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esy-osmfilter – A Python Library to Efficiently Extract OpenStreetMap Data Cover

esy-osmfilter – A Python Library to Efficiently Extract OpenStreetMap Data

By: Adam Pluta and  Ontje Lünsdorf  
Open Access
|Sep 2020

References

  1. Medjroubi, W, Philipp Müller, U, Scharf, M, Matke, C and Kleinhans, D 2017 Open data in power grid modelling: New approaches towards transparent grid models. Energy Reports, 3: 1421. DOI: 10.1016/j.egyr.2016.12.001
  2. Alhamwi, A, Medjroubi, W, Vogt, T and Agert, C Apr 2017 GIS-based urban energy systems models and tools: Introducing a model for the optimization of flexibilisation technologies in urban areas. Applied Energy, 191: 19. DOI: 10.1016/j.apenergy.2017.01.048
  3. Alhamwi, A, Medjroubi, W, Vogt, T and Agert, C 2017 Openstreetmap data in modelling the urban energy infrastructure: a first assessment and analysis. In Proceedings of the 9th International Conference on Applied Energy, 142: 19681976. Elsevier. DOI: 10.1016/j.egypro.2017.12.397
  4. Arsanjani, J J, Zipf, A, Mooney, P and Helbich, M 2015 An introduction to openstreetmap in geographic information science: Experiences, research, and applications. In OpenStreetMap in GIScience, 115. Springer. DOI: 10.1007/978-3-319-14280-7_1
DOI: https://doi.org/10.5334/jors.317 | Journal eISSN: 2049-9647
Language: English
Submitted on: Jan 27, 2020
Accepted on: Jun 22, 2020
Published on: Sep 1, 2020
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2020 Adam Pluta, Ontje Lünsdorf, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.