Wildfire is a sudden and highly destructive natural disaster that poses significant challenges in terms of response and rescue efforts. Influenced by factors such as climate, combustible materials, and ignition sources, wildfires have been increasingly occurring worldwide on an annual basis. In recent years, researchers have shown growing interest in studying wildfires, leading to a substantial body of related research. These studies encompass various topics, including wildfire prediction and forecasting, the analysis of spatial and temporal patterns, the assessment of ecological impacts, the simulation of wildfire behavior, the identification of influencing factors, the development of risk assessment models, techniques for managing combustible materials, decision-making technologies for firefighting, and fire-retardant methods. Understanding the factors that affect wildfire spread behavior, employing simulation methods, and conducting risk assessments are vital for effective wildfire prevention, disaster mitigation, and emergency response. Consequently, it is imperative to comprehensively review and explore further research in this field. This article primarily focuses on elucidating and discussing wildfire spread behavior as a key aspect. It summarizes the driving factors of wildfire spread behavior and introduces a wildfire spread behavior simulation software and its main applications based on these factors. Furthermore, it presents the research progress in wildfire risk assessment based on wildfire spread behavior factors and simulation, and provides an overview of various methods used for wildfire risk assessment. Finally, the article proposes several prospects for future research on wildfire spread: strengthening the dynamic monitoring of wildfires and utilizing comprehensive data from multiple sources, further exploring the differential effects of key factors on wildfire spread, investigating differences in driving factors, improving wildfire models in China, developing applicable software, and conducting accurate and scientific assessments of wildfire risks to protect ecological resources.

China boasts a vast expanse of mountainous terrain, characterized by intricate geological conditions and structural features, resulting in frequent geological disasters. Among these, landslides, as prototypical geological hazards, pose significant threats to both lives and property. Consequently, conducting a comprehensive landslide inventory in mountainous regions is imperative for current research. This study concentrates on the Yinshan Mountains, an ancient fault-block mountain range spanning east–west in the central Inner Mongolia Autonomous Region, extending from Langshan Mountains in the west to Damaqun Mountains in the east, with the narrow sense Xiao–Yin Mountains District in between. Employing multi-temporal high-resolution remote sensing images from Google Earth, this study conducted visual interpretation, identifying 10,968 landslides in the Yinshan area, encompassing a total area of 308.94 km². The largest landslide occupies 2.95 km², while the smallest covers 84.47 m². Specifically, the Langshan area comprises 331 landslides with a total area of 11.96 km², the narrow sense Xiao–Yin Mountains include 3393 landslides covering 64.13 km², and the Manhan Mountains, Damaqun Mountains, and adjacent areas account for 7244 landslides over a total area of 232.85 km². This research not only contributes to global landslide cataloging initiatives but also serves as a robust foundation for future geohazard prevention and management efforts.

Transmission lines often traverse mountainous regions prone to frequent geological hazards, making it of great practical significance to analyze the spatial distribution patterns of landslide traces along the transmission line corridors. This study focuses on the Hubei section of the ±800 kV ultra-high-voltage (UHV) transmission line from the upper reaches of the Jinsha River to Hubei. Based on high-resolution remote sensing imagery provided by Google Earth, a landslide traces inventory was constructed through visual interpretation. In addition, 13 factors, such as elevation, slope, aspect, relief, soil type and land cover, were selected to analyze the spatial distribution of landslides. The results indicate the following: (1) There are at least 18,598 landslides in the study area, with a total area of approximately 2671.82 km². The spatial distribution is uneven, exhibiting a general pattern of “dense in the west, sparse in the east”. The maximum landslide number density (LND) reaches 4.16 km⁻², and the maximum landslide area percentage (LAP) is 0.83%. (2) Landslides are predominantly distributed in areas with elevations of 278–1059 m, slope gradients of 20–30°, northwest and southeast aspects, surface roughness values of 400–600, Triassic and Jurassic strata, evergreen coniferous forest and sparse forest, as well as lixisols and ferrallitic soil. This study established a landslide traces database for the region, preliminarily revealing the distribution characteristics of landslides and their dominant controlling factors. It provides a scientific basis for geological hazard risk assessment and prevention for UHV transmission lines.