Abstract

Understanding the spatiotemporal dynamics between landscape pattern changes and ecological environmental quality is essential for optimizing regional landscapes and improving the ecological environment. However, previous studies have certain shortcomings in understanding both aspects: On one hand, ecological environment assessments that overlook air quality may be misleading; On the other hand, the spatiotemporal driving mechanisms between landscape patterns and ecological environmental quality are still unclear. This study considers air quality information, refines ecological remote sensing indices, and employs the Random Forest-Multiscale Geographically and Temporally Weighted Regression (RF-MGTWR) analytical framework to reveal the nonlinear effects and spatiotemporal heterogeneity between landscape patterns and ecological environmental quality across the dimensions of aggregation, connectivity, and diversity. The results indicate:(1) ARSEI (Advanced Remote Sensing Ecological Index) is more suitable for assessing ecological environment quality in areas with air pollution compared to RSEI (Remote Sensing Ecological Index). (2) Ecological environmental quality is most strongly influenced by landscape connectivity, followed by diversity and aggregation. The driving effects of landscape aggregation, diversity, and connectivity will change around the values of 91, 0.64, and 80, respectively, all exhibiting complex nonlinear relationships.(3) Landscape patterns exhibit opposing trends in ecological benefits between urban centers and rural areas: In urban centers, landscape aggregation is negatively correlated with ecological environmental quality, while increased connectivity and diversity have positive effects; this is reversed in areas with good ecological conditions. As urbanization progresses, the positive impacts of landscape connectivity and diversity are enhanced, although the positive effects of diversity gradually diminish. (4) The combination of random forests and MGTWR offers a comprehensive and innovative perspective for analyzing driving mechanisms. Based on the findings, landscape planners should pay attention to the impact thresholds, scales of action, and spatiotemporal heterogeneity between landscape indicators and ecological environment quality.

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