Wang Dongchao, Cao Jianfei, Zhang Baolei, Kong Kangning, Wang Run
College of Geography and Environment, Shandong Normal University, Jinan, Shandong, China.
Shandong Provincial Territorial Spatial Ecological Restoration Center, Jinan, Shandong, China.
PLoS One. 2024 Sep 16;19(9):e0307711. doi: 10.1371/journal.pone.0307711. eCollection 2024.
The prolonged dependence on industrial development has accentuated the cumulative effects of pollutants. Simultaneously, influenced by land construction activities and green space depletion, the Urban Heat Island (UHI) effect in cities has intensified year by year, jeopardizing the foundation of sustainable urban development. Prudent urban spatial planning holds the potential to robustly ameliorate the persistent deterioration of the UHI phenomenon. This study selects Jinan City as a case study and employs spatial autocorrelation and spatial regression algorithms to explore the spatiotemporal evolution of urban-rural patterns at the township scale. The aim is to identify key factors driving the spatiotemporal differentiation of Land Surface Temperature (LST) from 2013 to 2022. The research reveals a trend of initially rising and subsequently falling LST in various townships, with low-temperature concentration areas in the southern mountainous region and the northern plain area. The "West-Central-East" main urban axis and the southeast Laiwu District exhibit high-temperature zones. Significant influences on LST are attributed to pollution levels, topographical factors, urbanization levels, and urban greenness. The global Moran's Index for LST exceeds 0.7, indicating a strong positive spatial correlation. Cluster analysis results indicate High-High (HH) clustering in the central Shizhong District and Low-Low (LL) clustering in the northern Shanghe County. Multiscale Geographically Weighted Regression (MGWR) outperforms Geographically Weighted Regression (GWR) and Ordinary Linear Regression (OLR), providing a more accurate reflection of the regression relationships between variables. By investigating the spatiotemporal evolution of LST and its driving factors at the township scale, this study contributes insights for future urban planning and sustainable development.
对工业发展的长期依赖加剧了污染物的累积影响。与此同时，受土地建设活动和绿地减少的影响，城市热岛（UHI）效应逐年加剧，危及城市可持续发展的基础。审慎的城市空间规划有潜力有力地改善城市热岛现象的持续恶化。本研究选取济南市作为案例研究，采用空间自相关和空间回归算法，探索乡镇尺度上城乡格局的时空演变。目的是识别2013年至2022年地表温度（LST）时空分异的关键驱动因素。研究发现，各乡地表温度呈现先上升后下降的趋势，南部山区和北部平原地区为低温集中区。“西-中-东”城市主轴线和东南部的莱芜区为高温区。对地表温度有显著影响的因素包括污染水平、地形因素、城市化水平和城市绿化程度。地表温度的全局莫兰指数超过0.7，表明存在很强的正空间相关性。聚类分析结果表明，市中区中部为高高（HH）聚类，北部商河县为低低（LL）聚类。多尺度地理加权回归（MGWR）优于地理加权回归（GWR）和普通线性回归（OLR），能更准确地反映变量之间的回归关系。通过研究乡镇尺度上地表温度的时空演变及其驱动因素，本研究为未来城市规划和可持续发展提供了见解。
