利用多源遥感数据反演城市地表温度

Study on Retrieval Urban Land Surface Temperature with Multi-source Remote Sensing Data

目前利用单通道热红外遥感数据反演地表温度的方法有大气校正法、单窗算法和普适性单通道算法,使用这3种算法反演地表温度时的一个关键问题就是需要获取大气参数。目前大气参数的获取主要根据近地表(地表2m左右的高度)的大气水分含量或湿度和平均气温的观测值来估计,这种方法只能获得个别点上的数据,而无法获取面上像元尺度的大气参数。本文利用多源遥感数据的优势,首先利用MODIS近红外数据,在像元尺度上获取温度反演中所需大气参数——大气水分含量,再利用同时相的Landsat ETM+影像,采用Jim啨nez-Mu oz和Sobrino的普适性单通道算法反演地表温度。研究结果表明,多源遥感数据的综合应用是城市地表温度反演的有效途径与方法,可获得较合理的地表温度反演结果。

Now there are three methods for land surface temperature retrieval from single channel thermal infrared remote sensing data, that is, atmospheric correction, mono-window algorithm and single-channel algorithm. The atmospheric parameters are required while using these methods for retrieving land surface temperature. Generally, the atmospheric parameters are estimated by using the atmospheric water vapor or humidity and average air temperature above near sudace（2 meters＇ height）. This method can only obtain data from several points. In this paper, the distribution of atmospheric water vapor content was calculated by two channel ratio method based on MODIS near infrared data. Then, land surface temperature was retrieved by using the thermal infrared band of Landsat ETM ＋ and a generalized single-channel method developed by Jiménez-Mufioz and Sobrino. The exploited approach was applied to Changsha and Wuhan city. The results show that the combination of multi-source remote sensing data is effective for retrieving urban land surface temperature and can yield a reasonable estimation of land surface temperature.