通过遥感获取地表温度(地温,LST)可以弥补气象站地温数据局地性的不足。但受某些因素影响,遥感MODIS LST标准产品中的影像存在"云污染"等噪音像元以及空缺值,影响了LST数据应用。本文在利用LST产品的质量标记信息(QA)和直方图极值去除法过滤低质量、不可靠LST像元的基础上,提出了一种基于DEM-LST回归关系的滑动窗口空间重建算法,对2008年青藏高原东北部TERRA/AQUA上共4个温度通道的MODIS LST进行了重建,得到空间完整的LST时间序列。将重建后的LST与研究区11个气象站地表温度数据(T)的比较表必明上然,更在的没8 d联有ay系显合,著但成差是序异(仍列平然上均存LS绝在T-的对T误低一差水致分平性噪别很音为好1.表,5平5明℃均若和相需0.关要60系更℃数)高。达精L0.S度9T6的,与L平STT均存数绝在据对的需误差要差异更为与细2.0两致2者的℃的去;L时S云T空处与定理T义。在的月不、一年致的性尺度有 更多还原
【Abstract】 Land surface temperature(RS-LST) derived from remotely sensed data is a good alternative because traditional LST data from meteorological stations have limitations in terms of locality,accessbility and cost.Yet MODIS standard LST products from NASA may suffer from noises from various sources including‘cloud con-tamination,’ which greatly degrade the LST quality and hamper its efficient applications.The paper presents a novel algorithm which can reconstruct complete LST image based on regression ...