应用LSF概念模型反演草冠层叶面温度的试验

An Experiment on LSF Conceptual Model to Retrieve Grass Canopy Leaf Temperature

试验在已知土壤表面温度的前提下,分别利用AVHRR卫星遥感资料和准同步地面观测数据,应用LSF概念模型成功反演了草冠层叶面温度。通过对星、地资料反演的草冠层叶面温度比较发现,二者反演结果相差小于0.2K,说明利用卫星遥感资料,应用LSF概念模型反演草场冠层叶面温度可获得比较满意的结果。假设其他参数不变,分别对不同叶面发射率和不同土壤表面发射率反演的叶面温度分析发现,组分发射率的估算精度对反演结果影响较小,而整层空气柱可降水量的估算精度对卫星资料反演草冠层叶面温度影响大,用探空资料和露点温度估算的整层空气柱可降水量可导致反演的叶面温度相差达1.1K。在水分供应充足条件下,晴天11:00—17:00时,即使太阳总辐射强,叶面温度的变化幅度比土壤表面温度、空气温度小。以1999年8月6日为例,叶面温度变化仅有1.22K,而同时土壤表面温度变化为9.5K,1.5m高的空气温度变化为6.0K,叶面温度变化幅度比土壤表面温度、空气温度平缓。试验结果还表明,采用Becker和李召良的分裂窗模型反演青藏高原东南缘地区的陆地表面温度效果较好。

An experiment was conducted successfully to retrieve the leaf temperature of grass canopy by applying LSF conceptual model on data obtained on August 6, 1999 from AVHRR and synchronized ground observations with the known soil surface temperatures beforehand. The difference between the retrieved leaf temperatures from these two different data sources is less than 0. 2k, which means that the grass canopy leaf temperature can be retrieved satisfactorily through LSF conceptual model combined with satellite data. Further analysis on the retrieved leaf temperatures under different leaf and soil emissivity conditions reveals that the estimated accuracy of component emissivity shows little impact on the retrieved results, whereas the estimated accuracy of the precipitable vapor in the whole layer of the air column could affect the retrieved leaf temperatures significantly. The precipitable water vapour estimated based on the sounding data and dew-point temperature can lead to an error up to 1. l k in the retrieved leaf temperatures. When there exists sufficient vapour in the air, the variance of leaf temperature is only 1.22k in spite of the quite intensive solar radiation during 11.00-17.00 on fine days. In contrast, the variance of soil surface temperature can be 9.5k and the variance of air temperature at the height of 1.5m is 6.0k, therefore the variance of leaf temperature is much less than that of the soil surface temperature and air temperature. The experimental results also show that in the southeastern Tibetan plateau, the land surface temperature can be retrieved with quite high accuracy by Becket and Li＇s split window algorithm.