Analyzing Spatial–Temporal Changes and Driving Mechanism of Landscape Character Using Multi-Model Interpreters: A Case Study in Yanqing District, Beijing

To understand how landscapes have changed in Yanqing District, Beijing, during its urban development over the past 15 years, we referred to the Landscape Character Assessment (LCA) theory, selecting altitude, slope, roughness, forest type, land cover, and forest vegetation cover as characteristic factors, identified nine types of landscape character types (LCTs) from 2005 to 2020 through unsupervised clustering. Then, we applied multi-model interpreters, including the Optimal Parameter-Based Geographical Detector (OPGD) and SHapley Additive exPlanations (SHAP), to analyze how social and natural factors impact the spatiotemporal changes of these LCTs. The results indicate that over the past 15 years, the landscape character of Yanqing District has undergone significant changes, with more frequent changes occurring in the “piedmont” areas where mountains meet plains. Slope and precipitation are the main factors affecting the intensity of LCT changes. In contrast, the transformation of different landscape characters is affected by factors such as altitude, slope, precipitation, and distance to artificial surfaces. This study reveals the dynamic changes in landscape character and their driving mechanisms, helping to develop more targeted strategies for landscape management in Yanqing District to promote sustainable regional development.