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A Geoinformation System Approach for Strengthening Conservation Measures in Protected Area with Reference to Forest Fire

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A Geoinformation System Approach for Strengthening Conservation Measures in Protected Area with Reference to Forest Fire A Geo­Information System Approach for Strengthening Conservation Measures in Protected Area with Reference to Forest Fire Sanjay K Srivastava January, 2006 A Geo­Information System Approach for Strengthening Conservation Measures in Protected Area with Reference to Forest Fire by Sanjay K Srivastava Thesis submitted to the International Institute for Geo­information Science and Earth Observation in partial fulfilment of the requirements for the degree of Master of Science in Geo­information Science and Earth Observation, Specialisation: (fill in the name of the specialisation) Thesis Assessment Board Thesis Supervisors Chairman: Prof. Dr. Ir. Menno­Jan Kraak Dr. Sarnam Singh (IIRS) External Examiner : Dr. Alok Saxena Dr. Sameer Saran (IIRS) IIRS Member : Mr. P.L.N.Raju Dr. Ir. Luc G. J. Boerboom (ITC) Supervisor : Dr. Sarnam Singh Dr. Ir. Rolf A. de By (ITC) Supervisor : Dr. Sameer Saran ii r s INTERNATIONAL INSTITUTE FOR GEO­INFORMATION SCIENCE AND EARTH OBSERVATION ENSCHEDE, THE NETHERLANDS & INDIAN INSTITUTE OF REMOTE SENSING, NATIONAL REMOTE SENSING AGENCY (NRSA), DEPARTMENT OF SPACE, DEHRADUN, INDIA I certify that although I may have conferred with others in preparing for this assignment, and drawn upon a range of sources cited in this work, the content of this thesis report is my original work. Signed …………………………………… Disclaimer This document describes work undertaken as part of a programme of study at the International Institute for Geo­information Science and Earth Observation. All views and opinions expressed therein remain the sole responsibility of the author, and do not necessarily represent those of the institute. Abstract Innumerable forest fire spread models exist for taking decision towards effective fire management using the spatio­temporal database system. Most fire models operate at various scales using different algorithms for fire prediction and produce value/ maps denoting fire­frequency, fire­severity, fire­spread rate, fire­burn pattern or fire­risk. Prime variables considered in modelling are environmental variables and very 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 are caused as a result of biotic factors. The purpose of this study was to develop a geo­information system approach for tackling forest fire in Mudumalai Wildlife Sanctuary, Tamilnadu. In this study the main objective was to develop forest fire likelihood model integrating GIS and knowledge based approach for predicting fire­sensitive ignition areas considering major causative and anti­causative factors and suggest appropriate management strategy for strengthening conservation measures in the Protected Area (PA). In this modelling, various causative factors were identified and it was found that wildlife dependent (antler collection and poaching) contributed significantly to the fire occurrence followed by management dependent (uncontrolled tourism and grazing) with very less influence of demographic factors. Similarly, anti­ causative factor (stationing of anti­poaching/ fire camps) was considered quite significant. The likelihood model so developed envisaging various factors and habitat (flammability) accounted for different scenarios as a result pair­wise comparison on ordinal scale in knowledge matrix. The inferential statistics computed indicated towards the robustness of the model and its insensitivity to moderate changes. The area value evaluation model formulated with ecological, economic and social values was found extremely significant in terms of management intervention and regular fire incidences. Prioritization of the mitigation strategy provided for appropriate location of the various management interventions vis­à­vis likelihood model with area value and indicated further reduction in the fire likelihood. The model forms a good analysis tool for resource managers. A Graphic User Interface (GUI) so developed with the prototype allows the user to easily search, analyze and edit the information necessary to execute each simulation. It makes possible for this forest fire likelihood model to predict and to prevent forest fire in effective and scientific manner because it can assume exact forest fire likelihood in real time and present in proper time. Keywords: causative factor, anti­causative factor, likelihood, area value, mitigation, customization i Acknowledgements All “facts” are opinions, some more widely accepted than others. This M.Sc thesis is crystallization of my opinion using the knowledge of Geo­informatics. However, the same was not possible without the support of the following persons. First of all, I would like to thank