The analyses of land use and land cover (LULC) can identify the changes in natural resources and anthropogenic activities. Using remote sensing (RS) and Geographic Information System (GIS) techniques is essential for sustainable management, evaluation, and monitoring of the land surface dynamics. In this article, the spatiotemporal differences in LULC are detected and quantified using recent radar and optical remote sensing data. Applying normalized difference vegetation index (NDVI), Principal Component Analysis (PCA), and GIS-differences approaches on Landsat series (TM&OLI) data and Sentinel-2 images quantified the changes in vegetation. The results revealed that the eastern and northern sectors of the area experienced major changes in agricultural and residential activities. Multi-temporal change detection in vegetation between Landsat images for periods from 1992 to 2021 revealed an increase in vegetation reaching similar to 916 km2 as in 2021, vegetation covered an area of around 3759.35 km2, compared to 1992 which covered about 2843 km2. It is crucial for revealing changes in LU/LC in different environments, depending on the NDVI technique. Applying the Interferometry Synthetic Aperture Radar (InSAR) Coherence Change Detection (CCD) technique coupled with other methods of optical RS present valuable information regarding monitoring and observing spatiotemporal changes in the land surface in different climatic conditions. InSAR CCD that is an advanced implemented approach allowed revealing the minor land surface changes between the two dates of SAR images as the values close to 0 showed high changes. Overall, implementing optical and radar remote sensing approaches can observe and monitor the Earth's land surface on a spatiotemporal scale.