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Research on Improved Method of Storage and Query of Large- Scale Remote Sensing Images.
- Source :
- Journal of Database Management; Jul-Sep2018, Vol. 29 Issue 3, p1-16, 16p
- Publication Year :
- 2018
-
Abstract
- The traditional method is used to deal with massive remote sensing data stored in low efficiency and poor scalability. This article presents a parallel processing method based on MapReduce and HBase. The filling of remote sensing images by the Hilbert curve makes the MapReduce method construct pyramids in parallel to reduce network communication between nodes. Then, the authors design a massive remote sensing data storage model composed of metadata storage model, index structure and filter column family. Finally, this article uses MapReduce frameworks to realize pyramid construction, storage and query of remote sensing data. The experimental results show that this method can effectively improve the speed of data writing and querying, and has good scalability. [ABSTRACT FROM AUTHOR]
- Subjects :
- REMOTE-sensing images
REMOTE sensing
AERIAL photogrammetry
CLOUD computing
BIG data
Subjects
Details
- Language :
- English
- ISSN :
- 10638016
- Volume :
- 29
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- Journal of Database Management
- Publication Type :
- Academic Journal
- Accession number :
- 133552915
- Full Text :
- https://doi.org/10.4018/JDM.2018070101