A Study on the Extraction of Satellite Image Information for Two Types of Coastal Fishery Facility Fish Cages and Rafts Influenced by Clouds and Vessels

Abstract

Research on the extraction of satellite information for the areas of coastal fish cages and rafts is important to quickly grasp the pattern and structure of the coastal fishery aquaculture industry. This study proposes a multi-feature and rule-based object-oriented image classification (MROIC) model, integrating spatial-spectral enhancement techniques with object-based image analysis classification methods. The MROIC model enhances spectral information by constructing ratio bands alongside principal component analysis, subsequently employing rule sets, edge detection algorithms, and comprehensive algorithmic merging techniques. It is applicable to satellite image classification tasks in complex environments, including influence of clouds and vessels. The information of fish cage and raft facilities is extracted via the MROIC model on the southwest coast of Xiapu County, Fujian Province, as an example. The results showed that the MROIC model attained an average total classification accuracy of 90.43% and a Kappa coefficient of 0.80. Extracting the area of fisheries facilities under the influence of clouds and vessels can provide better extraction accuracy and lower omission error. The MROIC model proposed in this study demonstrates high extraction accuracy and strong applicability, offering technical support for government planning in fishery facility areas and aiding in the risk assessment and management efficiency of fishery facility insurance.