Preserve native orthophoto detail for training

backend/README.md

@@ -1357,6 +1357,10 @@ Settings: `ORTHOPHOTO_ENABLED`, `ORTHOPHOTO_WMS_URL`,
 `ORTHOPHOTO_TIMEOUT_SECONDS`, `ORTHOPHOTO_MAX_RESPONSE_MB` and
 `ORTHOPHOTO_CACHE_TTL_HOURS`. Keep the official HTTPS URL and 1 m profile
 unless a separately verified deployment/model profile requires a change.
+An explicit bounded request may provide `resolution_m` down to the governed
+product's native resolution. This is intended for reviewed training corpora;
+the service rejects source oversampling and records rolling-latest observation
+time as unknown per pixel rather than equating it with download time.
 
 Before a future `most_recent` source release is allowed into a governed pixel
 stage, run the metadata-only preflight for the exact intended rectangle:

backend/app/schemas/orthophoto.py

@@ -2,7 +2,7 @@ from __future__ import annotations
 
 from uuid import UUID
 
-from pydantic import BaseModel
+from pydantic import BaseModel, Field
 
 from .operations import VectorSelectionBBox
 
@@ -12,6 +12,7 @@ class OrthophotoAcquireRequest(BaseModel):
     area_id: UUID | None = None
     product_key: str = "most_recent"
     force_refresh: bool = False
+    resolution_m: float | None = Field(default=None, ge=0.1, le=2.0)
 
 
 class OrthophotoProductRead(BaseModel):

backend/app/services/orthophoto_acquisition_service.py

@@ -262,8 +262,16 @@ class OrthophotoAcquisitionService:
                 status_code=422,
             )
 
-        width = max(1, math.ceil(width_m / settings.orthophoto_resolution_m))
-        height = max(1, math.ceil(height_m / settings.orthophoto_resolution_m))
+        resolution_m = float(payload.resolution_m or settings.orthophoto_resolution_m)
+        if resolution_m < product.native_resolution_m:
+            raise AppError(
+                code="ORTHOPHOTO_RESOLUTION_EXCEEDS_SOURCE",
+                message="Requested sampling cannot be finer than the governed source resolution",
+                details={"requested_resolution_m": resolution_m, "native_resolution_m": product.native_resolution_m},
+                status_code=422,
+            )
+        width = max(1, math.ceil(width_m / resolution_m))
+        height = max(1, math.ceil(height_m / resolution_m))
         bbox_4326 = [min_x, min_y, max_x, max_y]
         bbox_31370 = [float(value) for value in lambert_bounds]
         request_identity = {
@@ -275,14 +283,14 @@ class OrthophotoAcquisitionService:
             "bbox_epsg31370": [round(value, 3) for value in bbox_31370],
             "width": width,
             "height": height,
-            "resolution_m": settings.orthophoto_resolution_m,
+            "resolution_m": resolution_m,
         }
         request_hash = hashlib.sha256(json.dumps(request_identity, sort_keys=True).encode("utf-8")).hexdigest()
         spatial_identity = {
             "bbox_epsg4326": request_identity["bbox_epsg4326"],
             "width": width,
             "height": height,
-            "resolution_m": settings.orthophoto_resolution_m,
+            "resolution_m": resolution_m,
         }
         spatial_hash = hashlib.sha256(json.dumps(spatial_identity, sort_keys=True).encode("utf-8")).hexdigest()
         params = {
@@ -522,7 +530,7 @@ class OrthophotoAcquisitionService:
                 layer=product.layer,
                 width=prepared["width"],
                 height=prepared["height"],
-                resolution_m=resolved_settings.orthophoto_resolution_m,
+                resolution_m=float(prepared["resolution_m"]),
                 bbox_epsg4326=prepared["bbox_epsg4326"],
                 bbox_epsg31370=prepared["bbox_epsg31370"],
                 attribution=product.attribution,
@@ -561,7 +569,10 @@ class OrthophotoAcquisitionService:
                 "observation_label": product.observation_label,
                 "observation_date_precision": product.temporal_granularity,
                 "native_resolution_m": product.native_resolution_m,
-                "requested_resolution_m": resolved_settings.orthophoto_resolution_m,
+                "requested_resolution_m": float(prepared["resolution_m"]),
+                "observation_time_precision": (
+                    "unknown_per_pixel" if product.key == "most_recent" or product.key.endswith("_latest") else "product_period"
+                ),
                 "color_mode": product.color_mode,
                 "supports_detection": product.supports_detection,
                 "layer": product.layer,
@@ -581,7 +592,7 @@ class OrthophotoAcquisitionService:
                 "bbox_epsg31370": prepared["bbox_epsg31370"],
                 "width": prepared["width"],
                 "height": prepared["height"],
-                "resolution_m": resolved_settings.orthophoto_resolution_m,
+                "resolution_m": float(prepared["resolution_m"]),
                 "limitation_message": product.limitation_message,
             },
         )
@@ -597,7 +608,7 @@ class OrthophotoAcquisitionService:
             layer=product.layer,
             width=prepared["width"],
             height=prepared["height"],
-            resolution_m=resolved_settings.orthophoto_resolution_m,
+            resolution_m=float(prepared["resolution_m"]),
             bbox_epsg4326=prepared["bbox_epsg4326"],
             bbox_epsg31370=prepared["bbox_epsg31370"],
             attribution=product.attribution,

