A method, device and equipment for monitoring changes in sea time and space for aquaculture and a storage medium
By super-resolution reconstruction of marine boundary data and analysis of NetCDF data, combined with the centroid method and geographic weighted regression model, the problem of high frequency and high efficiency in monitoring the spatiotemporal changes of marine aquaculture facilities was solved, realizing high-frequency and economical monitoring of marine aquaculture use.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- GUANGZHOU MARINE GEOLOGICAL SURVEY SANYA SOUTH CHINA SEA INST OF GEOLOGY
- Filing Date
- 2026-06-09
- Publication Date
- 2026-07-07
AI Technical Summary
Existing technologies are insufficient for high-frequency, cost-effective monitoring of the spatiotemporal changes of marine aquaculture facilities, especially in deep-water, offshore areas. Traditional remote sensing image monitoring is not timely enough, manual visual interpretation is time-consuming and labor-intensive, and artificial intelligence technology lacks in-depth research on marine hydrological data in the monitoring of marine patches used for aquaculture, leading to frequent identification errors and omissions.
Through super-resolution reconstruction based on target sea area boundary data, the centroid method is used to calculate the centroid point and convex boundary geometry of aquaculture facilities. Combined with NetCDF ocean current multidimensional data technology, the NetCDF ocean current multidimensional data is analyzed, and NetCDF wind field multidimensional data is analyzed to generate wind speed value vector field raster. Combined with a geographic weighted regression model, the spatiotemporal changes of aquaculture facilities are monitored.
It has enabled high-frequency and accurate monitoring of the spatiotemporal changes of marine areas used for aquaculture, improving monitoring efficiency and accuracy, reducing manpower and costs, and meeting the high timeliness requirements of routine monitoring.
Smart Images

Figure CN122345384A_ABST