Assessment of Desertification Changes in Baghdad Using Remote Sensing and the Minimum Distance Classification Algorithm (2013–2023)
DOI:
https://doi.org/10.70882/d0yzhw05Keywords:
Baghdad, Envi 5.3, Classifier, Minimum Distance Classifier, Remote Sensing, Geographic Information Systems.Abstract
New research was conducted to evaluate and track the development of desertification in Baghdad city during 2013, 2018, and 2023 with the use of remote sensing and a minimum distance classifier. The objective of the research is to provide a complete scientific view of the rate and change of desertification during each period of time, through advanced analysis methods that can help to understand the trend of desertification. The distance classifier was used as the primary classification and analysis tool; therefore, the spatial pattern of desertification was recognized across the studied years. By applying this technique, areas that are highly affected by desertification were identified, and those areas that have seen a decrease or increase in their desertification areas were identified. In addition to evaluating the factors that are responsible for the worsening of desertification (e.g., climate change and human activity), multiple sources of satellite data were utilized to evaluate the temporal trend of desertification changes and to make estimations regarding future projections for changes in desertification.
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