feat: add governed hydrology and historical imagery

backend/app/services/dataset_service.py

@@ -422,6 +422,11 @@ class DatasetService:
         source_metadata: dict[str, Any],
         provenance_metadata: dict[str, Any],
         area_id: UUID | None = None,
+        temporal_series_key: str | None = None,
+        observed_at: datetime | None = None,
+        valid_from: datetime | None = None,
+        valid_to: datetime | None = None,
+        temporal_granularity: str | None = None,
         source_version: str | None = None,
         content_type: str = "image/tiff",
     ) -> DatasetCreateResponse:
@@ -438,6 +443,14 @@ class DatasetService:
         safe_filename = DatasetService._validate_upload_filename(filename)
         if DatasetService._extension_for_path(safe_filename) not in DatasetService.RASTER_EXTENSIONS:
             raise AppError(code="INVALID_UPLOAD", message="Raster artifacts require a GeoTIFF filename", status_code=415)
+        temporal = DatasetService._validate_temporal_metadata(
+            temporal_series_key=temporal_series_key,
+            observed_at=observed_at,
+            valid_from=valid_from,
+            valid_to=valid_to,
+            temporal_granularity=temporal_granularity,
+            source_version=source_version,
+        )
 
         dataset_id = uuid.uuid4()
         storage_info = StorageService.persist_dataset_file(
@@ -462,7 +475,7 @@ class DatasetService:
                 source_metadata=source_metadata,
                 provenance_metadata=provenance_metadata,
                 imported_at=datetime.now(timezone.utc),
-                source_version=source_version,
+                **temporal,
                 storage_path=storage_info["storage_path"],
                 original_filename=storage_info["original_filename"],
                 stored_filename=storage_info["stored_filename"],
@@ -483,6 +496,9 @@ class DatasetService:
                     version=1,
                     storage_path=dataset.storage_path,
                     source_version=dataset.source_version,
+                    observed_at=dataset.observed_at,
+                    valid_from=dataset.valid_from,
+                    valid_to=dataset.valid_to,
                     checksum_sha256=dataset.checksum_sha256,
                     source_metadata=dataset.source_metadata,
                     provenance_metadata=dataset.provenance_metadata,

backend/app/services/geo_assistant_service.py

@@ -349,6 +349,7 @@ class GeoAssistantService:
                             "measurement_quality": (
                                 "schatting" if summary["is_estimate"] else "exact_binnen_bronrepresentatie"
                             ),
+                            "warning": summary.get("warning"),
                         }
                     )
                     if dataset.id not in source_dataset_ids:

backend/app/services/orthophoto_acquisition_service.py

@@ -1,9 +1,11 @@
 from __future__ import annotations
 
 import hashlib
+import io
 import json
 import math
 import warnings
+from dataclasses import dataclass
 from datetime import UTC, datetime, timedelta
 from pathlib import Path
 from typing import Any, Callable
@@ -20,21 +22,169 @@ from shapely.ops import transform as shapely_transform
 from app.core.config import Settings, get_settings
 from app.core.errors import AppError
 from app.models import Area, Dataset, Project
-from app.schemas.orthophoto import OrthophotoAcquireRequest, OrthophotoAcquisitionResult
+from app.schemas.orthophoto import OrthophotoAcquireRequest, OrthophotoAcquisitionResult, OrthophotoProductRead
 from app.services.dataset_service import DatasetService
 
