Abstract

Information about land use/cover is important and much more needed for different aspects of sustainable development and environmental management. Remote sensing datasets has become one of the most important and convenient tool to provide such information. The present study aimed to map land cover types for sub area in Al- Ahasaa Oasis, Saudi Arabia, using a subset of Landsat-ETM+ image. Different image preprocessing techniques in addition to a well-known and widely used classification method (i.e., Maximum Likelihood classifier) were applied. Accuracy assessment was carried out with 89% agreement and accepted according to the applied method. A different land cover classes were found in the study area, which includes (Sand dunes, Water bodies, Sabakha, Bare soil, Urban, and Agricultural lands). The study also revealed that the dominant land cover class is sand dunes with area approximately ± 70%. The study strongly indicated that the area has long been affected by sand movement. Finally, the study suggested that, further researches with more advanced methods rather than traditional methods are needed in the future to support the findings of this study, with a high degree of accuracy.

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