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IIJIT:Volume 6, Issue 4, April 2018

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Title:
Land Use Land Cover Classification and mapping for Al-Ulaa area: Saudi Arabia
Author Name:
Omar M.S. Al-kouri
Abstract:
ABSTRACT: Remote sensing softwares, (PCI) provide a power full tool for land use land cover feature detection, its help to classify urban and agriculture coverage area. In particularly the classification of IKNOS satellite image (Al-Ulaa area) provide land cover information which need to divide, and calculate the classes area of land cover land use separately (class by class), to get more accurate accounted for each type of feature area. Thus temporal IKNOS image base on supervised classification approach were used to extraction of urban and agriculture over the study area (Al-Ulaa) area. Remotely sensed data were analyzed and processed using feature extraction based image processing techniques. The result of this study shown, the agriculture class has a largest class on the study area 118 KM, but the urbanization is increasing over the time about 20.76% compare to historical data, This extensive and expansion change of agricultures due to fast development of urbanization. Keywords: Remote Sensing, land use land cover, feature detection, classification
Cite this article:
Omar M.S. Al-kouri , " Land Use Land Cover Classification and mapping for Al-Ulaa area: Saudi Arabia " , IPASJ INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY (IIJIT) , Volume 6, Issue 4, April 2018 , pp. 012-018 , ISSN 2321-5976.
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