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Khali Aziz Hamzah, Mohd Azahari Faidi and Hamdan Omar

MAPPING OF CITES-LISTED ENDANGERED TROPICAL PEAT SWAMP FOREST TREE SPECIES USING AIRBORNE HYPERSPECTRAL SENSOR. Khali Aziz Hamzah, Mohd Azahari Faidi and Hamdan Omar Forest Research Institute Malaysia (FRIM). ASIA GEOSPATIAL FORUM 17 – 19 SEPTEMBER 2012, HANOI, VIETNAM.

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Khali Aziz Hamzah, Mohd Azahari Faidi and Hamdan Omar

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  1. MAPPING OF CITES-LISTED ENDANGERED TROPICAL PEAT SWAMP FOREST TREE SPECIES USING AIRBORNE HYPERSPECTRAL SENSOR Khali Aziz Hamzah, MohdAzahariFaidi and Hamdan Omar Forest Research Institute Malaysia (FRIM) ASIA GEOSPATIAL FORUM 17 – 19 SEPTEMBER 2012, HANOI, VIETNAM

  2. PRESENTATION OUTLINE • Introduction • The Project • Result and Discussion • Conclusion

  3. MALAYSIA – FOREST AREA 3 Malaysia total land area - about 328,300 km2 About 59.5% (19.52 million ha) is still under forest cover

  4. MALAYSIA – FOREST MAP Sulu Sea South China Sea Strait Of Malacca

  5. ISSUES Ramin (Gonystylusbancanus) is an endangered peat swamp forest species It has been listed in Appendix ll of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) There is a need to identify the ramin population in the natural habitat for management purposes 5

  6. ABOUT THE SPECIES • 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

  7. Ramin – Gonystylus bancanus fruits seedling flower tree timbers

  8. RESEARCH JUSTIFICATION 8 To identify and locate ramin trees in a highly mixed peat swamp forest is a challenging task. The ideal way is to inventories the whole population, but this will be very expensive to implement in the field. Opportunities on mapping using hyperspectral remote sensing technology

  9. RAMIN IN THE FOREST • Ramin is considered canopy layer tree • 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.

  10. THE PROJECT Objective: • To generate spatial distribution maps of ramin in peat swamp forest using hyperspectral technology. Expected Output: • Spectral library, spatial distribution maps and spatial database for ramin

  11. Peat Swamp Forest, Pekan, PahangMALAYSIA PROJECT AREA

  12. PEAT SWAMP FOREST DURING DRY SEASON

  13. PEAT SWAMP FOREST DURING WET SEASON

  14. THE METHODOLOGY Accuracy Assessment Airborne Data Acquisition Field Survey Data Pre-Processing Spectral Library Data Classification • X,Y location • height • DBH (>20cm) • crown width Discriminating Ramin Vectorisation No Yes Ramin Distribution Map

  15. SPECTRORADIOMETER DATA COLLECTION Technical Specifications:

  16. AIRBORNE HYPERSPECTRAL DATA • - Sensor : HySpex VNIR-1600 • Spatial resolution, 0.5m - Number of bands, 160 • - Spectral Range : 0.4-1μm - Swath width,1km

  17. AIRBORNE HYPERSPECTRAL DATA Acquiring of airborne hyperspectral data in the study area Aircraft (9M - PIH) HySpex V-NIR 1600 Hyperspectral system installations 17

  18. RESULT & DISCUSSION SPECTRAL LIBRARY

  19. RESULT & DISCUSSION AIRBORNE HYPERSPECTRAL DATA

  20. RESULT & DISCUSSION • HySpex VNIR data cube Ramin spectral signature MerantiPaya spectral signature Pixel Understory spectral signature Spectral dimension Bintangor spectral signature Spatial dimension

  21. RESULT & DISCUSSION • Spectral signature of selected features in hyperspectral images

  22. RESULT & DISCUSSION • Correlation (ramin reflectance) between hyperspectral data and spectroradiometer measurement

  23. RESULT & DISCUSSION • Using Spectral Angle Mapper (SAM) classification technique the hyperspectral data can be used to map ramin distributions • It was found that the distribution of raminwithin the study area is about 21 tree per ha, • Mapping accuracy of 86%

  24. RESULT & DISCUSSION Ramin - Mean height, 34.70m - DBH, 21.6 – 83.5cm Virgin Forest : Ramin – 491/25ha (19.64/ha) Bintangor – 353/25ha (14.12/ha) Logged Over Forest: Ramin – 179/30ha (5.97/ha) Bintangor – 50/30ha (1.67/ha) 24

  25. CONCLUSION 25 Spectral library of the Ramin trees has been developed and can be used as reference spectral library for the future research project. Ramin trees can be identified using hyperspectral data with acceptable mapping accuracy (86%). Inventory of Ramin can be carried out faster. The availability of accurate information on ramin population from this study can be used to assist in designing rehabilitation and conservation programs in order to conserve and sustainably manage this species in line with the CITES requirements.

  26. Thank You Acknowledgements 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 donor), the USA, Japan, Norway, New Zealand and Switzerland.

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