Peat swamp forest fire hazard areas were identified and mapped by integrating GIS‐grid‐based and multi‐criteria analysis to provide valuable information about the areas most likely to be affected by fire in the Pekan District, south of Pahang, Malaysia. A spatially weighted index model was implemented to develop the fire hazard assessment model used in this study. Fire‐causing factors such as land use, road network, slope, aspect and elevation data were used in this application. A two‐mosaic Landsat TM scene was used to extract land use parameters of the study area. A triangle irregular network was generated from the digitized topographic map to produce a slope risk map, an aspect risk map and an elevation risk map. Spatial analysis was applied to reclassify and overlay all grid hazard maps to produce a final peat swamp forest fire hazard map. To validate the model, the actual fire occurrence map was compared with the fire hazard zone area derived from the model. The model can be used only for specific areas, and other criteria should be considered if the model is used for other areas. The results show that most of the actual fire spots are located in very high and high fire risk zones identified by the model.
Article navigation
1 December 2004
Review Article|
December 01 2004
GIS‐grid‐based and multi‐criteria analysis for identifying and mapping peat swamp forest fire hazard in Pahang, Malaysia Available to Purchase
Iwan Setiawan;
Iwan Setiawan
GIS & Geomatic Laboratory, Department of Civil Engineering, Faculty of Engineering, University Putra Malaysia, Serdang, Malaysia.
Search for other works by this author on:
A.R. Mahmud;
A.R. Mahmud
GIS & Geomatic Laboratory, Department of Civil Engineering, Faculty of Engineering, University Putra Malaysia, Serdang, Malaysia.
Search for other works by this author on:
S. Mansor;
S. Mansor
GIS & Geomatic Laboratory, Department of Civil Engineering, Faculty of Engineering, University Putra Malaysia, Serdang, Malaysia.
Search for other works by this author on:
A.R. Mohamed Shariff;
A.R. Mohamed Shariff
GIS & Geomatic Laboratory, Department of Civil Engineering, Faculty of Engineering, University Putra Malaysia, Serdang, Malaysia.
Search for other works by this author on:
A.A. Nuruddin
A.A. Nuruddin
GIS & Geomatic Laboratory, Department of Civil Engineering, Faculty of Engineering, University Putra Malaysia, Serdang, Malaysia.
Search for other works by this author on:
Publisher: Emerald Publishing
Online ISSN: 1758-6100
Print ISSN: 0965-3562
© Emerald Group Publishing Limited
2004
Disaster Prevention and Management: An International Journal (2004) 13 (5): 379–386.
Citation
Setiawan I, Mahmud A, Mansor S, Mohamed Shariff A, Nuruddin A (2004), "GIS‐grid‐based and multi‐criteria analysis for identifying and mapping peat swamp forest fire hazard in Pahang, Malaysia". Disaster Prevention and Management: An International Journal, Vol. 13 No. 5 pp. 379–386, doi: https://doi.org/10.1108/09653560410568507
Download citation file:
Suggested Reading
Forest fire susceptibility and risk mapping using remote sensing and geographical information systems (GIS)
Disaster Prevention and Management: An International Journal (June,2007)
Fuzzy AHP for forest fire risk modeling
Disaster Prevention and Management: An International Journal (April,2012)
Modelling fuel moisture under climate change
International Journal of Climate Change Strategies and Management (March,2011)
Human factors influencing fire safety measures
Disaster Prevention and Management: An International Journal (April,2004)
Using geographic information systems in assessment of major hazards of liquefied petroleum gas
Disaster Prevention and Management: An International Journal (April,2004)
Related Chapters
How is a geotechnical finite element analysis set up?
Geotechnical Finite Element Analysis: A practical guide
How are constitutive models selected?
Geotechnical Finite Element Analysis: A practical guide
How are soil and rock parameters obtained?
Geotechnical Finite Element Analysis: A practical guide
Recommended for you
These recommendations are informed by your reading behaviors and indicated interests.
