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基于Landsat数据的重庆市热环境时空格局变化研究

Spatial-Temporal Pattern Change of Thermal Environment in Chongqing Based on Landsat Data
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摘要 针对当前热环境加剧对城市生态环境和人类健康带来的严重威胁,采用辐射传输方程法和Landsat数据对2001年和2019年重庆市主城九区地表温度(Land Surface Temperature,LST)进行反演,对研究区城市热环境时空变化进行研究。基于此选取景观指数和驱动因子对热力景观格局变化和热环境驱动机制进行研究。结果表明:①2001—2019年,重庆市主城九区城市热环境明显增强,高温区域明显增多且整体向北扩张,到2019年LST总体呈现“内高外低”的分布格局。②中温区最大斑块指数增长了近12倍,代替次低温区成为研究区优势斑块类型。斑块数量和密度均下降了约62%,说明重庆市主城区的热力景观总体上呈聚集化,连通性较强。③NDVI和DEM与LST呈负相关,NDBI与LST呈正相关,影响程度为NDBI>NDVI>DEM。 The aggravation of thermal environment poses a serious threat to urban ecological environment and human health.The radiative transfer equation and Landsat data is used to retrieve Land Surface Temperature(LST)of downtown area of Chongqing in 2001 and 2019 to study the spatiotemporal changes of the urban thermal environment in these areas.The changes of thermal landscape pattern and the driving mechanism of thermal environment in this area are analyzed based on the selected landscape indexes and driving factors.The results show that:①from 2001 to 2019,the urban thermal environment in the main city of Chongqing became terrible,and the high-temperature areas increased and expanded northward as a whole.By 2019,LST showed a distribution pattern of“high inside and low outside”;②by analyzing the thermal landscape pattern,the maximum patch index in the middle temperature area increased 12 times,replacing the sub low temperature area as the dominant patch type in the study area.The number and density of patches decreased by about 62%,indicating that the thermal landscape in the main urban area of Chongqing is aggregated and has strong connectivity;③NDVI,DEM and NDBI are the main factors affecting LST in the study area.NDVI and DEM have a negative correlation with LST,and NDBI has a positive correlation with LST.The degree of impact is NDBI>NDVI>DEM.
作者 孟珂宇 徐丽华 MENG Keyu;XU Lihua(College of Resources and Environment,Southwest University,Chongqing 400715,China)
出处 《无线电工程》 2024年第3期751-758,共8页 Radio Engineering
基金 国家自然科学基金(41671291) 西南大学实验技术研究项目资助项目(SYJ2021040)。
关键词 城市热环境 地表温度反演 Landsat数据 景观格局 urban thermal environment LST retrieval Landsat data landscape pattern
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