一种改进的矩匹配方法在CMODIS数据条带去除中的应用

由于传感器之间对接受的地物辐射信号的响应特性不同,导致CMODIS数据中的许多波段含有大量的条带。这些噪声严重影响了CMODIS数据的解译和信息提取。介绍了几种常用在TM、MSS、SPOT等多传感器光谱仪中条带去除方法,提出了一种改进矩匹配方法用于CMODIS数据中的条带去除,并比较了这种方法和其它几种常用方法对几何纠正前非均匀地物分布的CMODIS数据的去条带噪声结果。结果表明这种新方法要优于以上提到的几种常用方法,具有很好的去条带噪声效果,同时保持图像原有的的信息。这种方法在其它多传感器遥感图像的条带噪声去除中也有很强的适用性。

Destriping in CMODIS Data by A Improved Moment Matching

Some primary land surface parameters needed in hydra-meteorology models can be retrieved from multispectra remote sensing data, and then the distribution map of Evapotranspiration(ET),which is very important in water resources management, can be made. Remote sensing retrieval of ET relates to some physical processes, and the validation and improvement of the retrieval results need to know about the techniques and methods to be used to monitor ET in situ, which is introduced briefly in this paper. Then the methods and development of retrieving ET by means of remote sensing are reviewed, especially the Surface Energy Balance Algorithm for Land(SEBAL in short) is demonstrated in detail.