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esy-osmfilter A Python Library to Efficiently Extract OpenStreetMap Data

Pluta, Adam and Lündsdorf, Ontje (2020) esy-osmfilter A Python Library to Efficiently Extract OpenStreetMap Data. Journal of Open Research Software, 8 (19). Ubiquity Press. DOI: 10.5334/jors.317 ISSN 2049-9647

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Official URL: http://dx.doi.org/10.5334/jors.317

Abstract

OpenStreetMap is the largest freely accessible geographic database of the world. The necessary processing steps to extract information from this database, namely reading, converting and filtering, can be very consuming in terms of computational time and disk space. esy-osmfilter is a Python library designed to read and filter OpenStreetMap data under optimization of disc space and computational time. It uses parallelized prefiltering for the OSM pbf-files data in order to quickly reduce the original data size. It can store the prefiltered data to the hard drive. In the main filtering process, these prefiltered data can be reused repeatedly to identify different items with the help of more specialized main filters. At the end, the output can be exported to the GeoJSON format. Funding statement: This work was funded as part of DLR Institute for Networked Energy Systems project SciGRID_gas by the German Federal Ministry for Economic Affairs and Energy (BMWi) within the funding of the 6. Energieforschungsprogramm der Bundesregierung. Funding Code: 03ET4063.

Item URL in elib:https://elib.dlr.de/135931/
Document Type:Article
Title:esy-osmfilter A Python Library to Efficiently Extract OpenStreetMap Data
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Pluta, AdamAdam.Pluta (at) dlr.dehttps://orcid.org/0000-0002-3423-3246
Lündsdorf, OntjeOntje.Luensdorf (at) dlr.deUNSPECIFIED
Date:1 September 2020
Journal or Publication Title:Journal of Open Research Software
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:No
Volume:8
DOI :10.5334/jors.317
Editors:
EditorsEmailEditor's ORCID iD
Hong, Neil ChueN.ChueHong@software.ac.ukUNSPECIFIED
Publisher:Ubiquity Press
ISSN:2049-9647
Status:Published
Keywords:OSM, OpenStreetMap, Python, GeoJSON, PBF, Protocol buffers, GeoJSON, geo
HGF - Research field:Energy
HGF - Program:Technology, Innovation and Society
HGF - Program Themes:Renewable Energy and Material Resources for Sustainable Futures - Integrating at Different Scales
DLR - Research area:Energy
DLR - Program:E SY - Energy Systems Analysis
DLR - Research theme (Project):E - Systems Analysis and Technology Assessment
Location: Oldenburg
Institutes and Institutions:Institute of Networked Energy Systems > Energy Systems Analysis
Deposited By: Pluta, Adam
Deposited On:01 Oct 2020 09:11
Last Modified:01 Oct 2020 09:11

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