基于Landsat-8数据和劈窗算法的地表温度反演及城市热岛效应研究

宋挺1; $22; $23; 严飞1; 黄君1; 吴蔚1

引用本文:	宋挺1，段峥2，刘军志3，严飞1，黄君1，吴蔚1.基于Landsat-8数据和劈窗算法的地表温度反演及城市热岛效应研究[J].环境监控与预警,2014,6(5):4-14
	SONG Ting1, DUAN Zheng2, LIU Jun zhi3,YAN Fei1,HUANG Jun1,WU Wei1.Land Surface Temperature Retrieval from Landsat 8 Data using Split window Algorithm and Its Application on the Study of Urban Heat Island Effect[J].Environmental Monitoring and Forewarning,2014,6(5):4-14

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基于Landsat-8数据和劈窗算法的地表温度反演及城市热岛效应研究
宋挺1，段峥2，刘军志3，严飞1，黄君1，吴蔚1^1,2
1. 无锡市环境监测中心站，江苏无锡 214121;2. 代尔夫特理工大学,代尔夫特,2628 CN,荷兰

摘要:

陆地表面温度（Land Surface Temperature, LST）是地表能量平衡组分中的一个重要参数。随着卫星遥感技术的快速发展，遥感反演成为获取区域LST的一个重要手段。目前已有学者提出多种基于遥感数据反演LST的算法，其中劈窗算法被证明是一种精度较高的算法。基于 Landsat-8卫星30 m空间分辨率的陆地成像仪（OLI）数据和100 m分辨率的热红外传感器（TIRS）数据，采用劈窗算法计算了无锡地区的LST，并采用地面实测水温数据和同步的MODIS温度产品对Landsat-8的计算结果进行了验证和对比分析。结果表明：基于Landsat-8数据和劈窗算法获取的LST精度较高，误差< 1K。在计算的LST结果基础上，进一步提取了热场变异指数来分析城市热岛空间分布特征，给出了城市热岛效应的定量化描述，并就不同地表覆盖类型对热岛效应的影响进行了分析。

关键词: 陆地表面温度 Landsat-8 劈窗算法热红外热岛效应

DOI：

分类号:X87

基金项目:

Land Surface Temperature Retrieval from Landsat 8 Data using Split window Algorithm and Its Application on the Study of Urban Heat Island Effect

SONG Ting1, DUAN Zheng2, LIU Jun zhi3,YAN Fei1,HUANG Jun1,WU Wei1^1,2

1.Wuxi Environmental Monitoring Central Station,Wuxi, Jiangsu 214121,China;2.Delft University of Technology, Delft, 2628 CN,Netherlands

Abstract:

Land Surface Temperature (LST) is an important parameter of surface energy balance components. With the rapid development of satellite remote sensing technology, satellite remote sensing has become an important approach to retrieving LST over large areas. Various satellite based retrieval algorithms have been proposed, and the Split Window algorithm has been proved to be a high precision algorithms. In this study, the LST of Wuxi was retrieved from Landsat 8 data with the SW algorithm. The retrieved LST data were further compared with both simultaneous ground measured temperature data and the MODIS LST product. Results showed that the retrieved LST had good accuracy with errors of less than 1 K. Furthermore, the Thermal Field Variance Composite Index computed from the retrieved LST data was used to analyze the spatial distribution of urban heat island. The urban heat island effect was quantified, and the effects of different land cover types on the heat island were also investigated.

Key words: Land surface temperature Landsat 8 Split window algorithm Thermal infrared Heat island effect