Jazan Region subjects mainly to environmental degradation due to anthropogenic activities. In the present study, remote sensing integrated with some mathematical treatments as overlay analysis for adequately evaluating land degradation of Jazan area. The present study focuses on vegetation, geological, urban, and coastal changes. Three satellite images were acquired for typically assessing these changes in 2008, 2014, and 2018. To detect the environmental degradation, normalized difference vegetation index (NDVI) and statistical model were used for vegetation, principal component analysis (PCA) and band ratios (b5/b7 and b3/bl) for geological changes, and normalized difference built index (NDBI) for urban degradation. Also, coastal changes had been detected using some analysis of ARCGIS. Results showed that NDVI in 2008, 2014, and 2018 were 5.7, 11, and 7.2%, respectively. From the linear model and statistical analysis of vegetation in the future, there is unaccountable disappearance of the vegetation by the end of 2020 with the disappearance of the evergreen areas of trees and desert plants around region. For geological changes, PCA of the three images give more than 80% of geological features of the study area. Band ratios, b5/b7 and b3/bl, emphasize alteration, clay, and Fe minerals that have specific spectral reflectance and absorption features in these bands. For coastal changes, the reasonable rate of beach growth was precisely 85.3% between 2008 and 2014, while this ratio positively declined to 14.7% between 2014 and 2018 of the economic expansion during the monitoring period from 2008 to 2018. Urban area of Jazan City was 262.34, 354.43, and 409.17 km2 for 2008, 2014, and 2018, respectively. Results showed that urban area has been increased from 2008 to 2018 with a percentage of 55.9%. The marked degradation may be reasonably anticipated to anthropogenic activities and unplanned management. Technology date should be applied universally to avoid environmental degradation of Jazan Region. Remote sensing and statistical model might offer an effective and good assessment of land degradation.