Sentinel-2 Satellite Framework for Remote Sensing Imagery: Detecting Land-Cover Change in Egypt
Land-cover change detection plays a critical role in understanding environmental and urban development patterns. With the rise of satellite imagery and remote sensing technologies, it has become possible to detect changes across vast landscapes with high accuracy and in real-time. This report focuses on using Sentinel-2 satellite imagery to monitor and detect land-cover changes in Sadat City, Egypt, a rapidly urbanizing area. The imagery was analyzed using remote sensing techniques and GIS tools to classify six major land-cover types: vegetation, water, desert, roads, urban areas, and bare ground (BG).
Dataset
The primary dataset for this study was acquired from: National Authority for Remote Sensing and Space Sciences (NARSS) Ministry of State for Scientific Research (Egypt) Additional satellite images were sourced from openly accessible platforms: ESA (European Space Agency) Sentinel Hub The Sentinel-2 satellite provides high-resolution multispectral images, covering the visible, near-infrared, and thermal infrared bands. These data sources allow for in-depth classification of land cover and enable the detection of changes over time. Data Classes The dataset is composed of six main classes: Vegetation: Includes areas covered by crops, forests, and grasslands. Water: Represents bodies of water like lakes, rivers, and reservoirs. Desert: Comprises barren sandy landscapes common in arid regions. Roads: Urban infrastructure and transportation networks. Urban: Built-up areas such as residential, commercial, and industrial zones. Bare Ground (BG): Areas with little to no vegetation, primarily soil or exposed land. These classes were defined based on the multispectral characteristics of the satellite imagery, which makes it easier to distinguish between different land covers.
Results
he classification of land cover in Sadat City revealed significant trends in urbanization and land-use change. Below are the key findings from the analysis of the satellite imagery:
