---
_id: '750'
abstract:
- lang: eng
  text: Modern communication technologies allow first responders to contact thousands
    of potential volunteers simultaneously for support during a crisis or disaster
    event. However, such volunteer efforts must be well coordinated and monitored,
    in order to offer an effective relief to the professionals. In this paper we extend
    earlier work on optimally assigning volunteers to selected landmark locations.
    In particular, we emphasize the aspect that obtaining good assignments requires
    not only advanced computational tools, but also a realistic measure of distance
    between volunteers and landmarks. Specifically, we propose the use of the Open
    Street Map (OSM) driving distance instead of he previously used flight distance.
    We find the OSM driving distance to be better aligned with the interests of volunteers
    and first responders. Furthermore, we show that relying on the flying distance
    leads to a substantial underestimation of the number of required volunteers, causing
    negative side effects in case of an actual crisis situation.
author:
- first_name: Jasmin
  full_name: Pielorz, Jasmin
  id: 49BC895A-F248-11E8-B48F-1D18A9856A87
  last_name: Pielorz
- first_name: Matthias
  full_name: Prandtstetter, Matthias
  last_name: Prandtstetter
- first_name: Markus
  full_name: Straub, Markus
  last_name: Straub
- first_name: Christoph
  full_name: Lampert, Christoph
  id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
  last_name: Lampert
  orcid: 0000-0001-8622-7887
citation:
  ama: 'Pielorz J, Prandtstetter M, Straub M, Lampert C. Optimal geospatial volunteer
    allocation needs realistic distances. In: <i>2017 IEEE International Conference
    on Big Data</i>. IEEE; 2017:3760-3763. doi:<a href="https://doi.org/10.1109/BigData.2017.8258375">10.1109/BigData.2017.8258375</a>'
  apa: 'Pielorz, J., Prandtstetter, M., Straub, M., &#38; Lampert, C. (2017). Optimal
    geospatial volunteer allocation needs realistic distances. In <i>2017 IEEE International
    Conference on Big Data</i> (pp. 3760–3763). Boston, MA, United States: IEEE. <a
    href="https://doi.org/10.1109/BigData.2017.8258375">https://doi.org/10.1109/BigData.2017.8258375</a>'
  chicago: Pielorz, Jasmin, Matthias Prandtstetter, Markus Straub, and Christoph Lampert.
    “Optimal Geospatial Volunteer Allocation Needs Realistic Distances.” In <i>2017
    IEEE International Conference on Big Data</i>, 3760–63. IEEE, 2017. <a href="https://doi.org/10.1109/BigData.2017.8258375">https://doi.org/10.1109/BigData.2017.8258375</a>.
  ieee: J. Pielorz, M. Prandtstetter, M. Straub, and C. Lampert, “Optimal geospatial
    volunteer allocation needs realistic distances,” in <i>2017 IEEE International
    Conference on Big Data</i>, Boston, MA, United States, 2017, pp. 3760–3763.
  ista: Pielorz J, Prandtstetter M, Straub M, Lampert C. 2017. Optimal geospatial
    volunteer allocation needs realistic distances. 2017 IEEE International Conference
    on Big Data. Big Data, 3760–3763.
  mla: Pielorz, Jasmin, et al. “Optimal Geospatial Volunteer Allocation Needs Realistic
    Distances.” <i>2017 IEEE International Conference on Big Data</i>, IEEE, 2017,
    pp. 3760–63, doi:<a href="https://doi.org/10.1109/BigData.2017.8258375">10.1109/BigData.2017.8258375</a>.
  short: J. Pielorz, M. Prandtstetter, M. Straub, C. Lampert, in:, 2017 IEEE International
    Conference on Big Data, IEEE, 2017, pp. 3760–3763.
conference:
  end_date: 2017-12-14
  location: Boston, MA, United States
  name: Big Data
  start_date: 2017-12-11
date_created: 2018-12-11T11:48:18Z
date_published: 2017-12-01T00:00:00Z
date_updated: 2021-01-12T08:13:55Z
day: '01'
department:
- _id: ChLa
doi: 10.1109/BigData.2017.8258375
language:
- iso: eng
month: '12'
oa_version: None
page: 3760 - 3763
publication: 2017 IEEE International Conference on Big Data
publication_identifier:
  isbn:
  - 978-153862714-3
publication_status: published
publisher: IEEE
publist_id: '6906'
quality_controlled: '1'
scopus_import: 1
status: public
title: Optimal geospatial volunteer allocation needs realistic distances
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2017'
...