Satellite Remote Sensing Technology for Forest Type Classification and Inventory in Gunung Stong Forest Reserve, Kelantan, Malaysia

In Malaysia and other developing countries access to the forest area is often difficult and forest information is inadequate. Remote sensing in forestry is very valuable and it has become important due to its capability to collect data from large areas and its capability to generate information. In...

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Main Author:	Khuzaimah, Zailani
Format:	Thesis
Language:	English English
Published:	2000
Subjects:	Forests and forestry - Remote sensing - Kelantan - Gunung Stong Forest Reserve
Online Access:	http://psasir.upm.edu.my/id/eprint/10026/1/FH_2000_10_IR.pdf
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id	my-upm-ir.10026
record_format	uketd_dc
spelling	my-upm-ir.100262023-12-06T03:41:38Z Satellite Remote Sensing Technology for Forest Type Classification and Inventory in Gunung Stong Forest Reserve, Kelantan, Malaysia 2000-11 Khuzaimah, Zailani In Malaysia and other developing countries access to the forest area is often difficult and forest information is inadequate. Remote sensing in forestry is very valuable and it has become important due to its capability to collect data from large areas and its capability to generate information. In other words, remote sensing technology offers reliable information essential for forest management and inventory. The objective of this study is to develop a technique for preliminary estimation of timber volume using satellite remote sensing imagery. Based on data analysis of the Landsat TM imagery, six classes of land cover were classified such as Primary Forest, Logged-Over Forest, Degraded Forest/ Plantation, Shrub, Barren Land / Cloud and Water Bodies/ Shadow. Using a forest canopy density technique, three volume intensity categories can be mapped out such as High Density (>35 m3 - 100 m3/ha) , Medium Density (20 m3 - 35 m3/ha) and Low Density (below 20 m3/ha) with an overall accuracy assessment of about 97.30 percent. The results of these studies imply that Malaysian loggers can now utilize these maps to have a preliminary estimate of the timber volume in the concession areas without really "flying over" the inaccessible sites. Consequently from the government's point of view, preliminary estimate of the concession fees can now be imposed on the loggers. It can be concluded that satellite remote sensing (i.e. Landsat TM) can be successfully used in forest type classification and inventory for macro-forest planning in Malaysia. However, high resolution satellite remote sensing data such as IKONOS- 1 or THEMAP airborne data taken from aircraft should be further investigated for micro-planning in forest management due to its high resolution capability for individual tree counting and mapping. Forests and forestry - Remote sensing - Kelantan - Gunung Stong Forest Reserve 2000-11 Thesis http://psasir.upm.edu.my/id/eprint/10026/ http://psasir.upm.edu.my/id/eprint/10026/1/FH_2000_10_IR.pdf text en public masters Universiti Putra Malaysia Forests and forestry - Remote sensing - Kelantan - Gunung Stong Forest Reserve 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 - Kelantan - Gunung Stong Forest Reserve
spellingShingle	Forests and forestry - Remote sensing - Kelantan - Gunung Stong Forest Reserve Khuzaimah, Zailani Satellite Remote Sensing Technology for Forest Type Classification and Inventory in Gunung Stong Forest Reserve, Kelantan, Malaysia
description	In Malaysia and other developing countries access to the forest area is often difficult and forest information is inadequate. Remote sensing in forestry is very valuable and it has become important due to its capability to collect data from large areas and its capability to generate information. In other words, remote sensing technology offers reliable information essential for forest management and inventory. The objective of this study is to develop a technique for preliminary estimation of timber volume using satellite remote sensing imagery. Based on data analysis of the Landsat TM imagery, six classes of land cover were classified such as Primary Forest, Logged-Over Forest, Degraded Forest/ Plantation, Shrub, Barren Land / Cloud and Water Bodies/ Shadow. Using a forest canopy density technique, three volume intensity categories can be mapped out such as High Density (>35 m3 - 100 m3/ha) , Medium Density (20 m3 - 35 m3/ha) and Low Density (below 20 m3/ha) with an overall accuracy assessment of about 97.30 percent. The results of these studies imply that Malaysian loggers can now utilize these maps to have a preliminary estimate of the timber volume in the concession areas without really "flying over" the inaccessible sites. Consequently from the government's point of view, preliminary estimate of the concession fees can now be imposed on the loggers. It can be concluded that satellite remote sensing (i.e. Landsat TM) can be successfully used in forest type classification and inventory for macro-forest planning in Malaysia. However, high resolution satellite remote sensing data such as IKONOS- 1 or THEMAP airborne data taken from aircraft should be further investigated for micro-planning in forest management due to its high resolution capability for individual tree counting and mapping.
format	Thesis
qualification_level	Master's degree
author	Khuzaimah, Zailani
author_facet	Khuzaimah, Zailani
author_sort	Khuzaimah, Zailani
title	Satellite Remote Sensing Technology for Forest Type Classification and Inventory in Gunung Stong Forest Reserve, Kelantan, Malaysia
title_short	Satellite Remote Sensing Technology for Forest Type Classification and Inventory in Gunung Stong Forest Reserve, Kelantan, Malaysia
title_full	Satellite Remote Sensing Technology for Forest Type Classification and Inventory in Gunung Stong Forest Reserve, Kelantan, Malaysia
title_fullStr	Satellite Remote Sensing Technology for Forest Type Classification and Inventory in Gunung Stong Forest Reserve, Kelantan, Malaysia
title_full_unstemmed	Satellite Remote Sensing Technology for Forest Type Classification and Inventory in Gunung Stong Forest Reserve, Kelantan, Malaysia
title_sort	satellite remote sensing technology for forest type classification and inventory in gunung stong forest reserve, kelantan, malaysia
granting_institution	Universiti Putra Malaysia
granting_department	Faculty of Forestry
publishDate	2000
url	http://psasir.upm.edu.my/id/eprint/10026/1/FH_2000_10_IR.pdf
_version_	1794018858632216576

Satellite Remote Sensing Technology for Forest Type Classification and Inventory in Gunung Stong Forest Reserve, Kelantan, Malaysia

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