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Forest Fire Susceptibility Mapping Using Analytical Hierarchy Process Approach for Chandoli National Park of Maharashtra, India
Shobha N Lohar
Shivaji University
Corresponding Author
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This work is licensed under a CC BY 4.0 License. Read Full License
The forest fire management starts with identifying fire potential areas. This study suggests a new approach based on Geographic Information Systems (GIS), Remote Sensing (RS), and Analytical Hierarchy Process (AHP) to map forest fire susceptibility of Chandoli National Park of Maharashtra. Influencing factors like past burnt area, Land Surface Temperature (LST), forest type, agriculture area, road network, and the vicinity of settlements taken into consideration. All variables assigned a weight based on their impact on the fire susceptibility. The final map categorized, ranging from very high to very low, into five fire susceptible regions. The result indicated that 12.99% (6506.89 ha) land area of the study region came in a very high susceptible region, while 18.70% (9361.10 ha) of high. The forest fire susceptibility map shows that 12.26%, 44.42%, 11.61% area comes under moderate, low, and very low- susceptible areas, respectively. Afterward, an accuracy assessment carried out with existing records of the forest fire. The mostly very high and high susceptible forest fire region comes where high road density, settlements and agriculture fields dominate. The result reveals that the anthropogenic factors and its activities in the forest region responsible for the frequent forest fire. The unification of remote sensing and the Analytical Hierarchy Process into GIS is beneficial to determining forested areas with high fire susceptibility and also to plan forest management after a forest fire.
Keywords
Forest Fire Susceptibility, Analytical Hierarchy Process, Past Burn Area, Chandoli National Park, GIS
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This is a preprint. It has not completed peer review.
Research
Forest Fire Susceptibility Mapping Using Analytical Hierarchy Process Approach for Chandoli National Park of Maharashtra, India
Shobha N Lohar
Shivaji University
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 22 Jun, 2020
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Physical Geography
License:
This work is licensed under a CC BY 4.0 License. Read Full License
The forest fire management starts with identifying fire potential areas. This study suggests a new approach based on Geographic Information Systems (GIS), Remote Sensing (RS), and Analytical Hierarchy Process (AHP) to map forest fire susceptibility of Chandoli National Park of Maharashtra. Influencing factors like past burnt area, Land Surface Temperature (LST), forest type, agriculture area, road network, and the vicinity of settlements taken into consideration. All variables assigned a weight based on their impact on the fire susceptibility. The final map categorized, ranging from very high to very low, into five fire susceptible regions. The result indicated that 12.99% (6506.89 ha) land area of the study region came in a very high susceptible region, while 18.70% (9361.10 ha) of high. The forest fire susceptibility map shows that 12.26%, 44.42%, 11.61% area comes under moderate, low, and very low- susceptible areas, respectively. Afterward, an accuracy assessment carried out with existing records of the forest fire. The mostly very high and high susceptible forest fire region comes where high road density, settlements and agriculture fields dominate. The result reveals that the anthropogenic factors and its activities in the forest region responsible for the frequent forest fire. The unification of remote sensing and the Analytical Hierarchy Process into GIS is beneficial to determining forested areas with high fire susceptibility and also to plan forest management after a forest fire.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the manuscript can be downloaded and accessed as a PDF.