Monitoring LU/LC Changes in El-Fayoum Governorate Using Support Vector Machine

Since the 1980s, El-Fayoum has witnessed several changes in land use. Images from Landsat satellites were used to examine the changes in land use/cover in EL-Fayoum from 2000 to 2020. For assessing quantitative data and processing satellite images for this study area’s assessment of land use change, Google Earth Engine (GEE) and ArcGIS Pro were utilized. GEE makes the processing and preprocessing required for satellite images fast and easy. The supervised land use classification process was compared by using a support vector machine algorithm (SVM) and maximum likelihood (MLH). SVM was better in accuracy than MLH, which was a respectable result for monitoring changes. It was discovered that within 20 years, 94.22 and 6.39 km2 of deteriorated agricultural land had been converted into urban areas and desert regions. Another 143.72 and 111.96 km2 of desert land were transformed into agricultural land and urban areas, respectively. The area of the water body decreased from 337.76 to 315.44 km2 with an annual change rate of −1.11%. The urban area increased from 200.70 to 350.34 km2 with an annual change rate of 7.48%. The findings of this study will be useful in organizing and putting into practice crucial management choices in order to preserve El-Fayoum’s biodiversity.