Mapping Forest Fire Risk Zones using Geospatial Tools : A risk assessment study in Manipur, India

Kanchan Puri, Ritesh Joshi

ISBN 10: 6139956447 / ISBN 13: 9786139956449

Published by LAP LAMBERT Academic Publishing, 2019

About this Item

Zustand: Sehr gut | Seiten: 56 | Sprache: Englisch | Produktart: Bücher | Fires have been a major agent of environmental change and forest fires are a major cause of changes in forest structure and function. Among various floristic regions, the northeast region suffers maximum from the fires due to the age-old practice of shifting cultivation and spread of fires from jhum fields. For proper mitigation and management, an early warning of forest fires through risk modelling is required. The present study demonstrates the potential use of remote sensing and Geographic Information System (GIS) in identifying forest fire prone areas in Manipur, southeastern part of Northeast India. Land use land cover (LULC), vegetation type, Digital elevation model (DEM), slope, aspect and proximity to roads and settlements; factors that influence the behavior of fire, were used to model the forest fire risk zones. Each class of the layers was given weight according to their fire inducing capability and their sensitivity to fire. Weighted sum modelling and ISODATA clustering was used to classify the fire zones.

Seller Inventory # 33516167/2

Bibliographic Details

• Title: Mapping Forest Fire Risk Zones using Geospatial Tools : A risk assessment study in Manipur, India
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2019
• Language: English
• ISBN 10: 6139956447
• ISBN 13: 9786139956449
• Binding: Soft cover
• Condition: Sehr gut
• Seller catalogs:
  • Bücher

About this title

Synopsis

Fires have been a major agent of environmental change and forest fires are a major cause of changes in forest structure and function. Among various floristic regions, the northeast region suffers maximum from the fires due to the age-old practice of shifting cultivation and spread of fires from jhum fields. For proper mitigation and management, an early warning of forest fires through risk modelling is required. The present study demonstrates the potential use of remote sensing and Geographic Information System (GIS) in identifying forest fire prone areas in Manipur, southeastern part of Northeast India. Land use land cover (LULC), vegetation type, Digital elevation model (DEM), slope, aspect and proximity to roads and settlements; factors that influence the behavior of fire, were used to model the forest fire risk zones. Each class of the layers was given weight according to their fire inducing capability and their sensitivity to fire. Weighted sum modelling and ISODATA clustering was used to classify the fire zones.