feat(sql): dim_cities — GeoNames spatial population fallback

Adds a coordinate-based population lookup as a fallback when string name
matching fails (~29% of cities). Uses bbox pre-filter (0.14° ≈ 15 km) then
ST_Distance_Sphere to find the nearest GeoNames location in the same country.

Fixes localization mismatches: Milano≠Milan, Wien≠Vienna, München≠Munich.

Population cascade: Eurostat EU > US Census > ONS UK > GeoNames string >
GeoNames spatial > 0.

Coverage: 70.5% → 98.5% (5,401 / 5,481 cities with population > 0).
Key cities before/after:
  Wien:   0 → 1,691,468
  Milano: 0 → 1,371,498
  München: already matched by string; verified still correct at 1,488,719

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

transform/sqlmesh_padelnomics/models/foundation/dim_cities.sql

@@ -12,7 +12,9 @@
 --   stg_population_uk    → ONS LAD population
 --   stg_population_geonames → GeoNames global fallback
 --
--- Population cascade: Eurostat EU > US Census > ONS UK > GeoNames > 0.
+-- Population cascade: Eurostat EU > US Census > ONS UK > GeoNames string > GeoNames spatial > 0.
+-- GeoNames spatial fallback: finds nearest location within ~15km when string name match fails.
+-- Fixes localization mismatches: Milano≠Milan, Wien≠Vienna, München≠Munich (~29% of cities).
 -- City name matching is case/whitespace-insensitive within each country.
 --
 -- Grain: (country_code, city_slug) — two cities in different countries can share a
@@ -75,9 +77,33 @@ uk_pop AS (
 ),
 -- GeoNames global fallback (all cities ≥50K)
 geonames_pop AS (
-  SELECT geoname_id, city_name, country_code, population, ref_year
+  SELECT geoname_id, city_name, country_code, lat, lon, population, ref_year
   FROM staging.stg_population_geonames
   QUALIFY ROW_NUMBER() OVER (PARTITION BY geoname_id ORDER BY ref_year DESC) = 1
+),
+-- GeoNames spatial fallback: for cities where string name match fails,
+-- find the nearest GeoNames location within ~15km.
+-- Fixes localization mismatches: Milano≠Milan, Wien≠Vienna, München≠Munich.
+-- Uses bbox pre-filter (ABS < 0.14°) then exact sphere distance, picks nearest.
+geonames_spatial AS (
+  SELECT
+    vc.country_code,
+    vc.city_slug,
+    gn.geoname_id                                            AS spatial_geoname_id,
+    gn.population                                            AS spatial_population,
+    gn.ref_year                                              AS spatial_ref_year
+  FROM venue_cities vc
+  JOIN geonames_pop gn
+    ON vc.country_code = gn.country_code
+    AND ABS(vc.centroid_lat - gn.lat) < 0.14   -- ~15km bbox pre-filter
+    AND ABS(vc.centroid_lon - gn.lon) < 0.14
+  QUALIFY ROW_NUMBER() OVER (
+    PARTITION BY vc.country_code, vc.city_slug
+    ORDER BY ST_Distance_Sphere(
+      ST_Point(vc.centroid_lon, vc.centroid_lat),
+      ST_Point(gn.lon, gn.lat)
+    )
+  ) = 1
 )
 SELECT
   vc.country_code,
@@ -135,13 +161,14 @@ SELECT
   ))                                                         AS country_slug,
   vc.centroid_lat                                            AS lat,
   vc.centroid_lon                                            AS lon,
-  -- Population cascade: Eurostat EU > US Census > ONS UK > GeoNames > 0.
+  -- Population cascade: Eurostat EU > US Census > ONS UK > GeoNames string > GeoNames spatial > 0.
-  -- City name match is case/whitespace-insensitive within each country.
+  -- Spatial fallback activates only when all string matches fail (~29% of cities).
   COALESCE(
     ep.population,
     usa.population,
     uk.population,
     gn.population,
+    gs.spatial_population,
     0
   )::BIGINT                                                  AS population,
   COALESCE(
@@ -149,14 +176,15 @@ SELECT
     usa.ref_year,
     uk.ref_year,
     gn.ref_year,
+    gs.spatial_ref_year,
     0
   )::INTEGER                                                 AS population_year,
   vc.padel_venue_count,
   ci.median_income_pps,
   ci.income_year,
   -- GeoNames ID: FK to dim_locations / location_opportunity_profile.
-  -- NULL when city name doesn't match any GeoNames entry.
+  -- String match preferred; spatial fallback used when name doesn't match (Milano→Milan, etc.)
-  gn.geoname_id
+  COALESCE(gn.geoname_id, gs.spatial_geoname_id)            AS geoname_id
 FROM venue_cities vc
 LEFT JOIN country_income ci ON vc.country_code = ci.country_code
 -- Eurostat EU population (via city code→name lookup)
@@ -171,10 +199,14 @@ LEFT JOIN us_pop usa
 LEFT JOIN uk_pop uk
   ON vc.country_code = uk.country_code
   AND LOWER(TRIM(vc.city_name)) = LOWER(TRIM(uk.city_name))
--- GeoNames global fallback
+-- GeoNames string match (primary)
 LEFT JOIN geonames_pop gn
   ON vc.country_code = gn.country_code
   AND LOWER(TRIM(vc.city_name)) = LOWER(TRIM(gn.city_name))
+-- GeoNames spatial fallback (nearest within ~15km, for when name match fails)
+LEFT JOIN geonames_spatial gs
+  ON vc.country_code = gs.country_code
+  AND vc.city_slug = gs.city_slug
 -- Enforce grain: if two cities in the same country have the same slug
 -- (e.g. 'São Paulo' and 'Sao Paulo'), keep the one with more venues
 QUALIFY ROW_NUMBER() OVER (