A new methodology for cloud detection and classification with ASTER data

摘要: [1] High spatial resolution sensors such as Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) have the potential to produce gridded, large area datasets of surface parameters elevation emissivity. These are typically derived by combining all clear-sky pixels over a given location for specified time period necessitating use an automated cloud detection classification algorithm. The current ASTER L1A mask lacks several key features needed it this purpose. We developed new algorithm which addresses these limitations using 2-pass approach similar Landsat-7 including further spectral tests cirrus shadows from MODIS. methodology is described together with case studies that highlight aspects comparisons MODIS mask.