2016
DOI: 10.1080/2150704x.2016.1187317
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Corals & benthic habitat mapping using DubaiSat-2: a spectral-spatial approach applied to Dalma Island, UAE (Arabian Gulf)

Abstract: Satellite 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 diff… Show more

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Cited by 7 publications
(2 citation statements)
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References 23 publications
(24 reference statements)
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“…Embedding spatial information in the modeling of classes is shown to significantly improve a classification's accuracy, especially when dealing with highly heterogeneous classes. In this work, as the first attempt, we employed a segmentation-based approach similar to the method that was successfully utilized to map the coral reef environment in the UAE [17]. The flowchart of the proposed method is shown in Figure 3.…”
Section: Methodsmentioning
confidence: 99%
“…Embedding spatial information in the modeling of classes is shown to significantly improve a classification's accuracy, especially when dealing with highly heterogeneous classes. In this work, as the first attempt, we employed a segmentation-based approach similar to the method that was successfully utilized to map the coral reef environment in the UAE [17]. The flowchart of the proposed method is shown in Figure 3.…”
Section: Methodsmentioning
confidence: 99%
“…Google Earth Engine (GEE) comprises a considerable amount of satellite and global data types 48 worldwide, making it possible to analyze this data for various purposes such as change detection 49 [15] , mapping [16,17] and ground level studies [18]. GEE has been widely used in a number of disciplines including reviewing global forest changes [19], estimating crop production [20], ground subsidence monitoring [21], coral reef mapping [22], modeling global surface water change [23,24], flood risk assessment [25], global urban mapping [26,27], renewable energy mapping [28], drought monitoring [29], and the reconstruction of the MODIS global vegetation index [30].…”
Section: Introductionmentioning
confidence: 99%