Image Processing Approaches as a Diagnostic Parameter to Determine Pollution by Using Satellite Imagery, Northern Iraq
Keywords:Remote sensing data, image processing, object detection, environment pollution
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.