Combining Landsat images with historic records to estimate the live coral cover of Luhuitou fringing reef in Northern South China Sea |
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Affiliation: | 1. Guangxi Laboratory on the Study of Coral Reefs in the South China Sea, Guangxi University, Nanning 530004, China;2. Coral Reef Research Center of China, Guangxi University, Nanning 530004, China;3. School of Marine Sciences, Guangxi University, Nanning 530004, China;4. Laboratory for Marine Geology, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266061, China |
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Abstract: | As an efficient indicator of coral reef health, live coral cover (LCC) is regularly surveyed and recorded by many coral reef documents. However, there usually exist some blanks for the historic records, while current in-field surveys are impossible to fill the blanks. To overcome such difficulties, we focus on exploiting the potential of optical satellite images. The purpose is to fill the blanks of the records over the past and further estimate the LCC in future. As historic records were usually lack of accurate geographical locations to match to the satellite images, a spectral index was defined based on the mean of the subsurface remote sensing reflectance. The index was then used to link the LCC with the satellite images by a cubic polynomial function. Thereafter, the LCC and the coefficients of the polynomial function were finally estimated by simultaneously combining the mean subsurface remote sensing reflectance, the historic LCC records, and the constraints among LCC in adjacent years. Experiments on a series of Landsat images of Luhuitou fringing reef (1973 to 2018) demonstrated that the proposed method is effective and feasible, where the introduction of the satellite images can greatly improve the accuracy. The Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Relative Errors (MRE) of the LCC were able to reach 5.4%, 4.0%, and 15.9% respectively. This is regarded as the first test on LCC estimation by combining such a long-term LCC records with a series of satellite images. |
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