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ScienceEarth: A Big Data Platform for Remote Sensing Data Processing.

Authors :
Xu, Chen
Du, Xiaoping
Yan, Zhenzhen
Fan, Xiangtao
Source :
Remote Sensing; Feb2020, Vol. 12 Issue 4, p607, 1p
Publication Year :
2020

Abstract

Mass remote sensing data management and processing is currently one of the most important topics. In this study, we introduce ScienceEarth, a cluster-based data processing framework. The aim of ScienceEarth is to store, manage, and process large-scale remote sensing data in a cloud-based cluster-computing environment. The platform consists of the following three main parts: ScienceGeoData, ScienceGeoIndex, and ScienceGeoSpark. ScienceGeoData stores and manages remote sensing data. ScienceGeoIndex is an index and query system, a spatial index based on quad-tree and Hilbert curve which is combined for heterogeneous tiled remote sensing data that makes efficient data retrieval in ScienceGeoData. ScienceGeoSpark is an easy-to-use computing framework in which we use Apache Spark as the analytics engine for big remote sensing data processing. The result of tests proves that ScienceEarth can efficiently store, retrieve, and process remote sensing data. The results reveal ScienceEarth has the potential and capabilities of efficient big remote sensing data processing. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
12
Issue :
4
Database :
Complementary Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
142147996
Full Text :
https://doi.org/10.3390/rs12040607