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This work highlights the estimation of the Al-Khoser River water case that disposes of its waste directly into the Tigris River within Mosul city. Furthermore, the work studies the effects of environmental and climate change and the impact of pollution resulting from waste thrown into the Al-Khoser River over the years. Al-Khoser River is located in the Northern Mesopotamia of Mosul city. This study aims to detect the polluted water area and the polluted surrounding area. Temporal remote sensing data of different Landsat generations were considered in this work, specifically Enhanced Thematic Mapper Plus of 2000 and Operational Land Imager of 2015. The study aims to measure the amount of pollution in the study area over 15 years using a supervised classification approach and other tools in ERDAS  Imagine Software version 2014. Supervised classification is favored for remote sensing data processing because it contains different digital image processing methods. It is noticed by applying to preprocess and post-processing techniques adopted in the polluted section of Al-Khoser River and monitoring the changes in the objects around it. Hence, the river’s water has been classified into clear water and contaminated water, which shows the impact of pollution over the years. The analysis detected a polluted area in the river that enlarged over the years 2000 to 2015 from 4.139 km² to 21.45 km², respectively. The study showed the differences in the size of objects around the river. The study concludes that daily wastes produced by the residential areas through which Al-Khoser and Tigris rivers pass would cause the polluted sections of the river to increase.

The aim of this work concentrates on utilizing powerful MATLAB programming (software version R2016a) to evaluate the impact of environmental variations of water case in the Mosul Dam reservoir and observed its receding impact on human life activities based on composite image processing applications. Furthermore, composite materials of different temporal remote sensing data increase powerfully the estimation of environmental variables of relevance to human health. Thus, temporal remote sensing data trends to enhance the efficiency of detecting receding water resources effect of human life impacts over different years. Two steps were implemented, which focuses on the estimation of changes in the water surface of the lake over 31 years. Preprocessing step concentrates on composite data materials from different Landsats to be more suitable for next step by utilizing color composite image processing and postprocessing step implemented the coastline detection of the reservoir and recognition of the quality of clear water in the lake due to the variation of water spectral reflectivity by hybrid classification method. The performance of this study is based on statistics measurements on the surface area of water level and overall accuracy, which indicated that hybrid classification method improves the capacity of integrating two classification methods, which gained highly identification water lake classes regarding its quality and more. The obtained results achieved the desired purpose of this study to investigate the high power application through implementing composite different image processing techniques with temporal satellite data to conversance the amount of water level changes in Mosul Dam reservoir and its impact on storage quantity over years.

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