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A hierarchical organization approach of multi-dimensional remote sensing data for lightweight Web Map Services

  • Zhao, Yongwang1
  • Hu, Chunyang2
  • Shen, Hualei1
  • Ma, Dianfu1
  • Li, Xuan3
  • Huang, Yonggang1
  • 1 Beihang University, National Laboratory of Software Development Environment, School of Computer Science and Engineering, Haidian District, Beijing, China , Beijing (China)
  • 2 AVIC Aerospace Life-Support Industries, LTD., NO.29, Xinhua Road, Xiangyang, Hubei, China , Xiangyang (China)
  • 3 Communication Satellite Division, Chinese Academy of Space Technology, Haidian District, Beijing, China , Beijing (China)
Published Article
Earth Science Informatics
Publication Date
Mar 01, 2012
DOI: 10.1007/s12145-012-0096-9
Springer Nature


With the rapid development of the World Wide Web, remote sensing (RS) data have become available to a wider range of public/professional users than ever before. Web Map Services (WMSs) provide a simple Web interface for requesting RS data from distributed geospatial databases. RS data providers typically expect to provide lightweight WMSs. They have a low construction cost, and can be easily managed and deployed on standard hardware/software platforms. However, existing systems for WMSs are often heavyweight and inherently hard to manage, due to their improper usage of databases or data storage. That is, they are not suitable for public data services on the Web. In addition, RS data are moving toward the multi-dimensional paradigm, which is characterized by multi-sensor, multi-spectral, multi-temporal and high resolution. Therefore, an efficient organization and storage approach of multi-dimensional RS data is needed for lightweight WMSs, and the efficient WMSs must support multi-dimensional Web browsing. In this paper, we propose a Global Remote Sensing Data Hierarchical Model (GRHM) based on the image pyramid and tiling techniques. GRHM is a logical model that is independent upon physical storage. To support lightweight WMSs, we propose a physical storage structure, and deploy multi-dimensional RS data on Web servers. To further improve the performance of WMSs, a data declustering method based on Hilbert space-filling curve is adopted for the distributed storage. We also provide an Open Geospatial Consortium (OGC) WMS and a Web map system in Web browsers. Experiments conducted on real RS datasets show promising performance of the proposed lightweight WMSs.

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