ScienceEarth: A Big Data Platform for Remote Sensing Data Processing
ScienceEarth: A Big Data Platform for Remote Sensing Data Processing
复制标题
科学地球：遥感数据处理大数据平台
DOI：
10.3390/rs12040607
复制
发表时间：
2020-02-01
期刊：
影响因子：
5
通讯作者：
Fan, Xiangtao
中科院分区：
文献类型：
--
作者：
Xu, Chen;Du, Xiaoping;Fan, Xiangtao
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.
