【摘要】 遥感地表温度产品是城市热环境演变研究的重要数据源。然而，受遥感器回访周期长及云雨天气情况下数据缺失等因素影响，高分辨率地表温度产品的代表性不足，导致精细尺度下城市长时序热环境的研究受限。本研究利用Landsat和MODIS遥感数据，采用时空融合方法重建了2013年—2022年武汉市核心城区夏季长时序高分辨率地表温度均值，并在精细尺度对武汉市热环境演变进行了分析。结果表明：（1）重建的高分辨率地表温度均值产品与地面站点观测数据具有较强的一致性，同时可以反映精细尺度下城市热环境时空变化的高度异质性；（2） 2013年—2022年，武汉市主城区高地表温度区占比呈现降低趋势并沿新城组群向周边区域扩张，原本独立的高温区域逐渐连接成片；（3） 2013年—2022年，武汉市各新城组群夏季高地表温度区除东南新城组群外皆呈现出扩张趋势，其中北部、西部、西南部扩张明显。本研究可为精细尺度下城市热环境的时空格局研究提供支撑，对城市生态文明建设和可持续发展具有重要意义。更多还原

【Abstract】 Remote sensing-derived Land Surface Temperature(LST) products are essential for studying urban thermal environment dynamics. However, limitations, such as long revisit intervals of remote sensors and data gaps caused by cloudy or rainy weather, hinder the representativeness of high-resolution LST products. As a result, long-term studies on urban thermal environments at fine spatial scales remain constrained. This study aims to reconstruct high-resolution summer mean LST data for Wuhan’s core urban area from 2013 to 2022 by using Landsat and MODIS remote sensing data through spatiotemporal fusion methods and to analyze the evolution of Wuhan’s thermal environment at a fine scale. The research employed spatiotemporal fusion techniques to integrate Landsat and MODIS data and reconstruct long-term high-resolution summer mean LST for Wuhan’s core urban area. The study area covered Wuhan’s central city and urban development zones. Validation was conducted using ground meteorological station data, and accuracy was assessed through Mean Absolute Error(MAE), Root Mean Squared Error(RMSE), and R2 metrics. LST classification and trend analysis were performed to examine the spatiotemporal patterns of thermal environment changes. Result(1) The reconstructed high-resolution mean LST product demonstrated strong consistency with ground observations(MAE=0.478 ℃, RMSE=0.5965 ℃, R~2=0.8538), effectively capturing the high spatiotemporal heterogeneity of urban thermal environments at fine scales.(2) From 2013 to 2022, the proportion of high-temperature zones in Wuhan’s main urban area decreased while expanding toward surrounding new town clusters along the development axes, with previously isolated high-temperature areas gradually merging.(3) During 2013—2022, all new town clusters, except the southeastern cluster, exhibited expanded high-temperature zones, with notable growth in northern, western, and southwestern areas. Conclusion This study provides an effective approach for reconstructing high-resolution LST data and analyzing fine-scale urban thermal environment patterns. The findings offer valuable insights into urban ecological civilization construction and sustainable development, supporting evidence-based urban planning and heat island mitigation strategies. The methodology and results help advance research on the spatiotemporal patterns of urban thermal environments at fine scales.更多还原