Language: English
Published by LAP LAMBERT Academic Publishing, 2023
ISBN 10: 620615050X ISBN 13: 9786206150503
Seller: preigu, Osnabrück, Germany
Taschenbuch. Condition: Neu. Forest Fire Risk Zonation Mapping Using GIS Techniques | Amit Kumar Verma (u. a.) | Taschenbuch | Englisch | 2023 | LAP LAMBERT Academic Publishing | EAN 9786206150503 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Language: English
Published by LAP LAMBERT Academic Publishing Jun 2023, 2023
ISBN 10: 620615050X ISBN 13: 9786206150503
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - 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. 88 pp. Englisch.
Language: English
Published by LAP Lambert Academic Publishing, 2023
ISBN 10: 620615050X ISBN 13: 9786206150503
Seller: moluna, Greven, Germany
Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 fir.
Language: English
Published by LAP LAMBERT Academic Publishing Jun 2023, 2023
ISBN 10: 620615050X ISBN 13: 9786206150503
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. 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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 88 pp. Englisch.
Language: English
Published by LAP LAMBERT Academic Publishing, 2023
ISBN 10: 620615050X ISBN 13: 9786206150503
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.