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SU Fenzhen,ZHOU Chenhu,ZHANG Tianyu. 2006. Constructing a raster-based spatio-temporal hierarchical data model for marine fisheries application. Acta Oceanologica Sinica, (1):57-63
Constructing a raster-based spatio-temporal hierarchical data model for marine fisheries application
Constructing a raster-based spatio-temporal hierarchical data model for marine fisheries application
Received:August 27, 2005  Revised:November 10, 2005
DOI:
Key words:marine geographical information system  spatio-temporal data model  knowledge discovery  fishery management  data warehouse
中文关键词:  marine geographical information system  spatio-temporal data model  knowledge discovery  fishery management  data warehouse
基金项目:
Author NameAffiliationE-mail
SU Fenzhen Marine GIS Center, State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China sufz@lreis.ac.cn 
ZHOU Chenhu Marine GIS Center, State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China  
ZHANG Tianyu Marine GIS Center, State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China  
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Abstract:
      Marine information has been increasing quickly.The traditional database technologies have disadvantages in manipulating large amounts of marine information which relates to the position in 3-D with the time.Recently,greater emphasis has been placed on GIS (geographical information system)to deal with the marine information.The GIS has shown great success for terrestrial applications in the last decades,but its use in marine fields has been far more restricted.One of the main reasons is that most of the GIS systems or their data models are designed for land applications.They cannot do well with the nature of the marine environment and for the marine information.And this becomes a fundamental challenge to the traditional GIS and its data structure.This work designed a data model,the raster-based spatio-temporal hierarchical data model (RSHDM),for the marine information system,or for the knowledge discovery from spatio-temporal data,which bases itself on the nature of the marine data and overcomes the shortages of the current spatio-temporal models when they are used in the field.As an experiment,the marine fishery data warehouse (FDW) for marine fishery management was set up,which was based on the RSHDM.The experiment proved that the RSHDM can do well with the data and can extract easily the aggregations that the management needs at different levels
中文摘要:
      Marine information has been increasing quickly.The traditional database technologies have disadvantages in manipulating large amounts of marine information which relates to the position in 3-D with the time.Recently,greater emphasis has been placed on GIS (geographical information system)to deal with the marine information.The GIS has shown great success for terrestrial applications in the last decades,but its use in marine fields has been far more restricted.One of the main reasons is that most of the GIS systems or their data models are designed for land applications.They cannot do well with the nature of the marine environment and for the marine information.And this becomes a fundamental challenge to the traditional GIS and its data structure.This work designed a data model,the raster-based spatio-temporal hierarchical data model (RSHDM),for the marine information system,or for the knowledge discovery from spatio-temporal data,which bases itself on the nature of the marine data and overcomes the shortages of the current spatio-temporal models when they are used in the field.As an experiment,the marine fishery data warehouse (FDW) for marine fishery management was set up,which was based on the RSHDM.The experiment proved that the RSHDM can do well with the data and can extract easily the aggregations that the management needs at different levels
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