 
+@dataclass(frozen=True)
+class OrthophotoProduct:
+    key: str
+    display_name: str
+    observation_label: str
+    temporal_granularity: str
+    native_resolution_m: float
+    wms_url: str
+    layer: str
+    catalog_url: str
+    limitation_message: str
+    supports_detection: bool = False
+    color_mode: str = "rgb"
+    observed_at: datetime | None = None
+    valid_from: datetime | None = None
+    valid_to: datetime | None = None
+
+
 class OrthophotoAcquisitionService:
     PROVIDER = "digitaal_vlaanderen_orthophoto"
     ATTRIBUTION = "Bron: Orthofotomozaiek Vlaanderen, Digitaal Vlaanderen"
     CATALOG_URL = "https://www.vlaanderen.be/datavindplaats/catalogus/orthofotomozaiek-middenschalig-winteropnamen-kleur-meest-recent-vlaanderen"
     LIMITATION = "Meest recente samengestelde winterorthofoto op het moment van de aanvraag; geen historische opnamedatum per pixel."
+    HISTORICAL_WINTER_WMS_URL = "https://geo.api.vlaanderen.be/OMW/wms"
+    HISTORICAL_WINTER_CATALOG_URL = "https://www.vlaanderen.be/datavindplaats/catalogus/wmts-orthofotomozaiek-middenschalig-winteropnamen"
+    HISTORICAL_SUMMER_WMS_URL = "https://geo.api.vlaanderen.be/OKZ/wms"
+    HISTORICAL_SUMMER_CATALOG_URL = "https://www.vlaanderen.be/datavindplaats/catalogus/orthofotomozaiek-kleinschalig-zomeropnamen"
+
+    @staticmethod
+    def _products(settings: Settings) -> dict[str, OrthophotoProduct]:
+        products: list[OrthophotoProduct] = [
+            OrthophotoProduct(
+                key="most_recent",
+                display_name="Meest recente winterluchtbeeld",
+                observation_label="Meest recent beschikbaar",
+                temporal_granularity="snapshot",
+                native_resolution_m=0.15,
+                wms_url=settings.orthophoto_wms_url,
+                layer=settings.orthophoto_wms_layer,
+                catalog_url=OrthophotoAcquisitionService.CATALOG_URL,
+                limitation_message=OrthophotoAcquisitionService.LIMITATION,
+                supports_detection=True,
+            )
+        ]
+        for year in range(2025, 2011, -1):
+            products.append(
+                OrthophotoProduct(
+                    key=str(year),
+                    display_name=f"Winterluchtbeeld {year}",
+                    observation_label=str(year),
+                    temporal_granularity="year",
+                    native_resolution_m=0.15 if year >= 2022 else 0.25,
+                    wms_url=OrthophotoAcquisitionService.HISTORICAL_WINTER_WMS_URL,
+                    layer=f"OMWRGB{year % 100:02d}VL",
+                    catalog_url=OrthophotoAcquisitionService.HISTORICAL_WINTER_CATALOG_URL,
+                    limitation_message=(
+                        "Officiële samengestelde winterorthofoto voor deze jaargang; de exacte opnamedatum kan per tegel verschillen. "
+                        "Historische beelden worden niet met de actuele GRB-toestand gevalideerd."
+                    ),
+                    observed_at=datetime(year, 1, 1, tzinfo=UTC),
+                    valid_from=datetime(year, 1, 1, tzinfo=UTC),
+                    valid_to=datetime(year, 12, 31, 23, 59, 59, tzinfo=UTC),
+                )
+            )
+        for key, start_year, end_year, layer in (
+            ("2008_2011", 2008, 2011, "OMWRGB08_11VL"),
+            ("2005_2007", 2005, 2007, "OMWRGB05_07VL"),
+            ("2000_2003", 2000, 2003, "OMWRGB00_03VL"),
+        ):
+            products.append(
+                OrthophotoProduct(
+                    key=key,
+                    display_name=f"Winterluchtbeeld {start_year}-{end_year}",
+                    observation_label=f"{start_year}-{end_year}",
+                    temporal_granularity="period",
+                    native_resolution_m=0.25,
+                    wms_url=OrthophotoAcquisitionService.HISTORICAL_WINTER_WMS_URL,
+                    layer=layer,
+                    catalog_url=OrthophotoAcquisitionService.HISTORICAL_WINTER_CATALOG_URL,
+                    limitation_message=(
+                        "Officiële samengestelde winterorthofoto uit een meerjarige opnameperiode; dit is geen exacte jaaropname. "
+                        "Historische beelden worden niet met de actuele GRB-toestand gevalideerd."
+                    ),
+                    observed_at=datetime(start_year, 1, 1, tzinfo=UTC),
+                    valid_from=datetime(start_year, 1, 1, tzinfo=UTC),
+                    valid_to=datetime(end_year, 12, 31, 23, 59, 59, tzinfo=UTC),
+                )
+            )
+        products.extend(
+            [
+                OrthophotoProduct(
+                    key="1979_1990",
+                    display_name="Zomerluchtbeeld 1979-1990",
+                    observation_label="1979-1990",
+                    temporal_granularity="period",
+                    native_resolution_m=1.0,
+                    wms_url=OrthophotoAcquisitionService.HISTORICAL_SUMMER_WMS_URL,
+                    layer="OKZRGB79_90VL",
+                    catalog_url=OrthophotoAcquisitionService.HISTORICAL_SUMMER_CATALOG_URL,
+                    limitation_message="Kleinschalig RGB-mozaïek uit meerdere zomervluchten tussen 1979 en 1990; geen exacte jaartoestand.",
+                    observed_at=datetime(1979, 1, 1, tzinfo=UTC),
+                    valid_from=datetime(1979, 1, 1, tzinfo=UTC),
+                    valid_to=datetime(1990, 12, 31, 23, 59, 59, tzinfo=UTC),
+                ),
+                OrthophotoProduct(
+                    key="1971",
+                    display_name="Zomerluchtbeeld 1971",
+                    observation_label="1971",
+                    temporal_granularity="year",
+                    native_resolution_m=1.0,
+                    wms_url=OrthophotoAcquisitionService.HISTORICAL_SUMMER_WMS_URL,
+                    layer="OKZPAN71VL",
+                    catalog_url=OrthophotoAcquisitionService.HISTORICAL_SUMMER_CATALOG_URL,
+                    limitation_message="Kleinschalig panchromatisch mozaïek uit 1971; zwart-wit en niet geschikt voor het huidige RGB-detectiemodel.",
+                    color_mode="panchromatic",
+                    observed_at=datetime(1971, 1, 1, tzinfo=UTC),
+                    valid_from=datetime(1971, 1, 1, tzinfo=UTC),
+                    valid_to=datetime(1971, 12, 31, 23, 59, 59, tzinfo=UTC),
+                ),
+            ]
+        )
+        return {product.key: product for product in products}
+
+    @staticmethod
+    def list_products(settings: Settings | None = None) -> list[dict[str, Any]]:
+        resolved_settings = settings or get_settings()
+        return [
+            OrthophotoProductRead(
+                key=product.key,
+                display_name=product.display_name,
+                observation_label=product.observation_label,
+                temporal_granularity=product.temporal_granularity,
+                native_resolution_m=product.native_resolution_m,
+                supports_detection=product.supports_detection,
+                color_mode=product.color_mode,
+                catalog_url=product.catalog_url,
+                limitation_message=product.limitation_message,
+            ).model_dump()
+            for product in OrthophotoAcquisitionService._products(resolved_settings).values()
+        ]
+
+    @staticmethod
+    def _product(product_key: str, settings: Settings) -> OrthophotoProduct:
+        product = OrthophotoAcquisitionService._products(settings).get(product_key.strip().lower())
+        if product is None:
+            raise AppError(
+                code="ORTHOPHOTO_PRODUCT_NOT_SUPPORTED",
+                message="Select an orthophoto product from the official product registry",
+                details={"product_key": product_key},
+                status_code=422,
+            )
+        return product
 
