Operational Data Store of Multi-Platform, Multi-Source, Multi-Scale, Multi-Temporal Data Sets

With the development of geographic information technologies, large amount of data collected from satellite, airborne, and ground based imaging systems. Large amount of structured data and unstructured data come to TB level. Data organization, management and application became a geographic informatio...

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Bibliographic Details
Main Authors: Weiwei Song, Yuanmin Fang, Jie Chen, Yongming Yang
Format: Conference Proceeding
Language:English
Subjects:
Complexity theory
Data mining
Data models
Memory
Object oriented modeling
Shape
Spatial databases
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Summary:With the development of geographic information technologies, large amount of data collected from satellite, airborne, and ground based imaging systems. Large amount of structured data and unstructured data come to TB level. Data organization, management and application became a geographic information bottleneck. In this paper, Operational Data Storage (ODS) of multi-platform, multi-source, multi-scale, multi-temporal image and data manipulation are studied. Through integrated planning, design massive GIS data storage structure, management tools and mechanisms for application service. Thinking of the data integration, data storage layer, data processing and data mart applications in terms of massive data, get the effective integration of multi-platform data, multi-source data, multiscale data, multi-temporal data, to provide efficient, accurate information services for application of geographic information. Studying spatial data conversion, data storage model, model of data services, designing Extract, Transformation and Loading (ETL) process for spatial data, a framework for spatial data ODS design be proposed, provide a base for further data mining and knowledge discovery in spatial data base available.
DOI:10.1109/ISIDF.2011.6024268