Forest Fire Hazard Rating Assessment In Peat Swamp Forest Using Integrated Remote Sensing And Geographical Information System

Forest fire can be a real disaster, regardless of their causes, be it human activity or nature. While it is difficult to control nature, it is possible to map different hazard levels thereby minimizing fire hazards and avoid potential damage. Satellite data plays an important role in detecting and m...

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Main Author:	Mohd Razali, Sheriza
Format:	Thesis
Language:	English English
Published:	2007
Subjects:	Forest fires - Prevention and control - Remote sensing - Case studies Forest fires - Prevention and control - Geographic information systems - Case studies
Online Access:	http://psasir.upm.edu.my/id/eprint/5070/1/FH_2007_6.pdf
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id	my-upm-ir.5070
record_format	uketd_dc
spelling	my-upm-ir.50702013-05-27T07:20:12Z Forest Fire Hazard Rating Assessment In Peat Swamp Forest Using Integrated Remote Sensing And Geographical Information System 2007 Mohd Razali, Sheriza Forest fire can be a real disaster, regardless of their causes, be it human activity or nature. While it is difficult to control nature, it is possible to map different hazard levels thereby minimizing fire hazards and avoid potential damage. Satellite data plays an important role in detecting and mapping forest fires, involving different types of vegetation. This study was conducted with two objectives: first by applying remote sensing techniques to delineate fuel types map and burnt areas in peat swamp forest; secondly was to develop a fire hazard modelling and mapping of fire hazard rating areas using the Geographical Information System (GIS). A fire prone peat swamp forest located in Penor, Pahang was selected for the study. A colour composite image from Landsat Thematic Mapper (TM) was transformed using Tasseled Cap Transformation (TC) and a fuel types map was produced. Roads and canal were digitized and developed as layers using ArcGIS 8.2. These layers were composite and four categories of forest fire hazard ranging from extreme to null were automatically derived. The final forest fire hazard rating map is presented in ArcView 3.1. In conclusion, almost 50% of the study areas were classified as ‘low’ hazard and only 10% of the areas were classified as ‘extreme’ hazard. As a result, the fire hazard map can be used for better forest fire management activities for that area. Forest fires - Prevention and control - Remote sensing - Case studies Forest fires - Prevention and control - Geographic information systems - Case studies 2007 Thesis http://psasir.upm.edu.my/id/eprint/5070/ http://psasir.upm.edu.my/id/eprint/5070/1/FH_2007_6.pdf application/pdf en public masters Universiti Putra Malaysia Forest fires - Prevention and control - Remote sensing - Case studies Forest fires - Prevention and control - Geographic information systems - Case studies Faculty Forestry English
institution	Universiti Putra Malaysia
collection	PSAS Institutional Repository
language	English English
topic	Forest fires - Prevention and control - Remote sensing - Case studies Forest fires - Prevention and control - Geographic information systems - Case studies
spellingShingle	Forest fires - Prevention and control - Remote sensing - Case studies Forest fires - Prevention and control - Geographic information systems - Case studies Mohd Razali, Sheriza Forest Fire Hazard Rating Assessment In Peat Swamp Forest Using Integrated Remote Sensing And Geographical Information System
description	Forest fire can be a real disaster, regardless of their causes, be it human activity or nature. While it is difficult to control nature, it is possible to map different hazard levels thereby minimizing fire hazards and avoid potential damage. Satellite data plays an important role in detecting and mapping forest fires, involving different types of vegetation. This study was conducted with two objectives: first by applying remote sensing techniques to delineate fuel types map and burnt areas in peat swamp forest; secondly was to develop a fire hazard modelling and mapping of fire hazard rating areas using the Geographical Information System (GIS). A fire prone peat swamp forest located in Penor, Pahang was selected for the study. A colour composite image from Landsat Thematic Mapper (TM) was transformed using Tasseled Cap Transformation (TC) and a fuel types map was produced. Roads and canal were digitized and developed as layers using ArcGIS 8.2. These layers were composite and four categories of forest fire hazard ranging from extreme to null were automatically derived. The final forest fire hazard rating map is presented in ArcView 3.1. In conclusion, almost 50% of the study areas were classified as ‘low’ hazard and only 10% of the areas were classified as ‘extreme’ hazard. As a result, the fire hazard map can be used for better forest fire management activities for that area.
format	Thesis
qualification_level	Master's degree
author	Mohd Razali, Sheriza
author_facet	Mohd Razali, Sheriza
author_sort	Mohd Razali, Sheriza
title	Forest Fire Hazard Rating Assessment In Peat Swamp Forest Using Integrated Remote Sensing And Geographical Information System
title_short	Forest Fire Hazard Rating Assessment In Peat Swamp Forest Using Integrated Remote Sensing And Geographical Information System
title_full	Forest Fire Hazard Rating Assessment In Peat Swamp Forest Using Integrated Remote Sensing And Geographical Information System
title_fullStr	Forest Fire Hazard Rating Assessment In Peat Swamp Forest Using Integrated Remote Sensing And Geographical Information System
title_full_unstemmed	Forest Fire Hazard Rating Assessment In Peat Swamp Forest Using Integrated Remote Sensing And Geographical Information System
title_sort	forest fire hazard rating assessment in peat swamp forest using integrated remote sensing and geographical information system
granting_institution	Universiti Putra Malaysia
granting_department	Faculty Forestry
publishDate	2007
url	http://psasir.upm.edu.my/id/eprint/5070/1/FH_2007_6.pdf
_version_	1747810344428896256

Forest Fire Hazard Rating Assessment In Peat Swamp Forest Using Integrated Remote Sensing And Geographical Information System

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