Coastal Marine Debris Density Mapping using a Segmentation Analysis of High-Resolution Satellite Imagery

Abstract

Coastal marine debris poses a serious threat to marine life and impacts fisheries and coastal tourism. This study describes a method that uses high-resolution satellite imagery to locate marine debris in a coastal area. We use the combination of in situ data from local coastal debris cleanup efforts together with nearly coincident high-resolution satellite imagery analyzed using a segmentation-based approach to isolate debris from other materials. We applied Shannon's entropy method, which represents the uncertainties of the segmentation results to obtain spectral signatures for individual semantic features. Then, we demonstrated the robustness of these features by designing a simple classification model to estimate the density of marine debris directly from a satellite image.