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Ramya Raghupathy, Mapbox, Basemap Completeness in Asian Cities | SotM Asia 2017
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State of the Map Asia (SotM-Asia) is the annual regional conference of OpenStreetMap (OSM) organized by OSM communities in Asia. First SotM-Asia was organized in Jakarta, Indonesia in 2015, and the second was organized in Manila, Philippines in 2016. This year’s conference, third in the series, was organized in Kathmandu, Nepal on September 23 – 24, 2017 at Park Village Resort, Budhanilkantha, Kathmandu, Nepal. We brought nearly 200 Open Mapping enthusiasts from Asia and beyond to this year’s SotM-Asia. The event provided an opportunity to share knowledge and experience among mappers; expand their network; and generate ideas to expand map coverage and effective use of OSM data in Asian continent. We chose ‘from creation to use of OSM data’ as the theme of this year’s conference, emphasizing on the effective use of OSM data. We also brought together a government panel from four different countries in this year’s SotM-Asia. We believe this event will deepen the bond and enhance collaboration among OSM communities across Asia. More information about the conference can be found on: http://stateofthemap.asia.
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Ramya Raghupathy, Mapbox, Basemap Completeness in Asian Cities | SotM Asia 2017
- How Complete is the Map? State of the Map Asia ramya@mapbox.com
- Completeness assessment • Tries to answer how much of the real world details reflect on the map • Feature level focus
- Completeness is a relative idea. A map is never complete!
- Why is completeness research important? • Identify areas to focus editing • Understand health of mapping community
- Prior work
- 80 cities for assessment
- From cities to tiles
- Compute basemap details for 1 billion z15 tiles worldwide
- Gold Standard • Benchmark / Baseline for a reliable reference • Helps measure quality in other datasets • Human Stamp of Approval • Use case: To determine model for feature level completeness that can be applied to estimate completeness elsewhere
- Gold Standard for Completeness Assessment • Identify Gold Standard tiles • Could be different for each feature • Start with a simple feature: building
- Identification of gold standard tiles for buildings I. Identify candidate tiles • Manual selection of candidate tiles likely to be excellent quality • Based on location (known edit patterns), feature counts/properties, “popularity”
- “Popular” = attracts lots of eyeballs
- Identification of gold standard tiles for buildings II. Three mappers rate each candidate tile on: • Coverage • Quality • Height • Building Type • Address Data
- Coverage:
- Coverage:
- Coverage:
- Coverage:
- Early learnings What predicts completeness?
- Densest tiles often have higher completeness
- Dense buildings in gold standard tile Kathmandu
- Dense buildings in gold standard tile Jakarta
- Dense buildings in gold standard tile New York City
- Dense buildings in gold standard tile Los Angeles
- Dense building tiles in gold standard tile San Francisco
- Dense building tiles in gold standard tile Washington DC
- But some less dense tiles are also very good
- Commercial areas have larger buildings, so less dense
- Built area as a better metric?
- Built area must account for parks, waterbodies, etc.
- But outside urban core, built area still not a predictor
- Suburb: low built area; quality map
- Road <-> building correlation?
- Residential roads in residential areas
- Commercial areas are surrounded by Major Highways
- Conclusion: It’s complex!
- Next steps: Building model integrating multiple factors based on gold standard ratings
- Dashboard
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