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Using Remote Sensing Data For Yellowfin Tuna Fishing Ground Forecasting in Vietnamese Offshore Areas

机译:越南海上地区利用遥感数据对黄鳍金枪鱼渔场预报

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The general study of relationship among environment - biosphere - human has become a good trend in order to predict the change of natural resources during a few last decades. In case, some of the factors can be impacted to the school of fish which can be oceanographical and biological conditions. A basic recruitment factor is used to access to describe biomass needing to consider relationship environmental conditions related to the first state of growth of individual of school offish. The aim of this paper is to analyze temperature data from remote sensing data storing and managing on the Themis Viewer software which is set up into MOVIMAR project, located at the Research Institute For Marine Fisheries (RIMF) for yellow tuna fish forecasting monthly. The Themis Viewer software allows users exploring sea surface temperature (SST) data from different sources including AVHRR on NOAA-19, MODIS on AQUA and TERRA, SEVIRI on MGS and on GEOS, The spatial resolution of data is 0.04 degree and 0.02 degree in medium and high resolution respectively. Structure of data contains mainly information such as time, position and SST. Fisheries data collection has been carried out on board of longline gear in the different programs including survey, observer and logbook throughout projects since 2000. The data are stored at the RIMF, yellowfin tuna data has generated from these data. The parameters as catch per unit effort (CPUE) and temperature structure have been used to make yellowfin tuna fishing ground forecasting monthly based upon the multivariate regression equations, its unit is kg per 100 hooks. Therefore, the results have shown on the mapping forecasting pointing out levels of CPUE indexes monthly. Temperature is directly related to the abundant habitat of schools of fish in the tropical sea area like Vietnamese seawater, the levels of CPUE index per 0.5 square nautical mile on the monthly mapping forecasting of yellow tuna fishing ground in the Vietnamese offshore areas based upon the relationship of temperature to yellowfin tuna.
机译:环境 - 生物圈 - 人类关系的一般性研究变得良好的趋势,以预测过去几十年的自然资源变化。如果某些因素可能会影响到可以是海洋和生物条件的鱼类。基本的招聘因素用于访问需要考虑与学校特性的个人增长状态相关的关系环境条件的生物质。本文的目的是分析来自遥感数据存储和管理的温度数据,该数据在Modimar项目中设立,该项目位于MoviMar项目,位于Movimar项目,位于MoviMar项目,该项目是黄金金枪鱼预测每月的黄金金枪鱼预报研究所。 Themis Viewer软件允许用户探索来自NOAA-19上的不同来源的海面温度(SST)数据,MGRR在Aqua和Terra上的Modis和MGS和Geos上的Seviri,数据的空间分辨率为0.04度和0.02度和高分辨率分别。数据结构主要包含时间,位置和SST等信息。渔业数据收集已在不同节目中的延绳度齿轮船上进行,包括自2000年以来的项目中的调查,观察者和日志。数据存储在RIMF,Yellowfin Tuna数据已从这些数据中生成。根据多元回归方程,使用每单位努力(CPUE)和温度结构的参数用于使黄鳍金枪鱼捕鱼地面预测预测每100个钩子为kg。因此,结果显示了在每月指向CPUE指标水平的映射预测上。温度与越南海水中的热带海域中的鱼类丰富的鱼类栖息地直接关系,每0.5平方海里的CPE指数水平在越南海上地区黄金金枪鱼捕捞地区的每月测绘预测温度向黄鳍金枪鱼。

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