Forest Wildfire Risk Assessment of Anning River Valley in Sichuan Province Based on Driving Factors with Multi-Source Data

Author:

Ji Cuicui1234,Yang Hengcong1ORCID,Li Xiaosong25,Pei Xiangjun34,Li Min6,Yuan Hao1,Cao Yiming1,Chen Boyu1,Qu Shiqian1,Zhang Na1,Chun Li1,Shi Lingyi1,Sun Fuyang7

Affiliation:

1. School of Smart City, Chongqing Jiaotong University, Chongqing 400074, China

2. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

3. State Key Laboratory of Geohazard Prevention and Geo-Environment Protection, Chengdu University of Technology, Chengdu 610059, China

4. State Environmental Protection Key Laboratory of Synergetic Control and Joint Remediation for Soil & Water Pollution, Chengdu University of Technology, Chengdu 610059, China

5. International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China

6. China Meteorological Services Association, Beijing 100081, China

7. Forest Fire Warning and Monitoring Information Center, Ministry of Emergency Management, Beijing 100054, China

Abstract

Forest fires can lead to a decline in ecosystem functions, such as biodiversity, soil quality, and carbon cycling, causing economic losses and health threats to human societies. Therefore, it is imperative to map forest-fire risk to mitigate the likelihood of forest-fire occurrence. In this study, we utilized the hierarchical analysis process (AHP), a comprehensive weighting method (CWM), and random forest to map the forest-fire risk in the Anning River Valley of Sichuan Province. We selected non-photosynthetic vegetation (NPV), photosynthetic vegetation (PV), normalized difference vegetation index (NDVI), plant species, land use, soil type, temperature, humidity, rainfall, wind speed, elevation, slope, aspect, distance to road, and distance to residential as forest-fire predisposing factors. We derived the following conclusions. (1) Overlaying historical fire points with mapped forest-fire risk revealed an accuracy that exceeded 86%, indicating the reliability of the results. (2) Forest fires in the Anning River Valley primarily occur in February, March, and April, typically months characterized by very low rainfall and dry conditions. (3) Areas with high and medium forest-fire risk were mainly distributed in Dechang and Xide counties, while low-risk areas were most prevalent in Xichang city and Mianning country. (4) Rainfall, temperature, elevation, and NPV emerged as the main influencing factors, exerting a dominant role in the occurrence of forest fires. Specifically, a higher NPV coverage correlates with an increased risk of forest fire. In conclusion, this study represents a novel approach by incorporating NPV and PV as key factors in triggering forest fires. By mapping forest-fire risk, we have provided a robust scientific foundation and decision-making support for effective fire management strategies. This research significantly contributes to advancing ecological civilization and fostering sustainable development.

Funder

China Meteorological Services Association Meteorological Science and Technology Innovation Platform Project

National Science Foundation of China

China Postdoctoral Science Foundation

General Project of Chongqing Natural Science Foundation

Publisher

MDPI AG

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