The digital Earth Observation Librarian:a data mining approach for large satellite images archives  

作　　者：Mihai Datcu Alexandru-Cosmin Grivei Daniela Espinoza-Molina Corneliu Octavian Dumitru Christoph Reck Vlad Manilici Gottfried Schwarz 

机构地区：[1]German Aerospace Center,Remote Sensing Technology Institute,Wessling,Germany [2]Research Center for Spatial Information,University Politehnica of Bucharest,Bucharest,Romania [3]German Remote Sensing Data Center,German Aerospace Center,Wessling,Germany

出　　处：《Big Earth Data》2020年第3期265-294,共30页地球大数据（英文）

基　　金：The work was supported by EOLib—an ESA technological project ESA EOLib project,2019.

摘　　要：Throughout the years,various Earth Observation(EO)satellites have generated huge amounts of data.The extraction of latent information in the data repositories is not a trivial task.New methodologies and tools,being capable of handling the size,complexity and variety of data,are required.Data scientists require support for the data manipulation,labeling and information extraction processes.This 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 general.The 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 images.EOLib is operated by DLR’s(German Aerospace Center’s)Multi-Mission Payload Ground Segment of its Remote Sensing Data Center at Oberpfaffenhofen,Germany.

关 键 词：Earth observation TERRASAR-X data mining system 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]