Wildfire Risk Assessment Considering Seasonal Differences: A Case Study of Nanning, China

Abstract

Wildfire disasters pose a significant threat to the stability and sustainability of ecosystems. The assessment of wildfire risk based on a seasonal dimension has contributed to improving the spatiotemporal targeting of fire prevention efforts. In this study, Nanning, China, was selected as the research area. The wildfire driving factors were chosen from both seasonal and nonseasonal aspects, and the datasets were divided into five periods: all seasons, spring, summer, autumn, and winter. The light gradient boosting machine (LGBM) was employed to construct wildfire danger models for different periods, evaluating the spatial distribution of high-wildfire-danger areas during these periods and the predictive performance differences. The SHapley Additive exPlanations (SHAP) method was utilized to analyze the differential contributions of various factors to wildfire occurrence in different seasons. Subsequently, the remote sensing ecological index (RSEI) was calculated using four indicators, greenness, heat, wetness, and dryness, to assess the ecological vulnerability in different seasons. Finally, by integrating danger and vulnerability information, wildfire risk models were developed to systematically assess the risk of wildfire disasters causing losses to the ecological environment in different seasons. The results indicate that: (1) The evaluation of wildfire danger based on individual seasons effectively compensates for the shortcomings of analyzing danger across all seasons, exhibiting higher predictive performance and richer details. (2) Wildfires in Nanning primarily occur in spring and winter, while the likelihood of wildfires in summer and autumn is relatively lower. In different seasons, NDVI is the most critical factor influencing wildfire occurrence, while slope is the most important nonseasonal factor. The influence of factors varies among different seasons, with seasonal factors having a more significant impact on wildfire danger. (3) The ecological vulnerability in Nanning exhibits significant differences between different seasons. Compared to spring and winter, the ecological environment is more vulnerable to wildfire disasters during summer and autumn. (4) The highest wildfire risk occurs in spring, posing the greatest threat to the ecological environment, while the lowest wildfire risk is observed in winter. Taking into account information on danger and vulnerability in different seasons enables a more comprehensive assessment of the risk differences in wildfire disasters causing ecological losses. The research findings provide a scientific theoretical basis for relevant departments regarding the prevention, control, and management of seasonal wildfires.

Keywords

• wildfire risk assessment
• seasonal differences
• ecological environment vulnerability
• LGBM
• SHAP