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云覆盖是热红外遥感应用和地表温度(Land Surface Temperature,LST)遥感定量反演的重要障碍。如何估算热红外遥感图像中云覆盖像元的地表温度,是热红外遥感的前沿研究难题。以地表热量平衡为基础,根据地表温度的空间分布连续性、植被对地表温度的影响,提出三种解决云覆盖像元地表温度估算方案:空间插值修正法、植被关系修正法和改进型地表热量平衡法,并探讨云覆盖区地表温度空间分布的洼地效应现象、洼地效应强度及计算方法。基于地表热量平衡方程的洼地效应强度因子和影像灰度值之间关系的数值模拟,是三种估算方案切实可行的关键。
Cloud coverage is an important obstacle to the quantitative retrieval of the remote sensing by thermal infrared remote sensing applications and Land Surface Temperature (LST). How to estimate the surface temperature of cloud-covered pixels in thermal infrared remote sensing images is a research challenge in the front of thermal infrared remote sensing. Based on the surface heat balance, three solutions are proposed to estimate the surface temperature of cloud-covered pixels based on the spatial distribution continuity of surface temperature and the effect of vegetation on the surface temperature: spatial interpolation method, vegetation relationship correction method and improved surface heat Balance method, and discusses the depression effect of the spatial distribution of surface temperature in the cloud cover area, the intensity of depression and its calculation method. The numerical simulation of the relationship between the depression intensity factor and the image gray value based on the surface heat balance equation is the key to the three estimation schemes.