Landsat TM 遥感影像中厚云和阴影如何去除
loud processing algorithms differ depending on the cloud status. Dynamic filtering method is suitable for the case that there exists relatively wide range of cloud in the image. Dynamic filtering method, combining the frequency filtering and gray value change, separates cloud and background features, and finally removes the cloud influence from the remote sensing image. Because this approach relates to the frequency filters and needs the choice of cutoff frequency, the useful information sometimes is lost in the filtering process. Moreover this approach can not be used for the thick cloud. For the local cloud distribution regions, the time average method is generally used. This algorithm can only be used in the region in which the surface feature change along the time is very small. For the dense vegetation cover region, due to vegetation growth is closely related with time, vegetation indices of different time are significantly different from each other. Therefore, such a simple substitution algorithm can not be used in this case. To solve the above problem, in this paper, the author suggests a new cloud removal method that uses the Landsat TM image data of the same region at different time. It uses the TM remote sensing image data of the same period, or nearly the same season in different years. Based on each band’s relative change of spectral characteristics, an enhancement model of thick cloud and its shadow is designed. In conjunction with these models and conventional unsupervised automatic classification method, image matching technique using linear regression analysis and pixel replacing operation, the cloud influenceReceived: 2009-06-12; Accepted: 2009-09-25 Foundation: Study on Methodologies in Geography (No. 2007FY140800). First author biography: RI Pyongsop (1970— ), male, doctor student. He graduated in 1993 from Kim Chaek University of Technology, Democratic People’s Republic of Korea. His research interest is remotely sensed imagery. E-mail: pyongsop@RI Pyongsop et al.: Cloud and shadow removal from Landsat TM data535can be eliminated or reduced from the Landsat TM remote sensing image data. The result shows that the algorithm can eliminate or reduce the cloud influence from the Landsat TM image data22.1STUDY AREA AND DATA SOURCEBrief description of the study areaThe study area is located in the central and western region of Korean Peninsula ranging from 125° 00 'E to 126° 10'E and from 38° 15 'N to 39° 30'N. The distance of a straight line between eastern and western end is about 105.84km, the distance of a straight line between north and south end is about 137.46km. The study area is about 14000km2. The region contains a variety of terrains including mountains, plains, sea, and so on. It contains a variety of land use/cover types including woodland, grassland, paddy fields, dry fields, salt, urban and industrial land, bare soil, reservoirs, lakes, canals, and tideland and so on. The spatial dis