backend/tests/test_sprint196_map_orthophoto_analysis.py

@@ -92,6 +92,7 @@ def _selection_payload(
     force_refresh: bool = True,
     area_id=None,
     product_key: str = "most_recent",
+    resolution_m: float | None = None,
 ) -> OrthophotoAcquireRequest:
     west, south = 199_000.0, 210_000.0
     transformer = Transformer.from_crs("EPSG:31370", "EPSG:4326", always_xy=True)
@@ -108,6 +109,7 @@ def _selection_payload(
         area_id=area_id,
         product_key=product_key,
         force_refresh=force_refresh,
+        resolution_m=resolution_m,
     )
 
 
@@ -143,6 +145,21 @@ def test_orthophoto_request_is_bounded_and_uses_official_wms_contract() -> None:
     assert len(prepared["request_hash"]) == 64
 
 
+def test_training_request_can_use_native_resolution_but_not_oversample_source() -> None:
+    settings = Settings(_env_file=None)
+    prepared = OrthophotoAcquisitionService._prepared_request(
+        _selection_payload(product_key="wallonia_latest", resolution_m=0.25), settings
+    )
+    assert 2_000 <= prepared["width"] <= 2_120
+    assert prepared["resolution_m"] == 0.25
+
+    with pytest.raises(AppError) as exc_info:
+        OrthophotoAcquisitionService._prepared_request(
+            _selection_payload(product_key="wallonia_latest", resolution_m=0.1), settings
+        )
+    assert exc_info.value.code == "ORTHOPHOTO_RESOLUTION_EXCEEDS_SOURCE"
+
+
 def test_orthophoto_product_registry_exposes_only_governed_official_layers() -> None:
     settings = Settings(_env_file=None)
     products = OrthophotoAcquisitionService.list_products(settings)

docs/API_CONTRACTS.md

@@ -385,6 +385,7 @@ least 99% of it.
   "bbox": {"min_x": 5.10, "min_y": 51.17, "max_x": 5.11, "max_y": 51.18, "crs": "EPSG:4326"},
   "area_id": "optional-project-area-uuid",
   "product_key": "most_recent",
+  "resolution_m": 0.25,
   "force_refresh": false
 }
 ```
@@ -394,6 +395,12 @@ identifies the raster Dataset; `result_json` contains provider, layer, pixel
 dimensions, EPSG:4326/EPSG:31370 bounds, sampling resolution, attribution,
 cache reuse and limitation text. Historical products also persist their
 observation/validity period and a spatially scoped temporal-series key.
+`resolution_m` is optional (0.1-2.0 m) and can never be finer than the
+allowlisted product's native resolution. It exists for governed training and
+review exports; ordinary workbench requests retain the configured 1 m default.
+For rolling `latest` products, acquisition time is not represented as the
+per-pixel observation date: provenance explicitly records
+`observation_time_precision=unknown_per_pixel`.
 
 ### GET `/api/v1/projects/{project_id}/datasets/grb/products`
 

frontend/src/types.ts

@@ -358,6 +358,7 @@ export interface OrthophotoAcquireRequest {
   area_id?: string
   product_key?: string
   force_refresh?: boolean
+  resolution_m?: number
 }
 
 export interface OrthophotoProductRead {

scripts/assemble_belgium_building_corpus.py

@@ -142,7 +142,12 @@ def main() -> int:
                 raster_path=raster_target,
                 source_name=reference_source,
                 min_label_px=args.min_label_px,
-                imagery_observed_at=raster.observed_at.isoformat() if raster.observed_at else None,
+                imagery_observed_at=(
+                    raster.observed_at.isoformat()
+                    if raster.observed_at
+                    and (raster.source_metadata or {}).get("observation_time_precision") != "unknown_per_pixel"
+                    else None
+                ),
                 reference_observed_at=reference.observed_at.isoformat() if reference.observed_at else None,
             )
             normalized_target.write_text(json.dumps(normalized, ensure_ascii=False), encoding="utf-8")

scripts/normalize_belgium_building_labels.py

@@ -160,10 +160,12 @@ def normalize(
             counts[str(decision["reason"])] += 1
 
     temporal_mismatch_days = None
+    temporal_alignment_status = "unknown"
     if imagery_observed_at and reference_observed_at:
         imagery_date = datetime.fromisoformat(imagery_observed_at.replace("Z", "+00:00"))
         reference_date = datetime.fromisoformat(reference_observed_at.replace("Z", "+00:00"))
         temporal_mismatch_days = abs((imagery_date - reference_date).days)
+        temporal_alignment_status = "measured"
     normalized = {
         "type": "FeatureCollection",
         "name": f"canonical-building-{source_name}",
@@ -179,6 +181,7 @@ def normalize(
         "imagery_observed_at": imagery_observed_at,
         "reference_observed_at": reference_observed_at,
         "temporal_mismatch_days": temporal_mismatch_days,
+        "temporal_alignment_status": temporal_alignment_status,
         "input_feature_count": len(payload["features"]),
         "accepted_feature_count": len(accepted),
         "decision_counts": dict(sorted(counts.items())),