Evaluation of Water Column Correction Methods in Mapping Seagrass Bed Using Remote Sensing Data in Khanh Hoa Province, Vietnam

Abstract

The use of remote sensing images for the interpretation of underwater substrate objects depends on their reflectance spectrum of different water depths. Thus, the water column correction step is important in the interpretation. Two commonly used water column correction methods are Lyzenga’s depth invariant index (DII) method and Sagawa’s bottom reflectance index (BRI) method. To evaluate the role of each method in Khanh Hoa waters, Tuan Le water, with a high seagrass coverage and moderate turbidity, and Thuy Trieu Lagoon, with high biodiversity of seagrass species and turbidity water, were selected as representatives. 70% of the survey data was used for ground training data of seagrass (dense and patchy), muddy-sand and sand features and the interpretation of both methods, whereas the remaining 30% of the survey data was used for validation of the mapping results. The maximum likelihood classification approach was used to extract the seagrass map and evaluated by overall accuracy as well as the Kappa coefficient. The processing results show that, in Tuan Le water, using the DII method gives an accuracy of 82.1% and the BRI of 80.1%; and in Thuy Trieu Lagoon, the DII method has an accuracy of 80.67% and the BRI of 80.0%. These results demonstrate that both methods have high accuracy results in both areas, but the method of BRI gives better results.