With the ongoing advancement of globalization significantly impacting the ecological environment, the continuous rise in the Land Surface Temperature (LST) is increasingly jeopardizing human production and living conditions. This study aims to investigate the seasonal variations in the LST and its driving factors using mathematical models. Taking the Wuhan Urban Agglomeration (WHUA) as a case study, it explores the seasonal characteristics of the LST and employs Principal Component Analysis (PCA) to categorize the driving factors. Additionally, it compares traditional models with machine-learning models to select the optimal model for this investigation. The main conclusions are as follows. (1) The WHUA’s LST exhibits significant differences among seasons and demonstrates distinct spatial-clustering characteristics in different seasons. (2) Compared to traditional geographic spatial models, Extreme Gradient Boosting (XGBoost) shows better explanatory power in investigating the driving effects of the LST. (3) Human Activity (HA) dominates the influence throughout the year and shows a significant positive correlation with the LST; Physical Geography (PG) exhibits a negative correlation with the LST; Climate and Weather (CW) show a similar variation to the PG, peaking in the transition; and the Landscape Pattern (LP) shows a weak positive correlation with the LST, peaking in winter while being relatively inconspicuous in summer and the transition. Finally, through comparative analysis of multiple driving factors and models, this study constructs a framework for exploring the seasonal features and driving factors of the LST, aiming to provide references and guidance for the development of the WHUA and similar regions.

Ecological security is crucial for regional sustainable development; however, as modern urbanization highlights ecological security challenges, major challenges have arisen. In this paper, we take the ecological region around Taihu Lake, China, as a typical research site, extract important ecological sources and key nodes using morphological spatial pattern analysis (MSPA) and circuit theory, and propose a regulatory framework for the ecological security pattern (ESP) of the ecological region based on the spatial characteristics of sources, corridors, and nodes. We obtained the following results: (1) The ESP includes 20 ecological sources, 37 ecological corridors, 36 critical ecological protection nodes, and 24 key ecological restoration nodes. (2) Most ecological sources are large and concentrated in western Zhejiang and west of Taihu Lake, which are both important ecological sources and ecological resistance surfaces. (3) The ecological corridors spread east, west, and south from Taihu Lake, with high network connectivity. (4) Shanghai serves as the central node, with the Su-Xi-Chang town cluster and the Qiantang River town cluster serving as the extension axes for the ecological resistance hot-spot area. The center of the elliptical ecological resistance surface (standard deviation) lies in Suzhou City, located on the east shore of Taihu Lake. (5) Ecological nodes were mostly located in ecological corridors or junctions. A “four zones and one belt” pattern is suggested in order to make the land around Taihu Lake more connected and stable ecologically. This study can be used as a guide for building and improving an ecological safety network.

The global ecological decline resulting from urban development presents a significant challenge for numerous regions striving to reconcile conservation efforts with developmental needs. This study explores the relationship between ecosystem service value (ESV) and habitat quality (HQ) under various scenarios to elucidate prospective development trajectories. This study utilized the PLUS model to simulate land use patterns in the Chengdu metropolitan area across four distinct development scenarios. Furthermore, it employed the equivalent factor method and the Invest model to quantify ESV and HQ values, and investigated the coupling coordination between ESV and HQ for each city using a coupling coordination model (CCM). The findings are as follows: (1) Between 2000 and 2020, land use in the Chengdu metropolitan area primarily expanded through the development of construction land. (2) Concurrently, ESV demonstrated a fluctuating trend characterized by an initial decline succeeded by an upsurge, culminating under the Development–Ecological Balance Scenario. Likewise, HQ displayed a similar fluctuating pattern with an initial decline succeeded by an increase, reaching its zenith under the Ecological Dominance Scenario. (3) The coupling coordination between ESV and HQ exhibited variability across cities and scenarios. Ultimately, this study offers a distinctive perspective on evaluating the interplay between urban development and conservation, providing valuable insights for promoting sustainable development in other regions.