Forest Fire Risk Zonation Mapping Using GIS Techniques

Amit Kumar Verma

ISBN 10: 620615050X / ISBN 13: 9786206150503

Published by LAP LAMBERT Academic Publishing Jun 2023, 2023

About this Item

Neuware -In this book we have provided information on how to identify forest fire risk zones by analyzing historical fire incidences along with influencive biophysical parameters responsible for forest fire for a particular landscape using GIS techniques. Forest fire risk zones were delineated by assigning subjective weights to the classes of all the parameters according to their sensitivity to fire or their fire-inducing capability. Two categories of fire sensitive regions such as most sensitive and sensitive fire intensity zones were identified. The result shows that almost 20% of the study area was predicted to be under most sensitive. The evolved GIS-based forest fire risk model of the study area was found to be in strong agreement with actual fire-affected sites. Such study can help in preparing base map for preparatory planning for forest fire management for a particular area.Books on Demand GmbH, Überseering 33, 22297 Hamburg 88 pp. Englisch.

Seller Inventory # 9786206150503

Bibliographic Details

• Title: Forest Fire Risk Zonation Mapping Using GIS Techniques
• Publisher: LAP LAMBERT Academic Publishing Jun 2023
• Publication Date: 2023
• Language: English
• ISBN 10: 620615050X
• ISBN 13: 9786206150503
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 6D millimeters 220 millimeters width by 150 millimeters height by 6 millimeters depth
• Weight: 149 grams

About this title

Synopsis

In this book we have provided information on how to identify forest fire risk zones by analyzing historical fire incidences along with influencive biophysical parameters responsible for forest fire for a particular landscape using GIS techniques. Forest fire risk zones were delineated by assigning subjective weights to the classes of all the parameters according to their sensitivity to fire or their fire-inducing capability. Two categories of fire sensitive regions such as most sensitive and sensitive fire intensity zones were identified. The result shows that almost 20% of the study area was predicted to be under most sensitive. The evolved GIS-based forest fire risk model of the study area was found to be in strong agreement with actual fire-affected sites. Such study can help in preparing base map for preparatory planning for forest fire management for a particular area.