The Assessment of More Suitable Image Spatial Resolutions for Offshore Aquaculture Areas Automatic Monitoring Based on Coupled NDWI and Mask R-CNN

Abstract

Wide-scale automatic monitoring based on the Normalized Difference Water Index (NDWI) and Mask Region-based Convolutional Neural Network (Mask R-CNN) with remote sensing images is of great significance for the management of aquaculture areas. However, different spatial resolutions brought different cost and model performance. To find more suitable image spatial resolutions for automatic monitoring offshore aquaculture areas, seven different resolution remote sensing images in the Sandu’ao area of China, from 2 m, 4 m, to 50 m, were compared. Results showed that the remote sensing images with a resolution of 15 m and above can achieve the corresponding recognition effect when no financial issues were considered, with the F1 score of over 0.75. By establishing a cost-effectiveness evaluation formula that comprehensively considers image price and recognition effect, the best image resolution in different scenes can be found, thus providing the most appropriate data scheme for the automatic monitoring of offshore aquaculture areas.

Marine Infrastructure Detection with Satellite Data—A Review

“…Through continuous research and modifications, UNet has established itself as a robust model for the detection of offshore infrastructures [20]. In addition to UNet, various algorithms have been used for image segmentation or object detection, including VGG [33,57,99,100], FCN [32,87,91], DeepLab [60,84,92], and R-CNN-based models [41,42,47,77,108], to name a few. This diversity illustrates the ongoing search for optimal solutions and the adaptation to the specific requirements of offshore detection.…”

“…Raft aquaculture was the most studied (46%) [31,32,37,39,46,50,[55][56][57][58][59][60][61][62][63][64][65][66][67][68][69][70][71][72][73] and 12% of aquaculture studies looked specifically at cages [40,52,[74][75][76][77]. The remaining 42% investigated different types of aquaculture including raft, cage or longline in combination [33][34][35][47][48][49]53,54,[78][79][80][81][82][83][84][85][86][87][88][8...…”

“…The zoomed-in map (Figure 8) of East and Southeast Asia clearly shows that aquaculture is being studied along the entire Chinese coast. The hotspots here are Sansha Bay in Fujian Province (16 studies) [33][34][35]37,47,49,56,65,69,73,76,80,83,85,86,88], the offshore area around Dalian in Liaoning Province (13 studies) [37,39,49,50,53,[57][58][59][60]62,67,68,73], and Haizhou Bay in Jiangsu Province (9 studies) [31,32,55,61,63,66,[71][72][73]. Further site and local studies of aquaculture were carried out on the coast of Japan [59,70,93,106], on the south coast of South Korea [81,82], the south coast of Vietnam [43,…”

Multi-Granularity Modeling Method for Effectiveness Evaluation of Remote Sensing Satellites

“…Remote sensing satellites are a type of satellite that utilizes optical or microwave technology to collect information about the ground or air targets. They have numerous applications in areas such as agriculture, forestry, marine, land management, environmental protection, weather forecasting, and military operations [1][2][3][4][5][6][7][8]. To create a comprehensive remote sensing satellite system, it is crucial to evaluate the effectiveness of these satellites [9,10].…”