The Effect of War on Land Use Dynamics in Mosul Iraq Using Remote Sensing and GIS Techniques

This study aims to assess the impact of war on the natural environment of Mosul, Iraq. To achieve that, remote sensing (RS) data and geographic information system (GIS) techniques were employed to identify and relate surface changes based on data from Landsat satellite images and maps. A couple of satellite imageries of 2003 and 2016 were acquired, processed, and analyzed. To evaluate the consequence of the war in the study area, a comparison was made via studying the prewar and post-war datasets of 2003 and 2016, respectively. Furthermore, the support vector machine learning (SVM), which is a supervised classification method was adopted for the classification of the land use and the rate of change was derived from the Landsat images (2003 and 2016). Also, testing of the classified images by ground control points (GCPs) provided 91.53% and 94.36% overall accuracies for 2003 and 2016 respectively. Findings show that the maximum change occurred in the agriculture area, which had decreased by 18%, followed by an urban area with 7%, which was converted to bare land with 44% in 2016. The increase in bare land is a sign of the consequence of the war on the existing land use and the destruction of the existing agricultural area. The approach highlights the capability of spatial technologies in the study and the evaluation of the impact of war on the land environment in 2003 and 2016.