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Spectral indices developed to extract features from satellite images are simple and fast methods that reduce processing time compared to traditional satellite image classification.In this paper, the effectiveness of the normalized difference building index (NDBI), the normalized difference vegetation index (NDVI), and the Normalized Difference Water Index (NDWI) were evaluated in land cover mapping and detecting its changes in the period from 2013 to 2023 in Fayoum Governorate, Egypt, using Landsat 8-OLI images. The results of supervised classification showed a decrease in green areas between 2013 and 2023 by 76.03 square kilometers, with a slight decrease in the areas occupied by water amounting to 3.8 square kilometers and an increase in built-up areas by 79.83 square kilometers, at the expense of green lands. On the other hand, the results of using spectral indices showed a decrease in green areas between 2013 and 2023 by 91.12 square kilometers, with a slight decrease in the areas occupied by water amounting to 3.35 square kilometers. Meanwhile, we noticed an increase in built-up areas by 94.47 square kilometers at the expense of green areas. The results showed a general convergence in the changes in the studied classes during the study period, with a great convergence in the change in the area of the water bodies resulted from the classification and from the NDWI and a convergence in the effectiveness of both the NDVI and NDBI.

Copyright of Journal of The Planner & Development is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The main aim of this present study is to identify and detect the land use, land cover changes occurred in the Ambo Woreda of West Shewa Zone in Ethiopia and to integrate the Remote Sensing and GIS data for analyzing and evaluating the changes in land-use of study area. Based on remotely sensed data, the Land Use Land Cover (LULC) maps and field records have been considered for investigation. Landsat7 ETM+ image of 2000 and Sentinel 2A image of 2020 are the two remotely sensed images of study area used in this study. The supervised classification based on maximum likelihood classifier in ArcGIS 10.3 has been used to identify the five major categories of LULC. The observation on the period of twenty years reveals that the agricultural land and built-up areas have stretched rapidly to the adjacent fallow lands. Also, there is significant loss in Hilly Vegetation due to settlements and industrial expansion in the fastest growing region of the Oromia Zone.

Copyright of Journal of Water & Soil Conservation is the property of Gorgan University of Agricultural Sciences & Natural Resources and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)