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UID:pretalx-foss4g-2022-HB7QW8@talks.staging.osgeo.org
DTSTART;TZID=CET:20220825T175500
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DESCRIPTION:Publicly available data tends to be spatially aggregated to adm
 inistrative units\, limiting the feasibility of nuanced analyses that refl
 ect the natural state of communities and provide actionable insights for a
  wide range of stakeholders. While higher resolution data is generally ava
 ilable within government agencies\, access for external researchers is lim
 ited due to well-established privacy concerns. Inspired by our own use cas
 e of developing a regional quality of life metric for neighborhoods in Den
 mark\, our team at Aalborg University’s Department of the Built Environm
 ent\, in collaboration with data.org’s Growth and Recovery Challenge\, a
 nd Data Clinic\, set out to develop and open source not only foundational 
 granular spatial units and data that adhere to privacy laws\, but also the
  accompanying methodology that has the potential for broad applicability i
 n other countries. \n \nIn this presentation\, we will demonstrate the met
 hodology’s generalizability\, particularly across common European land u
 se and geographical features\, and show how the resulting high-resolution 
 shape files and community data can become crucial tools for government dec
 ision-makers\, community organizations\, and researchers in their efforts 
 to increase transparency and engage in practical\, actionable research.\n 
 \nFocused initially on our Denmark use case\, we algorithmically create sp
 atial units with minimum household and population counts from country-wide
  hectare cell level data. Our approach uses data on road networks and admi
 nistrative boundaries to create socially meaningful component polygons. Th
 is is achieved by developing tools based on already existing open source p
 ackages available in R and Python. The hectare cells are then mapped onto 
 the polygons and clustered using the max-p regionalization algorithm with 
 constraints on the minimum population and household counts to arrive at th
 e final set of spatial units. \n \nTo improve the accessibility of this da
 ta to not just researchers but also administrative decision-makers\, commu
 nity organizations\, and the general public\, we are developing an online 
 tool to explore and visualize indicators within the resulting fine-grained
  regions such as disposable income\, educational level\, housing prices\, 
 migration rates\, distances to public institutions\, and labor market atta
 chments in Denmark. Regional inequality in Denmark has increased over time
 \, and with the help of this tool\, we hope to provide the ability to stud
 y these key metrics both within and across municipal regions. In the devel
 opment of the tool\, we prioritize user feedback and common use cases to e
 nsure both applicability and longevity.\n \nThis project has been develope
 d with an open-source mindset by: 1) creating flexible open data resources
  that can adapt to a wide range of public use cases 2) open sourcing the m
 ethodology for use in other countries/regions and 3) enabling the use of e
 xisting open data and tools such as Open Street Maps\, R and Python in the
  pipeline.\n \nWe firmly believe that the project has the potential to imp
 rove knowledge sharing and collaboration between GIS experts\, decision-ma
 kers\, researchers and the general public not only in Denmark\, but also i
 n Europe and beyond.
DTSTAMP:20260404T021358Z
LOCATION:Room 4
SUMMARY:Not too big\, not too small: open source geospatial units that are 
 just right - Sixten Maximillian Thestrup\, Elise Stenholt Sørensen\, Erin
  Stein
URL:https://talks.staging.osgeo.org/foss4g-2022/talk/HB7QW8/
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