OpenStreetMap is a free, editable map of the whole world that is being built by volunteers largely from scratch and released with an open-content license. The OpenStreetMap License allows free (or almost free) access to our map images and all of our underlying map data. The project aims to promote new and interesting uses of this data. See ”Why OpenStreetMap?” for more details about why we want an open-content map and for the answer to the question we hear most frequently: Why not just use Google maps?

References in zbMATH (referenced in 60 articles )

Showing results 1 to 20 of 60.
Sorted by year (citations)

1 2 3 next

  1. Cai, T. Tony; Wei, Hongji: Transfer learning for nonparametric classification: minimax rate and adaptive classifier (2021)
  2. Hugo Ledoux, Filip Biljecki, Balázs Dukai, Kavisha Kumar, Ravi Peters, Jantien Stoter, Tom Commandeur: 3dfier: automatic reconstruction of 3D city models (2021) not zbMATH
  3. Adam Pluta; Ontje Lunsdorf: esy-osmfilter - A Python Library to Efficiently Extract OpenStreetMap Data (2020) not zbMATH
  4. Audrito, Giorgio; Beal, Jacob; Damiani, Ferruccio; Pianini, Danilo; Viroli, Mirko: Field-based coordination with the share operator (2020)
  5. Baum, Moritz; Dibbelt, Julian; Pajor, Thomas; Sauer, Jonas; Wagner, Dorothea; Zündorf, Tobias: Energy-optimal routes for battery electric vehicles (2020)
  6. Plath, Michael; Blanck, Constantin; Fischer, Stefan; Allmaras, Moritz; Pirsing, Andreas; Schenk, Tim; Sohr, Annelie: Water cockpit: dashboards for decision support systems (2020)
  7. Sartori, Carlo S.; Buriol, Luciana S.: A study on the pickup and delivery problem with time windows: matheuristics and new instances (2020)
  8. Stefanie Wiegand: BigX: A geographical dataset visualisation tool (2020) not zbMATH
  9. Trekin, A. N.; Ignatiev, V. Yu.; Yakubovskii, P. Ya.: Deep neural networks for determining the parameters of buildings from single-shot satellite imagery (2020)
  10. Uppala, Medha; Handcock, Mark S.: Modeling wildfire ignition origins in southern California using linear network point processes (2020)
  11. Behrend, Moritz; Meisel, Frank; Fagerholt, Kjetil; Andersson, Henrik: An exact solution method for the capacitated item-sharing and crowdshipping problem (2019)
  12. Bertsimas, Dimitris; Delarue, Arthur; Jaillet, Patrick; Martin, Sébastien: Travel time estimation in the age of big data (2019)
  13. Bertsimas, Dimitris; Ng, Yeesian: Robust and stochastic formulations for ambulance deployment and dispatch (2019)
  14. Krumke, Sven O.; Schmidt, Eva; Streicher, Manuel: Robust multicovers with budgeted uncertainty (2019)
  15. Quach, Anna; Symanzik, Jürgen; Forsgren, Nicole: Soul of the community: an attempt to assess attachment to a community (2019)
  16. Álvarez-Miranda, Eduardo; Luipersbeck, Martin; Sinnl, Markus: Gotta (efficiently) catch them all: Pokémon GO meets orienteering problems (2018)
  17. Berli, Justin; Bunel, Mattia; Ducruet, César: Sea-land interdependence in the global maritime network: the case of Australian port cities (2018)
  18. Gagarin, Andrei; Corcoran, Padraig: Multiple domination models for placement of electric vehicle charging stations in road networks (2018)
  19. Leithner, Magdalena; Fikar, Christian: Simulating fresh food supply chains by integrating product quality (2018)
  20. Lum, Oliver; Golden, Bruce; Wasil, Edward: An open-source desktop application for generating arc-routing benchmark instances (2018)

1 2 3 next