Land Cover Classification of Al-Jadriya Region in Baghdad Using Remote Sensing and GIS

Abstract

Due to its commercial and economic significance and its adjacency to Iraq's largest university, the Al-Jadriya area in Baghdad holds vital importance. This region exhibits high population density, diverse land uses, and a wide range of land cover types. Therefore, accurately classifying the land features in this area is crucial to support decision-making and facilitate infrastructure development. This study aims to utilize remote sensing techniques and a high-resolution satellite image to classify the region. To achieve this, GIS and QGIS programs and a software package encompassing various classification methods were employed to accurately classify the features and determine the most practical classification methods for this data type. The results indicated that deep learning algorithms utilizing artificial intelligence were the most effective classification method; it achieved an 81.66% classification accuracy for the region, surpassing other techniques.