Abstract

Forest fires constitute a foremost environmental calamity that distresses the sustainability of the forest. The main source of degradation of Jharkhand forests are forest fires conquered by forest species of Sal and Bamboo. Palamau Tiger Reserve in Jharkhand state, India, is becoming more susceptible to forest fire due to anthropogenic disturbance coupled with speedy upsurge in population. In this study, forest fire risk in PTR was evaluated based on various fire inducing factors, viz., forest fuel, settlements, roads, bare soil index, elevation slope and aspect. Geoinformatics based multi-criteria decision analysis (MCDA) through method of AHP (analytic hierarchy process) used to extract forest fire risk map in five classes: Very low risk, low risk, moderate risk, high risk and very high risk. The results obtained showed that about 180 km² (14.85%) falls under very low fire risk zone, 234 km² (19.30%) falls in low fire risk zone, 269.73 km² (22.16%) falls under moderate fire risk zone, 299.36 km² (24.59%) falls under high fire risk zone and 232.56 km² (19.10%) falls in very high fire risk zone. Forest fire risk map was validated from historical fire incidents observed through field data, MODIS and SNPP-VIIRS satellite products. The results showed that the geoinformatics based forest fire risk zones delineated through MCDA-AHP method are in good agreement with historical forest fire occurrences, henceforth may be utilised for fire planning for mitigation in forest areas.

Research Highlights

• PTR is becoming more susceptible to forest fire due to anthropogenic disturbance coupled with speedy upsurge in population.

• Forest Fires Risk was evaluated based on various fire inducing factors viz., forest fuel, settlements, roads, bare soil index, elevation slope and aspect through method of AHP.

• Forest fire risk map was validated from historical fire incidents observed through field data, MODIS and SNPP-VIIRS satellite products.

• The results showed that the geoinformatics based forest fire risk zones are in good agreement with historical forest fire occurrences henceforth may be utilised for fire planning for mitigation in forest areas.

中文翻译：

---

通过层次分析法（AHP）基于地理信息学的多准则决策分析（MCDA），用于印度贾坎德邦帕拉毛老虎保护区的森林火灾风险制图

摘要

森林火灾是造成森林可持续发展的首要环境灾难。贾坎德邦森林退化的主要来源是萨尔和竹林物种征服的森林大火。由于人为干扰和人口迅速增加，印度贾坎德邦的帕拉毛老虎保护区正变得更容易受到森林大火的影响。在这项研究中，PTR的森林火灾风险是根据各种火灾诱发因素进行评估的，即森林燃料，定居点，道路，裸土指数，高低坡度和坡向。通过AHP（层次分析法）的方法，基于地理信息学的多准则决策分析（MCDA）用于提取森林火灾风险图，分为五类：极低风险，低风险，中度风险，高风险和极高风险。获得的结果表明，大约180公里²（14.85％）属于低火危险区，234 km ²（19.30％）属于低火危险区，269.73 km ²（22.16％）属于中度火危险区，299.36 km ²（24.59％）属于低火危险区高火灾危险区，并且有232.56 km ²（19.10％）属于高火灾危险区。通过现场数据，MODIS和SNPP-VIIRS卫星产品观测到的历史火灾事件验证了森林火灾风险图。结果表明，通过MCDA-AHP方法划分的基于森林地理信息学的森林火灾危险区与历史森林火灾发生情况吻合良好，因此可用于森林火灾减灾规划。

研究重点

• 由于人为干扰和人口迅速增加，PTR变得更容易受到森林火灾的影响。

• 通过AHP方法，基于森林，燃料，定居点，道路，裸土指数，高低坡度和坡向等多种火灾诱因，对森林火灾风险进行了评估。

• 通过现场数据，MODIS和SNPP-VIIRS卫星产品观测到的历史火灾事件验证了森林火灾风险图。

• 结果表明，基于地理信息学的森林火灾危险区与历史森林火灾的发生有很好的一致性，因此可用于森林地区减灾的火灾规划。