Pull OSM element type (N/W/R through to conflated dataset.

Author: njhenry

config.yaml

@@ -277,6 +277,7 @@ upload:
     conflated_layer_name: "conflated_pois"
     osm_properties:
       - osm_id
+      - osm_type       # node|way|relation — drives popup OSM link path
       - source
       - name
       - conf_mean      # drives confidence-based point coloring
@@ -292,6 +293,8 @@ upload:
     conflated_properties:
       - unified_id
       - source
+      - osm_id
+      - osm_type       # node|way|relation — drives popup OSM link path
       - shared_label
       - conf_mean
       - name

site/src/components/PoiPopup.vue

@@ -195,7 +195,7 @@
         <a
           v-if="entry.osm_id"
           class="osm-link"
-          :href="`https://www.openstreetmap.org/node/${cleanOsmId(entry.osm_id)}`"
+          :href="`https://www.openstreetmap.org/${entry.osm_type || 'node'}/${cleanOsmId(entry.osm_id)}`"
           target="_blank"
           rel="noopener"
         >

site/src/layers/conflatedLayer.js

@@ -70,6 +70,8 @@ export function wrapConflatedFeature(rf) {
     _source: 'conflated',
     unified_id: rf.get('unified_id'),
     source: rf.get('source'),
+    osm_id: rf.get('osm_id'),
+    osm_type: rf.get('osm_type'),
     shared_label: rf.get('shared_label'),
     name: rf.get('name'),
     brand: rf.get('brand'),

site/src/layers/osmLayer.js

@@ -75,6 +75,7 @@ export function wrapOsmFeature(rf) {
   const props = {
     _source: 'osm',
     osm_id: rf.get('osm_id'),
+    osm_type: rf.get('osm_type'),
     name: rf.get('name'),
     conf_mean: rf.get('conf_mean'),
     source_dataset: 'OpenStreetMap',

src/openpois/conflation/merge.py

@@ -116,6 +116,7 @@ def _build_matched_gdf(
     geoms = _pick_geometries(osm_geoms, ov_geoms)
 
     osm_ids = osm_gdf["osm_id"].to_numpy()[oi]
+    osm_types = osm_gdf["osm_type"].to_numpy()[oi]
     ov_ids = overture_gdf["overture_id"].to_numpy()[vi]
 
     unified_ids = np.array(
@@ -131,6 +132,7 @@ def _build_matched_gdf(
             "unified_id": unified_ids,
             "source": "matched",
             "osm_id": osm_ids,
+            "osm_type": osm_types,
             "overture_id": ov_ids,
             "name": names,
             "brand": brands,
@@ -166,6 +168,7 @@ def _build_unmatched_osm_gdf(
     n = len(idx)
 
     osm_ids = osm_gdf["osm_id"].to_numpy()[idx]
+    osm_types = osm_gdf["osm_type"].to_numpy()[idx]
     names = osm_gdf["name"].to_numpy()[idx]
     brand_arr = (
         osm_gdf["brand"].to_numpy()[idx]
@@ -186,6 +189,7 @@ def _build_unmatched_osm_gdf(
             "unified_id": unified_ids,
             "source": "osm",
             "osm_id": osm_ids,
+            "osm_type": osm_types,
             "overture_id": np.full(n, None, dtype = object),
             "name": names,
             "brand": brand_arr,
@@ -241,6 +245,7 @@ def _build_unmatched_overture_gdf(
             "unified_id": unified_ids,
             "source": "overture",
             "osm_id": np.full(n, None, dtype = object),
+            "osm_type": np.full(n, None, dtype = object),
             "overture_id": ov_ids,
             "name": names,
             "brand": brand_arr,

tests/test_merge.py

@@ -21,6 +21,7 @@ def osm_gdf():
     return gpd.GeoDataFrame(
         {
             "osm_id": [100, 200, 300],
+            "osm_type": ["node", "way", "relation"],
             "name": ["Coffee Shop", "Grocery Store", "Park"],
             "brand": ["Starbucks", None, None],
             "conf_mean": [0.8, 0.6, 0.9],
@@ -171,6 +172,7 @@ def test_geometry_preference_polygon_over_point(self):
         osm = gpd.GeoDataFrame(
             {
                 "osm_id": [1],
+                "osm_type": ["way"],
                 "name": ["Park"],
                 "brand": [None],
                 "conf_mean": [0.9],
@@ -219,7 +221,8 @@ def test_expected_columns(
             osm_labels, ov_labels,
         )
         expected_cols = {
-            "unified_id", "source", "osm_id", "overture_id",
+            "unified_id", "source", "osm_id", "osm_type",
+            "overture_id",
             "name", "brand", "shared_label",
             "conf_mean", "conf_lower", "conf_upper",
             "match_score", "match_distance_m",
@@ -252,6 +255,30 @@ def test_shared_label_values(
         ].iloc[0]
         assert park_row["shared_label"] == "Park"
 
+    def test_osm_type_propagation(
+        self, osm_gdf, overture_gdf, matches,
+    ):
+        """osm_type must flow through matched + unmatched-OSM rows and
+        be null on unmatched-Overture rows so the frontend can route
+        OpenStreetMap links to /node/, /way/, or /relation/ correctly.
+        """
+        osm_labels = np.array(["Cafe", "Supermarket", "Park"])
+        ov_labels = np.array(["Cafe", "Supermarket", "Park"])
+        result = merge_matched_pois(
+            osm_gdf, overture_gdf, matches,
+            osm_labels, ov_labels,
+        )
+        # Matched row (osm_idx=0 → node)
+        matched = result[result["source"] == "matched"].iloc[0]
+        assert matched["osm_type"] == "node"
+        # Unmatched-OSM rows (idx 1,2 → way, relation)
+        osm_only = result[result["source"] == "osm"].set_index("osm_id")
+        assert osm_only.loc[200, "osm_type"] == "way"
+        assert osm_only.loc[300, "osm_type"] == "relation"
+        # Unmatched-Overture rows carry no osm_type
+        ov_only = result[result["source"] == "overture"]
+        assert ov_only["osm_type"].isna().all()
+
 
 # -----------------------------------------------------------------
 # Disk-backed row-sliced merge