capacity for implementing timber listings. Donors to this collaborative program include the EU (primary to build capacity for implementing timber listings. Donors to this collaborative program include the EU (primary
donor), the USA, Japan, Norway, New Zealand and Switzerland.donor), the USA, Japan, Norway, New Zealand and Switzerland.
AcknowledgementsAcknowledgements
Thank YouThank You