In recent years, with the intensification of climate change, the occurrence of heavy rain events has become more frequent. Landslides triggered by heavy rainfall have become one of the common geological disasters around the world. This study selects an extreme rainfall event in August 2018 in Jiexi County, Guangdong province, as the research object. Based on high-resolution remote sensing images before and after the event, visual interpretation is conducted to obtain a detailed distribution map of rainfall-induced landslides. The results show that a total of 1844 rainfall-induced landslides were triggered within Jiexi County during this rainfall event. In terms of triggered scale, the total area of the landslides is 3.3884 million m², with the largest individual landslide covering an area of 22,300 m² and the smallest one covering an area of 417.78 m². The landslides are concentrated in the northeastern, central, and southwestern parts of the study area, consistent with the distribution trend of rainfall intensity. To investigate further the influence of the regional environment on landslide distribution, this study selects eight influencing factors, including elevation, slope aspect, slope angle, topographic wetness index (TWI), topographic relief, lithology, distance to river, and accumulated rainfall. The landslide number density (LND) and landslide area percentage (LAP) are used as evaluation indicators. Based on statistical analysis using a data analysis platform, the relationship between landslide distribution and influencing factors triggered by this event is revealed. The results of this study will contribute to understanding the development law of regional rainfall-induced landslides and provide assistance for disaster prevention and mitigation in the area. The research results show that the elevation range of 100–150 m is the high-risk zone for landslides. In addition, this study has verified previous findings that slopes in the southeast direction are more prone to landslides. The steeper the slope, the more significant its influence on landslide development. When the topographic wetness index (TWI) is less than 4, landslides tend to have a high-density distribution. Greater variation in terrain relief is more likely to trigger landslides. The instability of lithology in Mesozoic strata is the main cause of landslides. The farther away from the water system, the fewer landslides occur. An increase in cumulative rainfall leads to an increase in both the number and area of landslides.

The establishment of a regional historical landslide inventory plays an indispensable role in landslide assessment and prevention. In this study, based on the Google Earth platform, an inventory of ancient landslides in Hualong County, Qinghai Province was established. The inventory includes 3517 ancient landslides with individual areas ranging from 2354.6 m² to 12.44 km². The dominant characteristics include an elevation of 2600–2800 m, slope of 10–20°, aspects SW, W, and NW, mudstone and sandstone of Paleoproterozoic, Neoproterozoic and Quaternary loess, 8–10 km from faults, 0–1 km from rivers, cultivated and grassland types, NDVI of 0.25–0.3, and an average precipitation in the range of 480–500 mm. In addition, the geometric analysis of landslides shows that the average height and length of ancient landslides in the study area are 151.92 m and 429.52 m, respectively. The power law relationship between the two is L = 0.41 × H^1.37. The ancient landslide inventory of this study exhibits an integrated pattern of the development characteristics and spatial distribution of landslides in the Tibetan Plateau and the upper Yellow River basin, as well as providing a significant reference for subsequent landslide susceptibility mapping in the area.

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.