don't crash

pipeline/transform/tree_density.py

@@ -263,6 +263,43 @@ def _postcode_buffers(
     return circles, shapely.STRtree(circles)
 
 
+# 0.1 mm in the BNG working CRS (EPSG:27700) — far below survey resolution; the
+# same grid the postcode_boundaries overlay uses.
+_OVERLAY_GRID_M = 1e-4
+
+
+def _robust_intersection_area(a: np.ndarray, b: np.ndarray) -> np.ndarray:
+    """Vectorized ``area(a[i] ∩ b[i])`` that survives GEOS robustness failures.
+
+    External Forest Research TOW/NFI polygons are occasionally invalid
+    (self-intersections), and a single bad polygon makes the batched
+    ``shapely.intersection`` raise ``TopologyException: side location conflict``,
+    aborting the whole run. The fast path is the raw batched overlay — unchanged,
+    full-speed, when the data is clean — and only a failure triggers repair.
+
+    The repair deliberately uses a *plain* overlay rather than the fixed-precision
+    (``grid_size``) one: ``make_valid`` can emit a mixed-dimension
+    ``GeometryCollection`` (a polygon plus a dangling line), which OverlayNG
+    rejects with ``Overlay input is mixed-dimension`` — whereas a plain overlay
+    accepts it, and its non-polygonal debris has zero area and is dropped by the
+    ``clipped_area > 0`` filter downstream anyway. A final pointwise coordinate
+    snap (which never raises) collapses the near-coincident edges behind any
+    residual full-precision robustness failure.
+    """
+    try:
+        return shapely.area(shapely.intersection(a, b))
+    except shapely.errors.GEOSException:
+        pass
+    a = shapely.make_valid(a)
+    b = shapely.make_valid(b)
+    try:
+        return shapely.area(shapely.intersection(a, b))
+    except shapely.errors.GEOSException:
+        a = shapely.make_valid(shapely.set_precision(a, _OVERLAY_GRID_M, mode="pointwise"))
+        b = shapely.make_valid(shapely.set_precision(b, _OVERLAY_GRID_M, mode="pointwise"))
+        return shapely.area(shapely.intersection(a, b))
+
+
 def _accumulate_clipped_area(
     geoms: np.ndarray,
     circles: np.ndarray,
@@ -294,8 +331,8 @@ def _accumulate_clipped_area(
     if geom_index.size == 0:
         return
 
-    clipped_area = shapely.area(
-        shapely.intersection(geoms[geom_index], circles[postcode_index])
+    clipped_area = _robust_intersection_area(
+        geoms[geom_index], circles[postcode_index]
     )
     positive = clipped_area > 0
     geom_index = geom_index[positive]