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DOI: 10.14569/IJACSA.2020.0111289
PDF

A Big Data Framework for Satellite Images Processing using Apache Hadoop and RasterFrames: A Case Study of Surface Water Extraction in Phu Tho, Viet Nam

Author 1: Dung Nguyen
Author 2: Hong Anh Le

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 12, 2020.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Earth data, collected from many sources such as remote sensing imagery, social media, and sensors, are growing tremendously. Among them, satellite imagery which play an important roles for monitoring environment and natural changes are increased exponentially in term of both volume and speed. This paper introduces an approach to managing and analyzing such data sources based on Apache Hadoop and RasterFrames. First, it presents the architecture and the general flow of the proposed distributed framework. Based on this, we can imple-ment and perform efficient computations on a big data in parallel without moving data to the center computer which might lead to network congestion. Finally, the paper presents a case study that analyzes the water surface of a Vietnam region using the proposed platform.

Keywords: Satellite imagery; big data; water surface; Apache Hadoop; RasterFrames

Dung Nguyen and Hong Anh Le, “A Big Data Framework for Satellite Images Processing using Apache Hadoop and RasterFrames: A Case Study of Surface Water Extraction in Phu Tho, Viet Nam” International Journal of Advanced Computer Science and Applications(IJACSA), 11(12), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0111289

@article{Nguyen2020,
title = {A Big Data Framework for Satellite Images Processing using Apache Hadoop and RasterFrames: A Case Study of Surface Water Extraction in Phu Tho, Viet Nam},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0111289},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0111289},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {12},
author = {Dung Nguyen and Hong Anh Le}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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