     @staticmethod
     def _prepared_request(
         payload: OrthophotoAcquireRequest,
         settings: Settings,
     ) -> dict[str, Any]:
+        product = OrthophotoAcquisitionService._product(payload.product_key, settings)
         if payload.bbox.crs.upper() != "EPSG:4326":
             raise AppError(code="INVALID_CRS", message="Orthophoto selection bbox must use EPSG:4326", status_code=400)
         min_x = float(payload.bbox.min_x)
@@ -68,8 +218,9 @@ class OrthophotoAcquisitionService:
         bbox_31370 = [float(value) for value in lambert_bounds]
         request_identity = {
             "provider": OrthophotoAcquisitionService.PROVIDER,
-            "wms_url": settings.orthophoto_wms_url,
-            "layer": settings.orthophoto_wms_layer,
+            "product_key": product.key,
+            "wms_url": product.wms_url,
+            "layer": product.layer,
             "bbox_epsg4326": [round(value, 8) for value in bbox_4326],
             "bbox_epsg31370": [round(value, 3) for value in bbox_31370],
             "width": width,
@@ -77,11 +228,18 @@ class OrthophotoAcquisitionService:
             "resolution_m": settings.orthophoto_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,
+        }
+        spatial_hash = hashlib.sha256(json.dumps(spatial_identity, sort_keys=True).encode("utf-8")).hexdigest()
         params = {
             "SERVICE": "WMS",
             "VERSION": "1.3.0",
             "REQUEST": "GetMap",
-            "LAYERS": settings.orthophoto_wms_layer,
+            "LAYERS": product.layer,
             "STYLES": "",
             "FORMAT": "image/tiff",
             "CRS": "EPSG:31370",
@@ -91,8 +249,10 @@ class OrthophotoAcquisitionService:
         }
         return {
             **request_identity,
+            "product": product,
+            "spatial_hash": spatial_hash,
             "request_hash": request_hash,
-            "request_url": f"{settings.orthophoto_wms_url}?{urlencode(params)}",
+            "request_url": f"{product.wms_url}?{urlencode(params)}",
             "params": params,
             "bbox_epsg4326": bbox_4326,
             "bbox_epsg31370": bbox_31370,
@@ -124,8 +284,14 @@ class OrthophotoAcquisitionService:
             )
 
