Abstract

ABSTRACTSatellite remote sensing-based monitoring of coastal habitats, like those in the Arabian Gulf, presents a special challenge due to the attenuation of light through the turbid atmosphere and water, as well as the spectral similarity of many benthic habitats. The present study aims to evaluate the potential of DubaiSat-2 imagery in mapping corals and benthic habitat in the vicinity of Dalma Island, United Arab Emirates (UAE). To do so, this study proposes a spectral-spatial method that uses a combination of different remote sensing techniques in order to discern benthic communities with reference to their spatial distribution. This method involves multi-level segmentation, non-linear feature analysis and ensemble learning methods for the characterization of corals, benthic classes and underlying seabeds. Maximum Likelihood and Random Forest, pixel-based methods, were also used for comparison of classification performances. Comparative data are derived from published marine habitat maps. The spectral-spatial method achieves 96.60% overall accuracy. Maximum Likelihood and Random Forest classification methods are assessed to be 92.59% and 94.52% accurate, respectively. The application of the proposed method and the use of DubaiSat-2 imagery can help in achieving well-designed coastal management plans in the region.

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