With the development of modern economy and society, people have higher and higher requirements for spiritual needs request. The demand of traveling is a key growth point of the peoples spiritual needs. Forest tourism has become an important part of the forestry modernization. Its reasonable development can provide a site for urban residents leisure and health preservation, and help the revitalization of local villages and economic development. However, there are few studies on the evaluation methods of forest tourism land resources potential development around the world nowadays, and the planning and development of forest land resources are also lack of scientific guidance. The research work of this paper is carried out based on the realistic problems above, through analyzing the characteristics of the land resources of forest tourism, carding the main indicators of forest land resources development value, and fuzzy analytic hierarchy process (AHP) is studied to evaluate its development potential. The relevant conclusions can provide a theoretical guidance for the forest land resources development and planning, which will improve the development quality and effect of forest land resource.

Rapid urbanization and tourism-driven economic development have accelerated land-use/land-cover change (LUCC), reshaped landscape structure and increased landscape ecological risk (LER). Unraveling the spatiotemporal evolution of LER and its drivers is critical for regional ecological restoration and sustainable development. Using LUCC data for the Li River Basin (LRB) during 2000–2020, this study constructed an LER assessment model based on landscape pattern indices and employed an XGBoost–MGWR framework to identify key natural and socioeconomic drivers, as well as their nonlinear effects and spatial mechanisms. The results showed that: (1) forestland and cropland dominated the basin throughout the study period. Cropland and built-up land expanded, whereas forestland, grassland, and water areas contracted, with significant mutual conversions between forestland and cropland. (2) Relatively low- and middle-risk areas dominated the LER structure and exhibited a spatial pattern of “higher in the center and lower in the periphery”. Middle- and relatively high-risk areas expanded, while low and high-risk areas contracted, indicating a shift toward middle to relatively high risk levels. (3) Land-use intensity (LUI) and the digital elevation model (DEM) were the core drivers of LER change, while tourism intensity (TRI) showed an increasing influence over time. These findings provide a scientific basis for regional ecological management and sustainable development.

Accurately assessing the accessibility of fire services is critical for enhancing urban safety and the resilience of the built environment. However, existing studies often lack a systematic analysis of spatiotemporal dynamics across an entire municipality. To address this gap, this study develops a citywide dynamic assessment framework for Shanghai, integrating GIS with real-time traffic data across 240 consecutive intervals to assess the service accessibility of 195 fire stations in relation to 7973 key units of fire safety. The principal findings are threefold. First, the results reveal significant urban–suburban heterogeneity in emergency response times. Notably, the proximity advantage of fire stations in central urban areas is offset by traffic congestion, and the marginal benefit of traffic speed improvement exhibits a sharp decline once the average speed exceeds a critical threshold of 13.7–21.0 km/h. Second, the accessibility ratio demonstrates a clear temporal pattern, being highest on holidays and lowest during weekday peak hours, and follows a nonlinear spatial decline from the urban centre to the periphery. This pattern is influenced more critically by the matching of supply and demand than by fire station density alone. Third, the analysis identifies dynamic vulnerability hotspots, which display a ‘bimodal (M-shaped)’ pattern on weekdays and a ‘unimodal (A-shaped)’ pattern on weekends and holidays. This spatiotemporal mismatch shows that central urban areas, despite higher station density, can suffer from both high fire risk and low accessibility, revealing structural patterns consistent with the ‘Inverse Care Law’ in emergency service provision. This study concludes that merely improving traffic conditions is insufficient; optimising the spatial matching of resources is paramount for effective urban disaster prevention. By developing a refined dynamic assessment framework, this study advances current knowledge by focusing on demand locations consistent with actual fire regulatory priorities and examining spatiotemporal patterns across both urban and suburban areas, thereby providing quantitative, evidence-based support for the strategic planning of fire stations and the enhancement of infrastructure resilience.