     @staticmethod
-    def _cached_dataset(db, project_id: UUID, filename: str, settings: Settings) -> Dataset | None:
-        if settings.orthophoto_cache_ttl_hours <= 0:
+    def _cached_dataset(
+        db,
+        project_id: UUID,
+        filename: str,
+        settings: Settings,
+        product: OrthophotoProduct,
+    ) -> Dataset | None:
+        if product.key == "most_recent" and settings.orthophoto_cache_ttl_hours <= 0:
             return None
         candidate = (
             db.query(Dataset)
@@ -145,7 +311,7 @@ class OrthophotoAcquisitionService:
             return None
         if imported_at.tzinfo is None:
             imported_at = imported_at.replace(tzinfo=UTC)
-        if datetime.now(UTC) - imported_at > timedelta(hours=settings.orthophoto_cache_ttl_hours):
+        if product.key == "most_recent" and datetime.now(UTC) - imported_at > timedelta(hours=settings.orthophoto_cache_ttl_hours):
             return None
         return candidate
 
@@ -196,7 +362,9 @@ class OrthophotoAcquisitionService:
                 with warnings.catch_warnings():
                     warnings.simplefilter("ignore", NotGeoreferencedWarning)
                     with source_memory.open() as source:
-                        if source.width != prepared["width"] or source.height != prepared["height"] or source.count < 3:
+                        product: OrthophotoProduct = prepared["product"]
+                        minimum_band_count = 1 if product.color_mode == "panchromatic" else 3
+                        if source.width != prepared["width"] or source.height != prepared["height"] or source.count < minimum_band_count:
                             raise AppError(
                                 code="ORTHOPHOTO_PROVIDER_INVALID_RESPONSE",
                                 message="Official orthophoto dimensions or RGB bands do not match the bounded request",
@@ -216,7 +384,7 @@ class OrthophotoAcquisitionService:
                         with output_memory.open(**profile) as output:
                             output.write(image)
                             output.update_tags(
-                                source="Digitaal Vlaanderen OMWRGBMRVL WMS Ortho layer",
+                                source=f"Digitaal Vlaanderen WMS {product.layer}",
                                 source_url=prepared["request_url"],
                                 attribution=OrthophotoAcquisitionService.ATTRIBUTION,
                                 acquisition="explicit_bounded_map_selection",
@@ -245,44 +413,74 @@ class OrthophotoAcquisitionService:
         if not resolved_settings.orthophoto_enabled:
             raise AppError(code="ORTHOPHOTO_NOT_CONFIGURED", message="Official orthophoto acquisition is disabled", status_code=503)
         prepared = OrthophotoAcquisitionService._prepared_request(payload, resolved_settings)
+        product: OrthophotoProduct = prepared["product"]
         OrthophotoAcquisitionService._validate_area_scope(db, project_id, payload.area_id, prepared["bbox_epsg4326"])
-        filename = f"orthofoto_selectie_{prepared['request_hash'][:12]}.tif"
+        filename = f"orthofoto_{product.key}_{prepared['request_hash'][:12]}.tif"
 
