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A while back I posted here about SafeStreets, a free walkability and pedestrian-safety scorer that runs on OSM for any address, with Nimman Road in Chiang Mai as the example. Since then the product has moved on in two ways that I thought I can share: the scoring model and how it reads OSM changed. My focus has shifted to the US, so most of what follows is about that, with a short note on the international path at the end.
What changed in the product
The first entry described an earlier model built around a Network Design component (35 percent) and an Accessibility component (25 percent), with greenery and destination access making up the rest. The composite is now four components on a 0 to 10 scale:
Daily Reach:40 percent. Proximity-weighted access to 7 service categories.
Street Safety: 30 percent. Now its own first-class component, a weighted-OR of a crossings grid against pedestrian separation, plus a speed-exposure proxy.
Transit Reach:15 percent. GTFS via Transitland, OSM stops as fallback.
Walking Comfort:15 percent. Sentinel-2 canopy, terrain, air quality (the one non-OSM component).
There is also a new 6-tier label on top of the number, from Pedestrian-first down to Hostile, so the score reads in plain language rather than just a figure.
How it reads OSM now
The bigger change is mechanical. In the first entry every score hit live Overpass inside an 800m and 1,200m query, which was slow and broke whenever Overpass rate-limited me. US scoring is now Overpass-free. I precompute the street and safety metrics from a planet extract onto an H3 resolution-9 grid (roughly 26 million hexes covering the US, about 0.1 km2 each), paired with a local OSM POI layer of around 2 million amenities. A US score is now a hex lookup plus a POI merge, no live API call.
The OSM tags doing the work, by component:
Daily Reach: shop=, amenity=, leisure=, healthcare=, classified into the 7 categories and scored by distance to nearest plus density.
Street Safety: highway=crossing and footway=crossing for crossing coverage, sidewalk=* and highway=footway for pedestrian separation, and highway=* class plus maxspeed for speed exposure. Pedestrianized ways (highway=pedestrian, living_street) score highest.
Transit Reach: highway=bus_stop, railway=station/tram_stop, public_transport=platform where GTFS is thin.
So OSM is still the backbone for everything except comfort. The precompute moved the reading from request-time to build-time.
The international path-Briefly
International addresses, including Southeast Asia, still go through live Overpass with an Overture POI backfill. Same tags and model, read live rather than from the precomputed grid.
A note on limits
The precompute is a snapshot, so a US crossing you tag today does not move the score until I rebuild the grid. And at res-9 the safety signal is per-hex, not per-point, so it answers “is this a walkable area” rather than door-level precision. Where sidewalks and crossings are tagged, the score tracks reality closely; where they are not, Street Safety leans on road class and understates well-mapped quiet streets. sidewalk=, crossing=, and lit=* on ways remain the tags that most directly move a score.
If a US street you know well scores in a way that feels off, that mismatch is the feedback I am looking for. None of this works without OSM. Thank you all.
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