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High-Throughput Processing of Space Debris Data

Schreiber, Andreas (2015) High-Throughput Processing of Space Debris Data. PyData Seattle 2015, 24.-26. Jul 2015, Seattle, USA.

Full text not available from this repository.

Official URL: http://seattle.pydata.org/schedule/presentation/35/

Abstract

Space Debris are defunct objects in space, including old space vehicles (such as satellites or rocket stages) or fragments from collisions. Space debris can cause great damage to functional space ships and satellites. Thus detection of space debris and prediction of their orbital paths are essential for today's operation of space missions. The talk shows the Python based infrastructures BACARDI for gathering and storing space debris data from sensors and Skynet for high-throughput data processing and orbital collision detection.

Item URL in elib:https://elib.dlr.de/100059/
Document Type:Conference or Workshop Item (Speech)
Title:High-Throughput Processing of Space Debris Data
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Schreiber, AndreasUNSPECIFIEDUNSPECIFIED
Date:July 2015
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:Python, Big Data, Data Analytics, Provenance, Space Debris
Event Title:PyData Seattle 2015
Event Location:Seattle, USA
Event Type:international Conference
Event Dates:24.-26. Jul 2015
Organizer:NumFOCUS
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Technik für Raumfahrtsysteme
DLR - Research theme (Project):R - Space Debris / Set up DLR-Catalog Space Debris (old)
Location: Köln-Porz
Institutes and Institutions:Institut of Simulation and Software Technology > Distributed Systems and Component Software
Deposited By: Schreiber, Andreas
Deposited On:22 Dec 2015 11:23
Last Modified:10 May 2016 23:36

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