Multi-temporal assessment of land use/land cover change in arid region based on landsat satellite imagery: Case study in Fayoum Region, Egypt

Human activities impact the ecological conditions of the environment. To understand those impacts and achieve sustainable management; studying, detecting and monitoring land use/land cover (LULC) are required. This study's goal is to monitor the change in LULC in Fayoum governorate, Egypt, using maximum likelihood classification (MLC) and normalized difference vegetation index (NDVI). Landsat satellite images of 1984, 2001, and 2016 were utilized to determine the changes in LULC in the study area (3077 km(2)). Ground truth points were collected in 2016 and employed to perform the accuracy assessment for the classified maps. Four LULC classes were determined based on MLC; agricultural land, urban area, barren land, and water class. Based on NDVI, two classes were categorized; vegetated and non-vegetated. The results showed that the MLC accurately identified the LULC classes with an overall accuracy of 96%. Thus, this technique is recommended for classifying the satellite images in such areas.