期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2010
卷号：XXXVIII - Part 7B
页码：47-50
出版社：Copernicus Publications
摘要：Rainy clouds having high densities are considered as one of the main causes of flood events, therefore detection and classification of clouds can be very valuable for flood forecasting. In this study NOAA/AVHRR satellite images were used for object oriented classification. Sixteen bands were produced and utilized for cloud classification. This included the main five bands of NOAA/AVHRR and other important information such as albedo of band 1 and 2, brightness temperature of band 3,4 and 5, solar zenith and azimuth angles, land surface temperature, sea surface temperature, normalized difference vegetation index, deviation of nadir and cloud height. Multi-resolution segmentation followed by bi-spectral technique and hierarchical classification were performed using the sixteen produced layers. The obtained kappa coefficient and the overall accuracy were relatively high (kappa= 0.887, overall Acc.= 0.905). The results of the study demonstrated that the object oriented classification can be considered as a proper method for cloud detection and classification
关键词：Cloud Classification; Segmentation; Object Orient; Texture; Pattern; Bi-spectral; Brightness Temperature
