Abstract: In recent years, there has been an increase in interest in using Geographic Information Systems (GIS) to study soil erosion. Soil erosion is one of the greatest environmental challenges, making it imperative to study its prevention, assessment, and monitoring. Not only is fertile land being lost, but sediments in water are increasing, causing pollution, killing marine life, and obstructing water supply. GIS and remote sensing are thought to be accurate methods for mapping and analyzing land use and cover changes. A framework was developed for this study in order to classify, verify, and detect changes in land cover using multitemporal high resolution images. Using ArcMap software, a change detection model was developed to detect land loss and gain between multitemporal images. To implement the framework, high-resolution aerial images of Port Arthur in Southeast Texas were obtained from the National Agriculture Imagery Program (NAIP). The resolution of these images, taken between 2004 and 2020, ranged from 60 centimeters to 1 meter. The results revealed that the total land loss in the port was more than 770,000 m2 and the total land gain was more than 391,000 m2 over the 16-year period. This framework can be used to quantify and classify the type of change, as well as to assess the accuracy using change detection statistics.
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