Bøger af Amit Kumar Verma

In this book we have provided information on how to identify influencive biophysical parameters responsible for forest fire hazard and develop fire hazard model using GIS and statistical package. The result shows that Pine forests at lower elevation and near to settlement are badly impacted by fire. Variables such as precipitation of driest month, precipitation of warmest quarter, mean temperature of driest quarter, distance from forest guard chowki, forest canopy density, distance from settlement and elevation are significantly influencing forest fire regime in pine zone of Uttarakhand. The present methodology provides substantial improvement over frequency analysis method as used by earlier workers for developing fire hazard models in pine zone. Such types of models if recalibrated using future data can lead to higher degree of accuracy of fire prediction. GIS based modelling is helpful in identifying, mapping, quantification of biophysical parameters at spatio-temporal scale and also for the future predictions of forest fire. Geospatial modelling can potentially enhance forest fire management by providing spatially mapped fire hotspots.

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.