JOURNAL OF YANGTZE RIVER SCIENTIFIC RESEARCH INSTI ›› 2014, Vol. 31 ›› Issue (12): 107-112.DOI: 10.3969/j.issn.1001-5485.2014.12.022

• INFORMATION TECHNOLOGY APPLICATION • Previous Articles     Next Articles

A Scalable Structure for the Storage of High-resolution Remote
Sensing Images in Cloud Computing Environment

SHEN Sheng-yu1,LIU Zhe2,ZHANG Ping-cang1,ZHANG Tong3,WU Hua-yi3,CHEN Xiao-ping1   

  1. 1.Department of Soil and Water Conservation, Yangtze River Scientific Research Institute, Wuhan430010, China;
    2.Network and Information Center, Changjiang Water Resources Commission, Wuhan430010, China;
    3.State Key Laboratory of Information Engineering in Surveying, Mapping andRemote Sensing, Wuhan University, Wuhan 430079, China)
  • Received:2013-11-26 Revised:2014-12-05 Online:2014-12-01 Published:2014-12-05

Abstract: Traditional methods of processing remote sensing images could not effectively handle the mass daily production, mass pixel of single image, as well as the mass type and amount of objects. To solve the problem of image storage, we propose a structure for the storage of high-resolution remote sensing images in cloud computing environment, and expound the construction method based on MapReduce framework. We conducted experiments on large files of small image set in a Hadoop cluster and compared the image reading efficiency with that of traditional methods. The results proved that this storage structure has high scalability. Experiments also demonstrate this construction method has efficient reading/writing and processing ability.

Key words: cloud computing, high-resolution remote sensing image, storage structure, MapReduce, large files of small image sets, Hadoop

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