Assessment of Microw Ave Remote Sensing Technology (Nasa's Airsar-Topsar Data) for Forest Type Classification on Tioman Island, Pahang, Malaysia

Active microwave remote sensing is able to provide information about land surface and forest canopy that would otherwise be unobtainable in regions where cloud cover and darkness prevail. The general objective of this study is to assess the capability and applicability of NASA's airborne SAR...

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Main Author:	Sebastian, Chew
Format:	Thesis
Language:	English English
Published:	2000
Subjects:	Forests and forestry - Remote sensing - Pahang - Tioman Island
Online Access:	http://psasir.upm.edu.my/id/eprint/10001/1/FH_2000_1_IR.pdf
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id	my-upm-ir.10001
record_format	uketd_dc
spelling	my-upm-ir.100012023-12-06T01:51:37Z Assessment of Microw Ave Remote Sensing Technology (Nasa's Airsar-Topsar Data) for Forest Type Classification on Tioman Island, Pahang, Malaysia 2000-06 Sebastian, Chew Active microwave remote sensing is able to provide information about land surface and forest canopy that would otherwise be unobtainable in regions where cloud cover and darkness prevail. The general objective of this study is to assess the capability and applicability of NASA's airborne SAR (AirSAR) data to classify and map tropical forests utilizing the Environment for Visualizing Images (ENVI) image processing software. The specific objectives are to test the applicability of TOPSAR in classifying forest types of Tioman Island applying standard classification method, generate a digital topographic map, generate a DEM of the study site and produce a forest-type map of Tioman Island. The island is approximately 13,354 hectares. AirSAR's Topographic SAR (TOPSAR) data of the entire island comprising of two strips were acquired on a 3rd December 1996 flight mission. Prior to analysis, the image had to be despeckled to remove noise. Five adaptive filters were used and the Gamma filter with an 11x11 window produced the best visual results after initially applying image contrast stretching. Preliminary ground survey revealed that the island has at least five main vegetation types identified as primary forest, beach forest, secondary forest, coconut palm plantation and mangrove forest. Two methods of interpretation were applied. In the first method, visual interpretation was initially applied where distinct different tones and texture were designated as a "Region of Interest" (ROI) for signature extraction. 16 ROIs were created to represent four vegetation covers and polarization signatures for each ROI were generated. Extracted polarization signatures showed no specific signature or pattern for a particular known forest type. The second method, unsupervised classification, initially yielded 10 classification classes. However, only two land cover classes were readily distinguished and these could be classified as primary and secondary forests. An additional classification obtained is cleared land or developed land. It is therefore suggested that fully Polarimetric SAR data be used together with the TOPSAR. Forests and forestry - Remote sensing - Pahang - Tioman Island 2000-06 Thesis http://psasir.upm.edu.my/id/eprint/10001/ http://psasir.upm.edu.my/id/eprint/10001/1/FH_2000_1_IR.pdf text en public masters Universiti Putra Malaysia Forests and forestry - Remote sensing - Pahang - Tioman Island Faculty of Forestry Jusoff, Kamaruzaman English
institution	Universiti Putra Malaysia
collection	PSAS Institutional Repository
language	English English
advisor	Jusoff, Kamaruzaman
topic	Forests and forestry - Remote sensing - Pahang - Tioman Island
spellingShingle	Forests and forestry - Remote sensing - Pahang - Tioman Island Sebastian, Chew Assessment of Microw Ave Remote Sensing Technology (Nasa's Airsar-Topsar Data) for Forest Type Classification on Tioman Island, Pahang, Malaysia
description	Active microwave remote sensing is able to provide information about land surface and forest canopy that would otherwise be unobtainable in regions where cloud cover and darkness prevail. The general objective of this study is to assess the capability and applicability of NASA's airborne SAR (AirSAR) data to classify and map tropical forests utilizing the Environment for Visualizing Images (ENVI) image processing software. The specific objectives are to test the applicability of TOPSAR in classifying forest types of Tioman Island applying standard classification method, generate a digital topographic map, generate a DEM of the study site and produce a forest-type map of Tioman Island. The island is approximately 13,354 hectares. AirSAR's Topographic SAR (TOPSAR) data of the entire island comprising of two strips were acquired on a 3rd December 1996 flight mission. Prior to analysis, the image had to be despeckled to remove noise. Five adaptive filters were used and the Gamma filter with an 11x11 window produced the best visual results after initially applying image contrast stretching. Preliminary ground survey revealed that the island has at least five main vegetation types identified as primary forest, beach forest, secondary forest, coconut palm plantation and mangrove forest. Two methods of interpretation were applied. In the first method, visual interpretation was initially applied where distinct different tones and texture were designated as a "Region of Interest" (ROI) for signature extraction. 16 ROIs were created to represent four vegetation covers and polarization signatures for each ROI were generated. Extracted polarization signatures showed no specific signature or pattern for a particular known forest type. The second method, unsupervised classification, initially yielded 10 classification classes. However, only two land cover classes were readily distinguished and these could be classified as primary and secondary forests. An additional classification obtained is cleared land or developed land. It is therefore suggested that fully Polarimetric SAR data be used together with the TOPSAR.
format	Thesis
qualification_level	Master's degree
author	Sebastian, Chew
author_facet	Sebastian, Chew
author_sort	Sebastian, Chew
title	Assessment of Microw Ave Remote Sensing Technology (Nasa's Airsar-Topsar Data) for Forest Type Classification on Tioman Island, Pahang, Malaysia
title_short	Assessment of Microw Ave Remote Sensing Technology (Nasa's Airsar-Topsar Data) for Forest Type Classification on Tioman Island, Pahang, Malaysia
title_full	Assessment of Microw Ave Remote Sensing Technology (Nasa's Airsar-Topsar Data) for Forest Type Classification on Tioman Island, Pahang, Malaysia
title_fullStr	Assessment of Microw Ave Remote Sensing Technology (Nasa's Airsar-Topsar Data) for Forest Type Classification on Tioman Island, Pahang, Malaysia
title_full_unstemmed	Assessment of Microw Ave Remote Sensing Technology (Nasa's Airsar-Topsar Data) for Forest Type Classification on Tioman Island, Pahang, Malaysia
title_sort	assessment of microw ave remote sensing technology (nasa's airsar-topsar data) for forest type classification on tioman island, pahang, malaysia
granting_institution	Universiti Putra Malaysia
granting_department	Faculty of Forestry
publishDate	2000
url	http://psasir.upm.edu.my/id/eprint/10001/1/FH_2000_1_IR.pdf
_version_	1794018856444887040

Assessment of Microw Ave Remote Sensing Technology (Nasa's Airsar-Topsar Data) for Forest Type Classification on Tioman Island, Pahang, Malaysia

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