Coastal Aquaculture mapping using a novel combination model of GF-3 Fully Polarimetric SAR Imagery: A case study of Yancheng coastal wetland, China

Coastal aquaculture has become one of the main sources of animal protein and plays an important role in food and nutrition supplies and security around the world. Accurately mapping aquaculture areas is the basis for its sustainable management and use, and provides important support to policy development and implementation at regional, national, and global levels. Considering the concentrated and densely distributed characteristics of aquacultures, it is difficult to distinguish the dikes between aquacultures and identify small-scale aquacultures using medium-and low-resolution SAR images. GaoFen-3 (GF-3) is the first launched full-polarimetric C-band SAR satellite of China at metre-level resolution. This study aims to use a novel combination model to extract coastal aquacultures in the Yancheng coastal wetland, China on the basis of GF-3 Fully Polarimetric SAR Imagery. Polarimetric decomposition algorithms were applied to extract polarimetric scattering features and feature optimization was applied based on the separability index. To separate adjacent and even adhering ponds into individual aquaculture objects, we proposed a novel model that integrated two UNet++ subnetworks with the marker-controlled watershed (MCW) segmentation strategy to obtain more refined coastal aquaculture results. The accuracy assessment results demonstrated a considerable performance, with F1 greater than 95%, IoU greater than 90%, and insF1 higher than 85%. The experimental results indicate that the proposed algorithm achieved fairly high accuracy in aquaculture extraction and can effectively improve the boundary quality of individual aquacultures.