Abstract

Land surface temperature is a significant source of energy budget and climate information, contributing to various environmental and biophysical processes. This research includes comparing the LSTs retrieved from the ASTER sensor using the Reference Channel method, the Emissivity Normalization method (NOR), TES method and Retrieving LSE by taking the proportion of vegetation cover coupled with NDVI and integrates it into the TES algorithm. The results of derived LST from the four algorithms compare with MODIS data of 7 control points having thermally homogenous sites. The analysis showed that the four algorithms are suitable for LST retrieval, whereby the proposed emissivity-derived NDVI algorithms exhibited the highest degree of accuracy (RMSE 0.145), and the NOR had the least accuracy (RMSE 0.403). The analysis shows that emissivity derived NDVI TES method more reliant on the upwelling, downwelling and transmittance and will achieve the best results compared to the other three algorithms.

摘要

地表温度是能量收支和气候信息的重要来源，有助于各种环境和生物物理过程。本研究包括比较使用参考通道方法、发射率归一化方法（NOR）、TES 方法从 ASTER 传感器反演的 LST 以及通过植被覆盖比例与 NDVI 耦合反演 LSE 并将其集成到 TES 算法中。四种算法导出的 LST 结果与 7 个具有热均质位点的控制点的 MODIS 数据进行了比较。分析表明，四种算法都适用于 LST 反演，其中所提出的基于发射率的 NDVI 算法表现出最高的准确度（RMSE 0.145），而 NOR 的准确度最低（RMSE 0.403）。