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.

Engineering activities along the Sichuan–Tibet Railway (STR) could cause land degradation and threaten the surrounding ecological security. It is crucial to evaluate the integrated land ecology during and after the construction of this project. This study assesses the land ecology along the STR corridor from 2000 to 2022 using a transfer matrix, the analytic hierarchy process (AHP), and the PSR-TOPSIS model. The main results are as follows: (1) The novel comprehensive ecological assessment process including nine indicators is feasible. (2) The high-quality land ecological, surface vegetation, and environmental regions were concentrated in Ya’an and Nyingchi, whereas the low-quality regions were situated in Qamdo and Garze Tibetan Autonomous Prefecture. (3) There was an overall decline in the integrated land ecological quality along the STR from 2000 to 2022. While it steadily improved in the Ya’an and Nyingchi regions from 2010 to 2022, it continued to decline around the Qamdo region. (4) The most degraded land-use type during the 22 years was grassland, and farmland was the most secure land-use type. Overall, spatial analyses and examinations of residue disposal sites suggested that these locations have negatively impacted integrated land ecology since the beginning of the STR construction project. Our findings have implications for preserving the ecological ecosystem and ensuring the sustainability of the STR construction project.