-        cached = None if payload.force_refresh else OrthophotoAcquisitionService._cached_dataset(db, project_id, filename, resolved_settings)
+        cached = None if payload.force_refresh else OrthophotoAcquisitionService._cached_dataset(
+            db,
+            project_id,
+            filename,
+            resolved_settings,
+            product,
+        )
         if cached is not None:
             return OrthophotoAcquisitionResult(
                 output_dataset_id=cached.id,
                 reused=True,
                 provider=OrthophotoAcquisitionService.PROVIDER,
-                layer=resolved_settings.orthophoto_wms_layer,
+                product_key=product.key,
+                display_name=product.display_name,
+                observation_label=product.observation_label,
+                temporal_granularity=product.temporal_granularity,
+                supports_detection=product.supports_detection,
+                layer=product.layer,
                 width=prepared["width"],
                 height=prepared["height"],
                 resolution_m=resolved_settings.orthophoto_resolution_m,
                 bbox_epsg4326=prepared["bbox_epsg4326"],
                 bbox_epsg31370=prepared["bbox_epsg31370"],
                 attribution=OrthophotoAcquisitionService.ATTRIBUTION,
-                limitation_message=OrthophotoAcquisitionService.LIMITATION,
+                limitation_message=product.limitation_message,
             ).model_dump(mode="json")
 
         raw_content, response_content_type = OrthophotoAcquisitionService._fetch(prepared["request_url"], resolved_settings, opener)
         geotiff_content = OrthophotoAcquisitionService._georeference_tiff(raw_content, prepared)
         acquired_at = datetime.now(UTC)
+        observed_at = product.observed_at or acquired_at
         dataset = DatasetService.import_raster_bytes(
             db,
             project_id=project_id,
             area_id=payload.area_id,
             filename=filename,
             content=geotiff_content,
-            source="Digitaal Vlaanderen OMWRGBMRVL WMS",
+            source=f"Digitaal Vlaanderen WMS {product.layer}",
             source_name=OrthophotoAcquisitionService.PROVIDER,
-            source_version=f"most_recent_at_{acquired_at.date().isoformat()}",
+            temporal_series_key=f"digitaal-vlaanderen:orthophoto:{prepared['spatial_hash'][:24]}",
+            observed_at=observed_at,
+            valid_from=product.valid_from or observed_at,
+            valid_to=product.valid_to,
+            temporal_granularity=product.temporal_granularity,
+            source_version=(
+                f"most_recent_at_{acquired_at.date().isoformat()}"
+                if product.key == "most_recent"
+                else product.key
+            ),
             content_type="image/tiff",
             source_metadata={
                 "provider": OrthophotoAcquisitionService.PROVIDER,
                 "service": "WMS",
                 "service_version": "1.3.0",
-                "layer": resolved_settings.orthophoto_wms_layer,
-                "catalog_url": OrthophotoAcquisitionService.CATALOG_URL,
+                "product_key": product.key,
+                "product_display_name": product.display_name,
+                "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,
+                "color_mode": product.color_mode,
+                "supports_detection": product.supports_detection,
+                "layer": product.layer,
+                "catalog_url": product.catalog_url,
                 "attribution": OrthophotoAcquisitionService.ATTRIBUTION,
                 "license_note": "Gebruik volgens het gebruiksrecht geografische webdiensten van Digitaal Vlaanderen.",
             },
@@ -290,6 +488,7 @@ class OrthophotoAcquisitionService:
                 "acquisition": "explicit_bounded_map_selection",
                 "acquired_at": acquired_at.isoformat(),
                 "request_hash": prepared["request_hash"],
+                "spatial_hash": prepared["spatial_hash"],
                 "request_url": prepared["request_url"],
                 "response_content_type": response_content_type,
                 "bbox_epsg4326": prepared["bbox_epsg4326"],
@@ -297,19 +496,70 @@ class OrthophotoAcquisitionService:
                 "width": prepared["width"],
                 "height": prepared["height"],
                 "resolution_m": resolved_settings.orthophoto_resolution_m,
-                "limitation_message": OrthophotoAcquisitionService.LIMITATION,
+                "limitation_message": product.limitation_message,
             },
         )
         return OrthophotoAcquisitionResult(
             output_dataset_id=dataset.id,
             reused=False,
             provider=OrthophotoAcquisitionService.PROVIDER,
-            layer=resolved_settings.orthophoto_wms_layer,
+            product_key=product.key,
+            display_name=product.display_name,
+            observation_label=product.observation_label,
+            temporal_granularity=product.temporal_granularity,
+            supports_detection=product.supports_detection,
+            layer=product.layer,
             width=prepared["width"],
             height=prepared["height"],
             resolution_m=resolved_settings.orthophoto_resolution_m,
             bbox_epsg4326=prepared["bbox_epsg4326"],
             bbox_epsg31370=prepared["bbox_epsg31370"],
             attribution=OrthophotoAcquisitionService.ATTRIBUTION,
-            limitation_message=OrthophotoAcquisitionService.LIMITATION,
+            limitation_message=product.limitation_message,
         ).model_dump(mode="json")
+
+    @staticmethod
+    def render_png(db, project_id: UUID, dataset_id: UUID, *, max_dimension: int = 1600) -> bytes:
+        dataset = db.get(Dataset, dataset_id)
+        if (
+            dataset is None
+            or dataset.project_id != project_id
+            or dataset.source_name != OrthophotoAcquisitionService.PROVIDER
+            or dataset.status != "ready"
+            or not dataset.storage_path
+            or not Path(dataset.storage_path).is_file()
+        ):
+            raise AppError(code="ORTHOPHOTO_NOT_FOUND", message="Orthophoto dataset not found", status_code=404)
+        try:
+            import numpy as np
+            import rasterio
+            from PIL import Image
+            from rasterio.enums import Resampling
+        except ImportError as exc:
+            raise AppError(code="RASTER_PROCESSING_UNAVAILABLE", message="Raster preview dependencies are unavailable", status_code=503) from exc
+
+        try:
+            with rasterio.open(dataset.storage_path) as source:
+                scale = min(1.0, max_dimension / max(source.width, source.height))
+                width = max(1, round(source.width * scale))
+                height = max(1, round(source.height * scale))
+                indexes = [1] if source.count == 1 else list(range(1, min(source.count, 3) + 1))
+                pixels = source.read(indexes, out_shape=(len(indexes), height, width), resampling=Resampling.bilinear)
+                if pixels.dtype != np.uint8:
+                    pixels = np.clip(pixels, 0, 255).astype(np.uint8)
+                if len(indexes) == 1:
+                    image = Image.fromarray(pixels[0])
+                else:
+                    image = Image.fromarray(np.moveaxis(pixels[:3], 0, 2))
+                output = io.BytesIO()
+                image.save(output, format="PNG", optimize=True)
+                return output.getvalue()
+        except AppError:
+            raise
+        except Exception as exc:
+            raise AppError(
+                code="ORTHOPHOTO_PREVIEW_FAILED",
+                message="The persisted orthophoto could not be rendered",
+                details={"reason": str(exc)},
+                status_code=500,
+            ) from exc

