Spatiotemporal Prediction and Influencing Factor Analysis of Land Use and Habitat Quality in the Zhengzhou Metropolitan Area, China, Based on an Integrated Framework Combining intPLUS, InVEST, XGBoost, and SHAP

0pt 2.5ex plus 1ex minus .2ex 1.5ex plus .2ex 0pt 2ex plus .5ex minus .2ex 1ex plus .2ex 0pt 1.5ex plus .5ex minus .2ex 0.8ex plus .2ex The Zhengzhou Metropolitan Area (ZMA) is crucial to China’s regional growth strategy, but the region grapples with serious environmental issues, including land degradation and a problematic drop in its variety of plant and animal life. In this study, we leveraged a multisource data methodology to develop the intPLUS-InVEST-XGBoost-SHAP analytical framework for an in-depth investigation of land use transformations and habitat quality dynamics between 2000 and 2020. We investigated the causes of habitat quality changes and predicted trends up to 2050. The key findings were as follows. (1) From 2000 to 2020, the ZMA saw a 10.44% reduction in its farmland, while forests and developed areas experienced 16.9% and 14.4% growth, respectively. Construction activities rapidly augmented, expanding by a staggering 53.85%, and cropland and forest together occupied more than 80% of the land use; ZMA region land use was predicted to stabilize by 2050. (2) Cropland decrease was observed in natural, urban, and conservation-focused scenarios, whereas cropland conservation priority increased slightly, and construction land expanded across all scenarios. (3) From 2000 to 2020, the habitat quality index in ZMA rose from 0.5493 to 0.5196; expected scenarios indicated consistent spatial trends with ongoing improvement by 2050. (4) From 2000 to 2020, slope and temperature primarily determined ZMA habitat quality; across various scenarios, slope was predicted to be the key factor by 2050. Our findings bolstered multiscenario land use simulations and habitat quality forecasts across the urban metropolis, offering crucial intelligence for the progression and spatial management of the ZMA.