Against the backdrop of rapid urban expansion, preserving landscape connectivity has become a vital approach to addressing habitat fragmentation and enhancing biodiversity. This study takes Chongqing, China, as a case study and establishes a multi-scale evaluation framework encompassing the Main urban area-Main metropolitan area-Chongqing city. Using landscape connectivity indices and ecological security patterns, the study evaluates the structural and functional connectivity of the research area. Through comparative analysis, it demonstrates the scale-dependent differences in regional landscape connectivity and proposes protection strategies from a multi-scale perspective. The results indicate that in terms of structural connectivity, as the study scale expands, the dPC (Delta Probability of Connectivity) rankings of all core areas within the urban core significantly decline, while those in Jiangjin, Nanchuan, and Fuling districts within the metropolitan area experience significant degradation, moderate degradation, and upgrading, respectively. In terms of functional connectivity, the corridors (394.79 km²) and source areas (39.61 km²) in Beibei, Yubei, Nan’an, and Banan districts are crucial for landscape connectivity protection at small- to medium-scale levels, while the corridors (11.33 km²) and source areas (1,180.41 km²) in Nanchuan and Fuling districts are pivotal for connectivity protection at medium- to large-scale levels. This study provides systematic and comprehensive strategic references for the protection of landscape connectivity.

In the context of sustainable forest resource development, balancing ecological conservation with rational utilization is essential to achieving forest multifunctionality. Longyuwan National Forest Park, located in Luanchuan County, Henan Province, serves as a transitional zone between rural mountainous ecosystems and nearby urban settlements. Increasingly, this area faces urbanization pressures such as tourism expansion, infrastructure development, and intensified land use, which may threaten ecological stability. This study aims to evaluate the ecological sensitivity of the park and optimize its spatial functional zoning. Using the Analytic Hierarchy Process (AHP), we followed four key steps: constructing the hierarchical model, generating the pairwise judgment matrices, computing the weights and conducting the consistency check, and determining the final weights. A hierarchical evaluation framework was constructed using the AHP, incorporating twelve ecological indicators across geomorphological, hydrological, atmospheric, biological, and anthropogenic dimensions. Spatial analysis tools in ArcGIS 10.2, including reclassification and weighted overlay, were employed for single-factor and integrated sensitivity assessments. The results indicated that land-use type, elevation, and water-body distribution were the most influential indicators. Ecological sensitivity across the park was categorized into five levels: extremely high (0.02%), high (11.99%), moderate (73.53%), low (14.19%), and extremely low (0.28%). Based on these findings, four functional zones were delineated: ecological conservation (50.99%), core landscape (22.86%), general recreation (23.94%), and management and service (2.21%). This research provides spatially explicit insights into forest management under anthropogenic stress, offering theoretical support for the sustainable governance of forest–urban interface landscapes.

Urban green spaces (UGSs) play an important role in improving urban ecological envi-ronments and social well-being. In this study, we selected Chengdu, China as the research area. By integrating urban big data with spatial autocorrelation analysis, we identified UGS distributions across different years and their spatial clustering patterns. Furthermore, eleven factors influencing UGS distribution were systematically selected from both city-scale and neighborhood-scale perspectives. The main factors influencing the kernel density of UGS in Chengdu were explored using geographical detectors, and the results showed that the quantity and area of UGS in Chengdu gradually increased from 2012–2021 through an unbalanced spatial distribution. All influencing factors had an interac-tive relationship with the UGS kernel density. As the UGS kernel density increased, transportation hub had the greatest impact, the influence of air pollution and urban pre-cipitation on the density of UGS increased, and the nighttime light index decreased. By categorizing the influencing factors into natural environmental and human activity di-mensions, the analysis revealed that human activities and natural environment served as primary drivers of UGS density before and after 2018, respectively. Furthermore, their ef-fects on UGS gradually expanded from the urban core to encompass the entire metropoli-tan area over time. By exploring the relationship between the evolution of UGS spatial patterns and changes in the urban ecological environment and social development using a quantifiable method, this study provides references and guidelines for the future plan-ning of cities to achieve high-quality development.