基于MODIS和TM数据的陆面温度反演

Land Surface Temperature Retrieval Based on MODIS and TM Data

陆地表面温度(LST)反演一直是热红外遥感研究中的一大难题。目前,分辨率较高的Landsat5/TM数据是陆地表面温度(LST)反演的常用遥感信息源。然而,由于TM只有一个热通道,大多数情况下由TM6数据得到的都是星上亮度温度,与实际地表温度有较大差距。普适性单通道算法的提出为从TM6数据高精度地反演地表真实温度提供了可能。为寻找一条从TM6数据高精度反演陆地表面温度的有效途径,利用该算法对北京地区的地表温度进行了反演试验,对该算法必需的总大气水蒸汽含量通过MOD IS数据计算获得。同时利用卫星过境时的同步实测数据对反演精度进行了检验,并与用标准大气数据得到的结果进行了比较。其结果表明,该方法具有较高的反演精度,其rmsd值为1.67℃,显示了多源数据结合的优势。

Land surface temperature（LST） retrieval has been a key issue in the thermal infrared remote sensing research area. Landsat5 TM data with a higher spatial resolution thermal infrared band of 120m was often used to retrieve land surface temperature. However, the fact that Landsat 5 possesses only one thermal infrared band is also a critical limitation for LST retrieval. In most cases, only at-satellite brightness temperature was thus obtained from TM6 data, which is far different from the land surface temperature. Hence the precision of land surface temperature retrieval was actually not so satisfied. While the proposal of the generalized single-channel algorithm in 2003 makes it possible to figure out land surface temperature from TM6 data with high precision. Based on this algorithm, a test for land surface temperature retrieval of Beijing region was carried out with Landsat 5 TM data acquired on 6 May 2005. MODIS data received on the same day was used to compute the total atmospheric water vapor content which is necessary for the algorithm. Furthermore, the retrieving result has been validated using simultaneously measured in situ data, and compared with that of using standard atmosphere data. A significantly high precision with a root mean square deviation（rmsd） of 1.67℃ has been achieved by the approach introduced in this paper, which shows the advantages of synthetically utilizing multi-satellite data.