the Govt of Tamilnadu, for deputing me for this course and sponsoring my fellowship for the training program. I would like to thank immensely, Thiru J.C. Kala, IFS, for taking personal interest in nominating my name and Dr. Sukhdev, IFS, for providing necessary support. This course would not have been possible without the consent of Dean IIRS, Director, NRSA and Director, ITC, Netherlands. Lot of technical effort has gone into the formulation of this thesis. I would like to place on records the guidance and technical inputs provided by my both ITC and IIRS supervisors. I would like to thank Dr. Luc Boerboom, Supervisor (ITC) for helping me in formulation of my research proposal and providing necessary guidance. My special thanks are due to Dr. Rolf de By, Supervisor (ITC), who not only provided me with the technical guidance and necessary encouragement, but also helped me in shaping my proposal in the real geo­informatics framework. I would like to thank Dr. Sarnam Singh, Supervisor (IIRS) for providing necessary guidance and undertaking field visit along with me. This thesis was not possible without unstinted support and technical guidance of Dr. Sameer Saran, Supervisor (IIRS), who also ensured that the study resulted in a meaningful geo­informatics research. Major consideration in this study was the collection of spatial and non­spatial information. I would like to thank Thiru C.K. Sreedharan, IFS and Thiru Amit Asthana, IFS, for rendering help in the procurement of GIS related data. I would like to convey my special thanks to Thiru Ashok Upreti, IFS, for ensuring that all the information and data related to the study area was made available along with necessary support during the field visit. I would like to thank Thiru. Ajai Desai and his team for rendering necessary help related to collection of animal census data during the field visit. Thanks are also due to Thiru. Soundarajan (NWEA) and his team in this regard. I would also like to thank Dr. R.Sukumar (IISC) and his team for making available data for the study area. Analysis and discussion formed an integral part of the thesis. I would like to convey my special gratitude to Thiru A. Udayan, IFS for his comments on data computation. My thanks are also due to Sh. Rajat Pal, IFS (FSI) and his team especially Sh. Harnam Singh for providing necessary support. I would also like to thank Sh. Rajesh Kumar, ISS, for his valuable suggestions. Mid­term reviews and concurrent evaluation are extremely significant in the research. I would like to thank Prof. Alfred Stein (ITC) Dr. V.K.Dadhwal, Sh. P.L.N.Raju and Sh. C. Jeganathan (IIRS) for their valuable comments. I would also like to thank all the staff of Geo­informatics division including my colleagues and friends. Last, but not the least, I would like to thank my wife for providing enough motivation for undertaking this course at this age. Place: Dehradun Sanjay K Srivastava, IFS January, 2006 ii Table of contents Abstract ………………………………………………………………………………………………. i Acknowledgements ………………………………………………………………………………….. ii Table of contents ……………………………………………………………………………………. iii List of figures ……………………………………………………………………………………….viii List of tables …………………………………………………………………………………………..x 1. Introduction.................................................................................................................................1 1.1. Background & Justification.................................................................................................1 1.1.1. Forest Fires – Global scenario.........................................................................................2 1.1.2. Forest Fires – Indian scenario .........................................................................................4 1.1.3. Impact of Forest Fire......................................................................................................5 1.1.4. Forest Fire vis­à­vis Protected Area Conservation ...........................................................6 1.1.5. Geo­information System approach ..................................................................................6 1.1.6. The Forest Fire Terminology...........................................................................................7 1.1.6.1. Fire Risk................................................................................................................7 1.1.6.2. Fire Hazard............................................................................................................7 1.1.6.3. Fire Vulnerability...................................................................................................7 1.1.6.4. Fire Severity ..........................................................................................................7 1.1.6.5. Fire Likelihood.......................................................................................................7
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