Object-oriented approaches to mapping channel habitat on the lower Congo River
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Information about large river channels is required for assessments of ecologically and economically important fish assemblages, but field mapping can be an expensive and time-consuming process. Classification of fluvial fish habitats using remotely sensed images is a potential alternative. This study examines whether widely available satellite images can be used to map habitat on the Lower Congo River in Western Africa using an object-oriented approach. One Landsat 7 image and three ASTER images of the river were classified using object-oriented techniques and the results were compared to existing topographic maps. Although insufficient ground truth data were available for a numerical accuracy assessment, the habitat maps produced from the ASTER images correctly identified all major turbulent areas, islands, and rock formations. This study concludes that an object-oriented approach provides procedural benefits over pixel-based approaches, and that the ability to incorporate spatial context is a major advantage in habitat classification.