Coastal Marine Debris Detection and Density Mapping With Very High Resolution Satellite Imagery
Ken‐ichi Sasaki, Tatsuyuki Sekine, Louis-Jerome Burtz, William J. Emery
Abstract
Marine debris is a serious problem for marine ecosystems and related coastal activities. We carry out a study using <i>in-situ</i> debris clean-up data (collected by a local Japanese company) together with high spatial resolution satellite images to determine how well the satellite images can be used to estimate the amount and type of debris deposited on the beaches of the island in southern Japan. We use machine learning techniques to analyze the satellite images and find that Shannon's entropy computed from World-View 2 and 3 imagery from Maxar Corp. yields a useful detection and mapping of the coastal debris when compared with the <i>in-situ</i> clean-up data. We also assign a debris concentration to each satellite image pixel to visualize the distribution of the debris. The algorithm linking the satellite images to the ground truth clean-up data can now be used in areas where no ground truth data are available.