A geo-information system approach for forest fire likelihood based on causative and anti-causative factors

Abstract

Innumerable forest fire spread models exist for taking a decision, but far less focus is on the real causative factors which initiate/ignite fire in an area. It has been observed that the majority of the forest fires in India are initiated due to anthropogenic factors. In this study, we develop a geo-information system approach for management of forest fire in Mudumalai Wildlife Sanctuary, Tamil Nadu, India, with the objective to develop a forest fire likelihood model, integrating GIS and knowledge-based approach for predicting fire-sensitive initiation areas considering major causative and anti-causative factors. Amongst the various causative factors investigated, it was found that wildlife-dependent factor (antler collection and poaching) contributed significantly to fire occurrence followed by management-dependent factors (uncontrolled tourism and grazing), with much less influence of demographic factors. Similarly, anti-causative factor (stationing of anti-poaching/ fire camps) was considered as quite significant.

The likelihood model so developed, envisaging various factors and flammability, accounted for different scenarios as a result of pair-wise comparison on an ordinal scale in a knowledge matrix. The inferential statistics computed indicated the robustness of the model and its insensitivity to moderate changes. It makes it possible for this forest fire likelihood model to predict and prevent a forest fire in an effective and scientific manner because it can assume forest fire likelihood in real time and present in proper time.

Keywords:

• causative factor
• anti-causative factor
• fire likelihood model

Acknowledgments

Much technical effort has gone into the formulation of this work. The authors would like to thank the Government of Tamil Nadu and the officials of the Forest Department for providing the necessary support. The authors would also like to place on record the guidance and technical inputs provided by the faculty of ITC, The Netherlands and IIRS, Dehradun. The authors also thank the Nilgiris Wildlife and Environment Association, Indian Institute of Science, Bombay Natural History Society, and Forest Survey of India for making available certain field-based information.