Mapping the Future: The Intersection of Geospatial, Open Source, and Open Data
summary
New Zealand’s open-data push delivers concrete outputs: rapid post-Cyclone Gabriel response uses Sentinel SAR and tasked satellite imagery plus targeted LiDAR to map floods and erosion; flood extents are extracted from 10 m imagery. The open-source hazard engine RiskScape (GPL) models rockfall and coastal flood risk for Queenstown and Auckland. Landonline is rebuilt with OpenLayers + GeoServer to ingest sale prices and streamline notices of change. Persistent gaps: no authoritative national roads layer or single property source of truth.
AI-written summary · about
chapters (10)
- 0:00Introduction and passion
- 4:15Open data as the secret source
- 7:26Government role and barriers
- 11:45Case studies and challenges
- 19:27RISCAPE and natural hazard modeling
- 23:25Building assessments after disasters
- 26:57Iwi leaders and climate platforms
- 29:10Modernizing property systems
- 34:56Future vision for centralized platforms
- 40:13Q&A and closing remarks
related talks
18mThe future of open data
12mOpen Data and the Future of ...
40mHow do you harness crowd sourcing for a community that also delivers for business?
01h 41mOpenStreetWhat? Mapping The World With Open Data
13mDemocratising Open (Geo)Data for Open Innovation and Solutioning
24mWhy LINZ uses open source software
23mFOSS4G Pasifika Roadmap: Then/Now/Beyond
22mMap-based tools for Māori communities