Surface Changes of Al-Hammar Marsh using Remote Sensing and Geographic Information Systems
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Abstract
The study examines temporal variation in water levels by calculating the surface area of the Al-Hammar Marsh in southern Iraq over 11 years (2013–2023), because of the consistent Landsat-8 and Landsat-9 data. Because it represents years of remarkable hydrological diversity in Iraq, it provides a trusted assessment for the surface changes of Al-Hammar marsh by using geographic information systems and remote sensing. The change in the surface was determined by utilizing supervised classification (maximum likelihood) to classify the region. Water and vegetation were the two land cover classes that we determined using ArcMap software. Then the thematic maps were created by the same software. The resulting signalize that the surface area changed a lot over the study years, where the large area was recorded in 2019 (1144 km2), and the small area was recorded in 2023 (295 km2). The accuracy assessment showed the supervised classification provided high trust, with overall accuracy ranging between 87 % to 98% and a kappa coefficient ranging between 0.88 and 0.98, which indicated strong agreement.
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