大气水分含量的空间异质性及其对地表温度反演的影响

Spatial Heterogeneity of Atmospheric Water Vapor and Its Influence on the Retrieval of Land Surface Temperature Based on Remote Sensing Data

大气水分含量是影响单波段热红外地表温度反演的关键因素之一。研究大气水分含量空间异质性对地表温度反演的影响误差有助于单波段热红外数据的合理应用。以MODIS MOD 05_L2产品为数据源,探讨区域大气水分含量的空间异质性及其对Landsat地表温度反演的影响。在推导大气水分含量对地表温度反演误差模型的基础上,针对Landsat5热红外波段,结合不同区域的大气水分含量分布状况,对大气水分含量的空间异质性可能引起的地表温度反演误差进行了模拟计算与对比分析。结果显示,大气水分含量空间异质性对地表温度反演的影响与大气水分含量及其异质性程度有关：当大气水分含量的空间异质性相对较大时,误差值和误差范围都比较大,达到0.5~2℃,相对误差为2%~20%;当大气水分含量空间分布较均匀时,误差值和误差范围为0.1~0.2℃,相对误差为0.5%~2%。可见,对于空间异质性程度较大的区域,区域面上大气参数的获得对地表温度的准确反演具有重要意义。

Atmospheric water vapor is one of the key factors affecting the retrieval of land surface temperature（LST） from the single-band infrared image.It is conductive to the rational usage of single-band infrared data to find out the influence of spatial heterogeneity of AWV on the retrieval of LST.With the MODIS MOD05_L2 products as data sources,this paper discussed the spatial heterogeneity of AWV at the regional scale and its impact on the retrieval of LST from Landsat image.Firstly,an error model was deduced with regard to the influence of AWV on the retrieval of LST from remote sensing data.Then,in order to explore the retrieval error of LST possibly caused by the spatial heterogeneity of AWV at the regional scale,the authors conducted simulation tests followed by comparative analyses under spatially different distribution conditions of AWV in several regions,particularly for the thermal infrared band of Landsat 5.Results obtained in this paper indicate that the retrieval error of LST caused by the spatial heterogeneity of AWV has to do with the value and the heterogeneity degree of AWV.For example,when AWV had relatively high heterogeneity,an error was relatively great,ranging from 0.5℃ to 2℃ with relative error from 2% to 20% accordingly;by contrast,when AWV was relatively uniform,error was comparatively insignificant and ranged from 0.1℃ to 0.2℃ with relative error from 0.5% to 2% accordingly.In conclusion,with regard to regions with a relatively high degree of atmospheric heterogeneity,it is vital to get atmospheric parameters properly at the regional scale so as to retrieve LST precisely from remote sensing data.