Where's your hood at? Crowdsourcing Neighbourhoods using Open Source Tools
summary
Built an interactive site wellyhoods.com with Leaflet, Mapbox tiles and a Node.js/Fly backend and collects polygons and focal points; it runs three months and gathers 920 responses of which 886 are usable. Analysis uses Python, geopandas and OSMnx with a 60 m hex grid to map consensus, finds many street and green-space boundaries, focal-point clusters at shops, schools and beaches, and statistical results: longer residency increases polygon area and modal days driving increase area while walking correlates with smaller areas; suburb congruence with official localities is low (congruence 0.18).
AI-written summary · about
chapters (17)
- 0:00Intro
- 0:10Why Care About Neighbourhoods
- 0:58Research Questions
- 2:30Draw Neighborhood Boundaries
- 3:13Crowdsourcing
- 4:40Drawbacks
- 5:13Solutions
- 6:24Website
- 7:07Map
- 7:32Wellington
- 9:06Analysis
- 9:54Levels Consensus
- 10:44Personal Characteristics
- 11:41Motor Transport
- 12:12Neighbourhoods vs Official Boundaries
- 13:12Focal Points
- 14:53Residential polygons
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