Abstract
Land cover mapping of marshland areas from satellite images data is not a simple process, due to the similarity of the spectral characteristics of the land cover. This leads to challenges being encountered with some land covers classes, especially in wetlands classes. In this study, satellite images from the Sentinel 2B by ESA (European Space Agency) were used to classify the land cover of Al‑Hawizeh marsh/Iraq‑Iran border. Three classification methods were used aimed at comparing their accuracy, using multispectral satellite images with a spatial resolution of 10 m. The classification process was performed using three different algorithms, namely: Maximum Likelihood Classification (MLC), Artificial Neural Networks (ANN), and Support Vector Machine (SVM). The classification algorithms were carried out using ENVI 5.1 software to detect six land cover classes: deep water marsh, shallow water marsh, marsh vegetation (aquatic vegetation), urban area (built‑up area), agriculture area, and barren soil. The results showed that the MLC method applied to Sentinel 2B images provides a higher overall accuracy and the kappa coefficient compared to the ANN and SVM methods. Overall accuracy values for MLC, ANN, and SVM methods were 85.32%, 70.64%, and 77.01% respectively.
Highlights
Marshlands represent one of the richest areas of biodiversity in Iraq’s ecosys‐ tems [1]
The results showed that the Maximum Likelihood Classification (MLC) method applied to Sentinel 2B imag‐ es provides a higher overall accuracy and the kappa coefficient compared to the Artificial Neural Networks (ANN) and Support Vector Machine (SVM) methods
This study aims to classify the land cover of the Al‐Hawizeh marsh using three classification methods (MLC, ANN, and SVM) to compare the accuracy of classifi‐ cation methods using satellite images from Sentinel 2B
Summary
Marshlands represent one of the richest areas of biodiversity in Iraq’s ecosys‐ tems [1]. The Mesopotamian Marshes (Ahwar of Southern Iraq) is unique in that it is one of the world’s largest inland delta systems in an extremely hot and arid environ‐ ment [2], it plays an important role in global ecosystems by supporting rare wildlife and rich biodiversity, especially of migratory birds [3]. The marshlands included a chain of almost interconnected per‐ manent and seasonal marshes, shallow and deep lake units that merged into larger wetland complexes during high floods; mudflats and desert regularly inundated in periods of elevated water levels; and a great variety of habitats and ecological fea‐ tures [5]. The Al‐Hawizeh marsh is part of the Mesopotamian Marshes that included in the Ramsar list of wetlands of international importance as they regularly harbor considerable numbers of threatened, endemic, and restricted‐ranged bird and mam‐ mal species and they provide a home and livelihoods for many of the indige‐ nous people living there
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
