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- W4387363628 abstract "Coastal ecosystems are facing heightened risks due to human-induced climate change, including rising water levels and intensified storm events. Accurate bathymetry data is crucial for assessing the impacts of these threats. However, traditional data collection methods can be cost-prohibitive. This study investigates the feasibility of using freely accessible Landsat and Sentinel satellite imagery to estimate bathymetry and its correlation with hydrographic chart soundings in Port Klang, Malaysia. Through analysis of the blue and green spectral bands from the Landsat 8 and Sentinel 2 datasets, a bathymetry map of Port Klang's seabed is generated. The precision of this derived bathymetry is evaluated using statistical metrics like Root Mean Square Error (RMSE) and the coefficient of determination. The results reveal a strong statistical connection (R2 = 0.9411) and correlation (R2 = 0.7958) between bathymetry data derived from hydrographic chart soundings and satellite imagery. This research not only advances our understanding of employing Landsat imagery for bathymetry assessment but also underscores the significance of such assessments in the context of climate change's impact on coastal ecosystems. The primary goal of this research is to contribute to the comprehension of Landsat imagery's utility in bathymetry evaluation, with the potential to enhance safety protocols in seaport terminals and provide valuable insights for decision-making concerning the management of coastal ecosystems amidst climate-related challenges. The findings of this research have practical implications for a wide range of stakeholders involved in coastal management, environmental protection, climate adaptation and disaster preparedness." @default.
- W4387363628 created "2023-10-06" @default.
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- W4387363628 date "2023-10-01" @default.
- W4387363628 modified "2023-10-09" @default.
- W4387363628 title "Assessing coastal bathymetry and climate change impacts on coastal ecosystems using Landsat 8 and Sentinel-2 satellite imagery" @default.
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- W4387363628 doi "https://doi.org/10.1016/j.envres.2023.117314" @default.
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