backend/app/services/vector_feature_service.py

@@ -23,6 +23,7 @@ FULL_AREA_CLIPPED_OPERATOR_TOOLS = {
     "provision_official_landuse_timeseries.py",
     "provision_regional_grb_buildings.py",
     "provision_regional_grb_context.py",
+    "provision_waterinfo_station_history.py",
 }
 
 
@@ -439,7 +440,7 @@ class VectorFeatureService:
             length_m = db.query(func.coalesce(func.sum(length_expression), 0.0)).filter(*metric_filter).scalar()
             divisor = 1_000.0 if unit == "km" else 1.0
             metric_value = float(length_m or 0.0) / divisor
-        elif method in {"sum", "area_weighted_sum"}:
+        elif method in {"sum", "mean", "area_weighted_sum"}:
             property_name = str(config.get("property") or "").strip()
             if not property_name:
                 raise AppError(
@@ -457,8 +458,9 @@ class VectorFeatureService:
                 )
                 coverage_ratio = intersection_area / func.nullif(source_area, 0.0)
                 value_expression = numeric_value * coverage_ratio
+            aggregate_function = func.avg if method == "mean" else func.sum
             aggregate_value = (
-                db.query(func.coalesce(func.sum(value_expression), 0.0))
+                db.query(func.coalesce(aggregate_function(value_expression), 0.0))
                 .filter(*selection_filter)
                 .filter(VectorFeature.properties_json.op("->>")(property_name).isnot(None))
                 .scalar()