Title: An improved distributed storage model of remote sensing images based on the HDFS and pyramid structure

Authors: Linhui Li; Weipeng Jing; Nihong Wang

Addresses: College of Information and Computer Engineering, Northeast Forestry University, Harbin City, 150040, Heilongjiang Province, China ' College of Information and Computer Engineering, Northeast Forestry University, Harbin City, 150040, Heilongjiang Province, China ' College of Information and Computer Engineering, Northeast Forestry University, Harbin City, 150040, Heilongjiang Province, China

Abstract: With the rapidly growing amount of remote sensing data, data management needs to adopt a new architecture. Some improvements have been made in some areas. For example, the Hadoop distributed file system (HDFS) can be utilised for large files. However, small files will be produced when storing remote sensing images in the pyramid-based structure. In this paper, we propose a method based on the Hadoop system with MapFile. The method is an improved storage model for efficient storage and allows for access of the small files on the HDFS. The proposed method combines small files into the MapFile serialised container, and it reduces the number of small files. The metadata sensor information is stored in the index to improve the search speed. Results demonstrate the efficiency of remote sensing image processing using the pyramid model and the reduced execution time compared with the HDFS, HDWebGIS and Hadoop archives.

Keywords: remote sensing image; pyramid structure; MapReduce; MapFile; small files; HDFS; serialised container; index; search speed; Hadoop.

DOI: 10.1504/IJCAT.2019.098037

International Journal of Computer Applications in Technology, 2019 Vol.59 No.2, pp.142 - 151

Received: 11 Apr 2018
Accepted: 04 May 2018
Published online: 27 Feb 2019 *

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