Considering Mountain Micro-Topographic Characteristics in Habitat Quality Assessments and Its Nonlinear Influencing Mechanism

Optimizing the habitat quality (HQ) assessment and revealing its nonlinear influence mechanisms, particularly by considering the mountain micro-topographic characteristics, are critically important for promoting sustainable development and safeguarding the ecological environment of mountain cities. Taking the Chongqing main city (CMC) as the study area, first, the Geomorphons algorithm was used to identify the mountain micro-topographic positions. On this basis, the HQ assessment of the InVEST model was optimized by collecting the multispectral data from UAV, and its spatiotemporal change trend was analyzed by the least-squares method. Secondly, hotspot analysis was used to explore the spatiotemporal differentiation of HQ on different land use and geomorphological types. Finally, based on the generalized additive model, the dominant influencing factors were determined, and their nonlinear effects were analyzed. The results showed the following: (1) The average HQ of the CMC showed an increasing trend from 2000 to 2020. The HQ of the four mountains and two rivers was higher, while it was lower in the central urban area. (2) The HQ hotspots were mainly distributed in parallel mountain areas and composed of forests, grasslands, and waters. The heterogeneity of HQ at the mountain micro-topographic scale was manifested in that the summits were always the hotspots of HQ. (3) HQ was influenced by a range of factors, including both natural environmental conditions and socio-economic drivers, among which the normalized difference vegetation index was the most important influencing factor.