Refresh Print


Introduction and Objectives

The Earth Observation image Librarian (EOLib) project serves to setup the next-generation of Image Information Mining (IIM) systems, implementing novel techniques for image content exploration. EOLib will exploit information about Earth Observation (EO) product contents which is usually hidden in raster data, image time series and metadata, thus enabling content-based search in very large archives of high resolution EO data. EOLib will be interfaced to and operated in the DLR Multi-Mission Payload Ground Segment (PGS) of the DLR Remote Sensing Data Center, representing at the same time a general new concept for the operations of Ground Segment infrastructures. 

Expected Results

EOLib is an Image Information Mining system for Earth Observation (EO) data. It processes, extracts and accesses the content of EO products. It stores higher-level abstractions of these products as semantic annotations. EOLib offers information mining services on the original corpus of EO products based on the EO content, associated metadata, semantic annotations and information from external GIS sources.
EOLib is integrated with the Payload Ground Segment (PGS) existing at DLR’s premises at Oberpfaffenhofen. EOLib offers data model generation, visual data mining and knowledge discovery in databases (including semantic annotation), queries, and Epitome production functionalities.
EOLib consists of several independent systems that communicate with each other via established interfaces in a service-oriented architecture. Each of these systems may integrate one or several components which provide specific functionality to the system.

Project Schedule

M1Jul 2012DLRSRR
M2Apr 2013DLRPDR
M3Oct 2014DLRCDR
M4Dec 2015DLRAR
M5May 2016DLRFP




EOLib Scenarios
EOLib Architecture Concept
EOLib Feature Extraction Algorithms
EOLib Image Information Mining Algorithms

Contributors to this page: Michele Iapaolo .

Page last modified on Thursday 14 of July 2016 13:29:40 CEST by Michele Iapaolo.