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Adds the City of Sandpoint's printed "Downtown & Waterfront Public Parking" map as a georeferenced overlay, and lets you track your time on any of its areas without ever touching the ParkSmarter/IPS API. Georeferencing (tools/citymap/) - The PDF carries no geo metadata, so the page->WebMercator affine is recovered by fitting the drawing to OSM street centrelines. - pdftocairo writes stroked street segments with per-path matrix() transforms in local coords while filled lots are absolute; both are handled. The five legend swatches share the real geometry's colours and are identified by stroke-width and position, then dropped. - 49 areas, fitted to RMS 4.1 m (X) / 3.5 m (Y). On-street segments land a mean 4.0 m from the nearest OSM road. sp-039/040 sit further out because they are angled bays along the old rail corridor, on no named road at all. - Sandpoint's grid jogs 38 m between N 2nd Ave and S 2nd Ave; the page shows the same jog at the fitted scale, which independently confirms the fit. App - Map tab: "City map" layer in the legend's colours, tappable. - "Park here" pins the car from GPS and auto-detects the containing area (40 m snap). With no fix it asks you to tap the spot instead, so the pin never depends on GPS working. - The pin lives in its own storage key, not inside the session: pinning the car without starting a timer must survive backing out of the screen. - Durations cap at the posted limit — a 2-hour space is not offered a 4-hour timer. Lots and no-limit spots get the long options. - Reuses the existing foreground-service countdown. The second notification button reads "+1 hr" for a city area rather than "Extend": there is nothing to buy, so it edits the local timer and says so. - Account -> Align city map: nudge/scale/rotate the whole overlay against a live GPS fix. Save-on-phone needs no admin token, since the person who can see the misalignment is the one standing on the street. Server - parking_areas + map_overlay tables, public read, admin replace-all. The areas come from one source document, so replacement is wholesale rather than an upsert. Dropped geometryCenter from the geo module: on the real data it returns a point in the water for the crescent City Beach lot and mid-block for L-shaped runs. Nothing used it. Tests: 8 geometry tests in app/, 5 area/overlay tests in server/. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
72 lines
3.4 KiB
Markdown
72 lines
3.4 KiB
Markdown
# Georeferencing the city parking map
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Turns the City of Sandpoint's printed **Downtown & Waterfront Public Parking** PDF into
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`app/src/features/citymap/parkingAreas.json` — the colour-coded overlay the app draws and
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hit-tests against.
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Run this again when the city publishes a new edition of the map.
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## Why it needs doing at all
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The PDF carries **no** georeferencing metadata (no `/Measure`, `/GPTS`, `/LPTS`, `/GEO`,
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`/Viewport`, `/GCS`). It is a north-up Web Mercator screenshot of a slippy map with vector
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parking stripes drawn on top, so page coordinates relate to the world by a plain affine
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transform — which has to be recovered by fitting the drawing to something we already know
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the coordinates of. That something is OpenStreetMap's street centrelines.
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Two structural details cost the most time, so they are worth knowing up front:
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- `pdftocairo` writes each **stroked** street segment with its own `matrix()` transform and
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*local* coordinates, while **filled** lots are in absolute page coordinates. Both have to
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be handled or the streets land in a heap near the origin.
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- The legend swatches are drawn in the same five colours as the real geometry. They are
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identified by stroke-width 7 inside the legend card's x-band and dropped.
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## Pipeline
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```bash
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# 0. deps: poppler-utils (pdftocairo, pdftotext, pdfimages), python3, curl
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pdftocairo -svg downtown_and_waterfront_public_parking_map.pdf map.svg
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# 1. vector geometry -> page coordinates, bucketed by the legend's five colours
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python3 extract_map.py map.svg map_page_coords.json
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# 2. OSM street centrelines for downtown Sandpoint
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curl -s --data-binary @roads.overpass https://overpass-api.de/api/interpreter -o osm.json
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# 3. fit page -> Web Mercator against named streets; prints per-street residuals
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python3 georef.py # writes fit_raw.json
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# 4. apply the fit, name each area from OSM, verify, emit the GeoJSON
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python3 build_geojson.py # writes parking_areas.geojson
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cp parking_areas.geojson ../../app/src/features/citymap/parkingAreas.json
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```
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## What "good" looks like
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`georef.py` prints a residual per control street and `build_geojson.py` prints how far each
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on-street segment sits from the nearest OSM road. The current edition fits to:
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| Check | Result |
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| --- | --- |
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| X control residual (avenues) | **RMS 4.1 m** |
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| Y control residual (streets) | **RMS 3.5 m** |
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| On-street segments vs nearest OSM road | **mean 4.0 m**, 40 of 42 under 10 m |
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The two segments over 10 m (`sp-039`, `sp-040`) are correct, not errors: they are angled
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bays along the old rail corridor that sit on no named road at all — the nearest way is a
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service alley 19 m off. Anything much worse than the table above means a control street was
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mis-identified; `georef.py`'s per-street residuals will say which.
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Residual error is also correctable after the fact without re-running any of this — the app's
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**Account → Align city map** screen nudges the whole overlay against a live GPS fix and
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persists the correction.
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## Control points
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`georef.py` maps page grid lines to OSM street names by hand (`AVENUES` / `STREETS`). Sandpoint's
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grid **jogs** between its north and south halves — North 2nd Ave and South 2nd Ave are 38 m
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apart — so each control street is measured only over the span its page segment actually
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covers, and both halves are used as independent control points. That jog is a useful sanity
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check: the page shows the same 9.3 pt offset, which at the fitted scale is 38 m.
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