Monitoring LULC Changes in El-Fayoum Governorate using Support Vector Machine. |
Paper ID : 1094-ICRSSSA-FULL (R2) |
Authors |
Islam Atef Fouad *1, Wael Mohamed Ahmed2, Ramadan H. Abdel-Maguid1 1Civil Engineering Department, Faculty of Engineering, Fayoum University, Fayoum 63514, Egypt. 2Geomatics Engineering Lab, Civil Engineering Department, Faculty of Engineering, Cairo University, Giza 12316, Egypt. |
Abstract |
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 satel-lite images for this study area's assessment of land use change, Google Earth En-gine (GEE) and ARCGIS Pro were utilized. GEE makes the processing and pre-processing required for satellite images fast and easy. The supervised land use classification process was compared between using a support vector machine al-gorithm (SVM) and maximum likelihood (MLH). SVM was better in accuracy than MLH, which was a respectable result for monitoring changes. It was dis-covered that within 20 years, respectively, 94.22 km2 and 6.39 km2 of deteriorat-ed agricultural land had been converted into urban areas and desert regions. An-other 143.72 km2 and 111.96 km2 of desert land were transformed into agricul-tural land and urban areas, respectively. The area of the water body decreased from 337.76 km2 to 315.44 km2 with an annual change rate of -1.11%. The ur-ban area increased from 200.70 km2 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 biodiversi-ty. |
Keywords |
Google Earth Engine; Change detection; Support vector machine; remote sensing, GIS. |
Status: Accepted (Oral Presentation) |