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Автор MAHAR, K.
Автор AFIFI, M. S.
Дата выпуска 1995
dc.description AbstractA major source of quantitative data, which contains information that can be used in the classification of land covers, is the Landsat series of low orbiting spacecrafts, which began in 1972 with Landsat-1. The later versions of this series, starting with Landsat-4 and -5 are equipped with Thematic Mapper ( TM) sensor systems, which generate a vector for different intensity responses, of each pixel, in seven light and infrared spectral bands. With knowledge of different spectral responses of land covers it is possible to identify categories when analysing the vector data formats. This paper introduces a computerized procedure which is believed to be effective in identification of land covers. The method is particularly applicable to the Thematic Mapper system. It combines the linear analysis with the correlation procedures in specific formats, using a small number of reference identifiable categories in order to aggregate and pinpoint the pixel contents ( with small probability of error). Fine identification of categories ( such as the separation of corn or wheat in the vegetation covers) is the subject of further promising applicability using this described computerized technique.
Формат application.pdf
Издатель Taylor & Francis Group
Копирайт Copyright Taylor and Francis Group, LLC
Название Linear and correlation analysis for computerized identification of categories in Landsat images
Тип research-article
DOI 10.1080/01431169508954555
Electronic ISSN 1366-5901
Print ISSN 0143-1161
Журнал International Journal of Remote Sensing
Том 16
Первая страница 2277
Последняя страница 2284
Аффилиация MAHAR, K.; College of Computer and Information Sciences, King Saud University
Аффилиация AFIFI, M. S.; College of Engineering, Electrical Engineering Department, King Saud University
Выпуск 12

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