The digital Earth Observation Librarian:a data mining approach for large satellite images archives
作者机构：German Aerospace CenterRemote Sensing Technology InstituteWesslingGermany Research Center for Spatial InformationUniversity Politehnica of BucharestBucharestRomania German Remote Sensing Data CenterGerman Aerospace CenterWesslingGermany
出 版 物：《Big Earth Data》 (地球大数据（英文）)
年 卷 期：2020年第4卷第3期
页 面：265-294页
核心收录：
学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0709[理学-地质学] 0708[理学-地球物理学] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：The work was supported by EOLib—an ESA technological project ESA EOLib project 2019
主 题：Earth observation TerraSAR-X data mining system
摘 要：Throughout the years,various Earth Observation(EO)satellites have generated huge amounts of *** extraction of latent information in the data repositories is not a trivial *** methodologies and tools,being capable of handling the size,complexity and variety of data,are *** scientists require support for the data manipulation,labeling and information extraction *** paper presents our Earth Observation Image Librarian(EOLib),a modular software framework which offers innovative image data mining capabilities for TerraSAR-X and EO image data,in *** main goal of EOLib is to reduce the time needed to bring information to end-users from Payload Ground Segments(PGS).EOLib is composed of several modules which offer functionalities such as data ingestion,feature extraction from SAR(Synthetic Aperture Radar)data,meta-data extraction,semantic definition of the image content through machine learning and data mining methods,advanced querying of the image archives based on content,meta-data and semantic categories,as well as 3-D visualization of the processed *** is operated by DLR’s(German Aerospace Center’s)Multi-Mission Payload Ground Segment of its Remote Sensing Data Center at Oberpfaffenhofen,Germany.
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