Development of an Index for Forest Fire Risk Assessment Considering Hazard Factors and the Hazard-Formative Environment

Author:

Gong Adu12,Huang Zhiqing12,Liu Longfei3,Yang Yuqing12,Ba Wanru12,Wang Haihan12

Affiliation:

1. State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

2. Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

3. National Disaster Reduction Center of China, Ministry of Emergency Management of the People’s Republic of China, Beijing 100124, China

Abstract

Forest fires are characterized by a rapid and devastating nature, underscoring the practical significance of forest fire risk monitoring. Currently, forest fire risk assessments inadequately account for non-meteorological hazard factors, lack the hazard-formative environment and contextual disaster knowledge for fire occurrence mechanisms. In response, based on MODIS products, we augmented the FFDI (forest fire danger index) with the RDST (regional disaster system theory) and selected various fire risk indicators, including lightning. MOD14 was used for the correlation analysis of fire and its indicators. Through the amalgamation of the analytic hierarchy process (AHP), the entropy method, and the minimal relative entropy theory, we formulated the CFFRI (composite forest fire risk index) and assessed forest fire risks spanning from 2010 to 2019 in Southwest China, which were validated with historical disaster data and MCD64. The findings revealed that the CFFRI yields consistently higher overall fire risk values, with 89% falling within the high-risk category and 11% within the moderate-risk category. In contrast, the FFDI designated 56% of cases as fourth-tier fire risks and 44% as third-tier fire risks. Notably, the CFFRI achieved an accuracy of 85% in its calculated results, while the FFDI attained 76%. These outcomes robustly demonstrate a superior applicability of the CFFRI compared with the traditional FFDI.

Funder

State Key Laboratory of Remote Sensing Science and Beijing Engineering Research Center for Global Land Remote Sensing Products

National Key Research and Development Program of China

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

Reference75 articles.

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