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基于近实时海洋遥感数据的渔场预报系统设计与实现
引用本文:雷林,高峰,官文江,陈新军.基于近实时海洋遥感数据的渔场预报系统设计与实现[J].上海海洋大学学报,2019,28(3):464-470.
作者姓名:雷林  高峰  官文江  陈新军
作者单位:上海海洋大学 海洋科学学院, 上海 201306;农业农村部大洋渔业开发重点实验室, 上海 201306;国家远洋渔业工程技术研究中心, 上海 201306;大洋渔业资源可持续开发教育部重点实验室, 上海 201306;农业农村部大洋渔业资源环境科学观测实验站, 上海 201306,上海海洋大学 海洋科学学院, 上海 201306;农业农村部大洋渔业开发重点实验室, 上海 201306;国家远洋渔业工程技术研究中心, 上海 201306;大洋渔业资源可持续开发教育部重点实验室, 上海 201306;农业农村部大洋渔业资源环境科学观测实验站, 上海 201306,上海海洋大学 海洋科学学院, 上海 201306;农业农村部大洋渔业开发重点实验室, 上海 201306;国家远洋渔业工程技术研究中心, 上海 201306;大洋渔业资源可持续开发教育部重点实验室, 上海 201306;农业农村部大洋渔业资源环境科学观测实验站, 上海 201306,上海海洋大学 海洋科学学院, 上海 201306;农业农村部大洋渔业开发重点实验室, 上海 201306;国家远洋渔业工程技术研究中心, 上海 201306;大洋渔业资源可持续开发教育部重点实验室, 上海 201306;农业农村部大洋渔业资源环境科学观测实验站, 上海 201306
基金项目:卫星海洋遥感业务化应用项目(201801004);国家海洋局公益性项目(201505014)
摘    要:针对国内渔业企业对于渔场预报系统的需要,设计和开发基于近实时海洋遥感数据的渔场预报系统。系统分为陆地数据服务和渔情预报软件两个模块,其中:陆地服务模块负责收集全球近实时海洋环境数据,并提供环境数据下载服务;渔情预报软件可以从陆地服务器下载海洋环境数据,并通过这些数据,使用栖息地适应性指数模型进行渔场预报,为渔业企业和作业渔船的捕捞决策提供辅助。两个模块之间以国际海事卫星船队宽带系统作为数据传输手段。前期的远洋渔船应用试验表明,该系统能稳定下载海洋环境数据并实现渔场预报,预报结果作为捕捞决策的重要辅助信息,可为渔业生产者选择作业地点提供很好的参考。

关 键 词:海洋遥感  渔场预报  栖息地适应性指数模型
收稿时间:2018/3/13 0:00:00
修稿时间:2018/8/7 0:00:00

Design and implementation of fishing ground forecasting system based on near real-time remote sensing data
LEI Lin,GAO Feng,GUAN Wenjiang and CHEN Xinjun.Design and implementation of fishing ground forecasting system based on near real-time remote sensing data[J].Journal of Shanghai Ocean University,2019,28(3):464-470.
Authors:LEI Lin  GAO Feng  GUAN Wenjiang and CHEN Xinjun
Institution:College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China;Key Laboratory of Oceanic Fisheries Exploration, Ministry of Agriculture and Rural Affairs, Shanghai 201306, China;National Engineering Research Center for Oceanic Fisheries, Shanghai 201306, China;Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai 201306, China;Scientific Observing and Experimental Station of Oceanic Fishery Resources, Ministry of Agriculture and Rural Affairs, Shanghai 201306, China,College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China;Key Laboratory of Oceanic Fisheries Exploration, Ministry of Agriculture and Rural Affairs, Shanghai 201306, China;National Engineering Research Center for Oceanic Fisheries, Shanghai 201306, China;Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai 201306, China;Scientific Observing and Experimental Station of Oceanic Fishery Resources, Ministry of Agriculture and Rural Affairs, Shanghai 201306, China,College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China;Key Laboratory of Oceanic Fisheries Exploration, Ministry of Agriculture and Rural Affairs, Shanghai 201306, China;National Engineering Research Center for Oceanic Fisheries, Shanghai 201306, China;Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai 201306, China;Scientific Observing and Experimental Station of Oceanic Fishery Resources, Ministry of Agriculture and Rural Affairs, Shanghai 201306, China and College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China;Key Laboratory of Oceanic Fisheries Exploration, Ministry of Agriculture and Rural Affairs, Shanghai 201306, China;National Engineering Research Center for Oceanic Fisheries, Shanghai 201306, China;Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai 201306, China;Scientific Observing and Experimental Station of Oceanic Fishery Resources, Ministry of Agriculture and Rural Affairs, Shanghai 201306, China
Abstract:To fulfill the needs of fishing ground forecasting system of domestic fishery companies, a fishing ground forecasting system is developed based on near real-time remote sensing data. The system has two modules, the land data service module and the fishing ground forecasting software module. The land service module is responsible for collecting the global near real-time marine environment data and providing the environmental data downloading service. The fishing ground forecasting software module can download the marine environment data from the land server and use the data to forecast the fishing ground using the habitat suitability index model. The system uses the International Maritime Satellite broadband services as data transmission channel. Former application tests of deep-sea fishing vessels indicated that the system can download the environmental data stably and calculate the potential fishing ground, which is important auxiliary information for fishing decision and can be used as a reference for fishing location selection.
Keywords:ocean remote sensing  fishing ground forecasting  Habitat Suitability Index(HSI) model
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