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geointel/backend/app/services/flood_hazard_acquisition_service.py
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Add governed VMM flood hazard scenarios
2026-07-15 22:14:12 +02:00

552 lines
30 KiB
Python

from __future__ import annotations
import hashlib
import json
import math
import time
from dataclasses import dataclass
from datetime import UTC, datetime
from email.parser import BytesParser
from email.policy import default
from pathlib import Path
from typing import Any, Callable
from urllib.error import HTTPError, URLError
from urllib.parse import urlencode
from urllib.request import Request, urlopen
from uuid import UUID
from geoalchemy2.shape import to_shape
from pyproj import Transformer
from shapely.geometry import box, mapping
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.flood_hazard import FloodHazardAcquireRequest, FloodHazardAcquisitionResult, FloodHazardProductRead
from app.services.dataset_service import DatasetService
@dataclass(frozen=True)
class FloodHazardProduct:
key: str
display_name: str
mechanism: str
climate_context: str
probability_class: str
return_period_years: int
coverage_id: str
published_on: str
catalog_url: str
class FloodHazardAcquisitionService:
PROVIDER = "vmm_flood_hazard"
SOURCE_CRS = "EPSG:31370"
NATIVE_RESOLUTION_M = 2.0
SOURCE_VALUE_UNIT = "cm"
NORMALIZED_VALUE_UNIT = "m"
NODATA = -9999.0
SOURCE_VERSION = "VMM OGRK flood hazard maps"
ATTRIBUTION = "Bron: VMM"
LICENSE_NOTE = "Publieke toegang; gebruik en bronvermelding volgens de metadata van VMM/GDI-Vlaanderen."
WCS_TILE_SIDE_M = 10_000.0
WCS_REQUEST_INTERVAL_SECONDS = 1.0
WCS_RETRY_DELAY_SECONDS = 3.0
WCS_TRANSIENT_STATUS_CODES = frozenset({400, 429, 502, 503, 504})
SERVICE_CATALOG_URL = "https://www.vlaanderen.be/datavindplaats/catalogus/publieke-inspire-coverage-service-van-ogrk"
LIMITATION = (
"Gemodelleerde maximale overstromingsdiepte voor een vast kans- en klimaatscenario. "
"Dit is geen actuele waterstand, geen bathymetrie en geen permanente diepte of inhoud van een waterlichaam."
)
@staticmethod
def _products() -> dict[str, FloodHazardProduct]:
products: list[FloodHazardProduct] = []
probability = {
10: ("grote kans", "grote-kans"),
100: ("middelgrote kans", "middelgrote-kans"),
1000: ("kleine kans", "kleine-kans"),
}
for mechanism, code in (("pluviaal", "PLU"), ("fluviaal", "FLU")):
for climate_key, climate_code, climate_label, published_on in (
("current", "noCC", "huidig klimaat", "2021-08-31"),
("future_2050", "hCC", "klimaatprojectie 2050", "2021-08-31" if mechanism == "fluviaal" else "2019-12-22"),
):
for period, (probability_label, probability_slug) in probability.items():
climate_slug = (
"huidig-klimaat"
if climate_key == "current"
else "toekomstig-klimaat-met-klimaatprojectie-2050"
)
catalog_url = (
"https://www.vlaanderen.be/datavindplaats/catalogus/"
f"overstromingsgevaarkaart-waterdiepte-{mechanism}-{climate_slug}-{probability_slug}"
)
products.append(
FloodHazardProduct(
key=f"{mechanism}_{climate_key}_t{period}",
display_name=(
f"{mechanism.capitalize()} - {climate_label} - {probability_label} (T{period})"
),
mechanism=mechanism,
climate_context=climate_label,
probability_class=probability_label,
return_period_years=period,
coverage_id=(
f"Overstromingsgevaarkaarten-{code.replace('PLU', 'PLUVIAAL').replace('FLU', 'FLUVIAAL')}:"
f"waterdiepte_{code}_{climate_code}_T{period}"
),
published_on=published_on,
catalog_url=catalog_url,
)
)
return {product.key: product for product in products}
@staticmethod
def list_products() -> list[dict[str, Any]]:
return [
FloodHazardProductRead(
key=product.key,
display_name=product.display_name,
mechanism=product.mechanism,
climate_context=product.climate_context,
probability_class=product.probability_class,
return_period_years=product.return_period_years,
coverage_id=product.coverage_id,
native_resolution_m=FloodHazardAcquisitionService.NATIVE_RESOLUTION_M,
source_crs=FloodHazardAcquisitionService.SOURCE_CRS,
source_value_unit=FloodHazardAcquisitionService.SOURCE_VALUE_UNIT,
normalized_value_unit=FloodHazardAcquisitionService.NORMALIZED_VALUE_UNIT,
published_on=product.published_on,
catalog_url=product.catalog_url,
attribution=FloodHazardAcquisitionService.ATTRIBUTION,
limitation_message=FloodHazardAcquisitionService.LIMITATION,
).model_dump()
for product in FloodHazardAcquisitionService._products().values()
]
@staticmethod
def _product(product_key: str) -> FloodHazardProduct:
product = FloodHazardAcquisitionService._products().get(product_key.strip().lower())
if product is None:
raise AppError(
code="FLOOD_HAZARD_PRODUCT_NOT_SUPPORTED",
message="Select a governed VMM fluvial or pluvial flood-depth scenario",
details={"product_key": product_key},
status_code=422,
)
return product
@staticmethod
def _prepared_request(payload: FloodHazardAcquireRequest, settings: Settings) -> dict[str, Any]:
if not settings.flood_hazard_enabled:
raise AppError(code="FLOOD_HAZARD_NOT_CONFIGURED", message="VMM flood-hazard acquisition is disabled", status_code=503)
product = FloodHazardAcquisitionService._product(payload.product_key)
resolution_m = float(payload.resolution_m or settings.flood_hazard_resolution_m)
values = (payload.bbox.min_x, payload.bbox.min_y, payload.bbox.max_x, payload.bbox.max_y)
if not all(math.isfinite(value) for value in values) or payload.bbox.min_x >= payload.bbox.max_x or payload.bbox.min_y >= payload.bbox.max_y:
raise AppError(code="INVALID_BBOX", message="Flood-hazard selection must be a finite non-empty rectangle", status_code=400)
transformer = Transformer.from_crs("EPSG:4326", FloodHazardAcquisitionService.SOURCE_CRS, always_xy=True)
metric_bounds = transformer.transform_bounds(*values, densify_pts=21)
width_m = float(metric_bounds[2] - metric_bounds[0])
height_m = float(metric_bounds[3] - metric_bounds[1])
if width_m < settings.flood_hazard_min_side_m or height_m < settings.flood_hazard_min_side_m:
raise AppError(
code="FLOOD_HAZARD_SELECTION_TOO_SMALL",
message=f"Select an area of at least {settings.flood_hazard_min_side_m:g} by {settings.flood_hazard_min_side_m:g} metres",
status_code=422,
)
if width_m > settings.flood_hazard_max_side_m or height_m > settings.flood_hazard_max_side_m:
raise AppError(
code="FLOOD_HAZARD_SELECTION_TOO_LARGE",
message=f"Select an area no larger than {settings.flood_hazard_max_side_m:g} by {settings.flood_hazard_max_side_m:g} metres",
details={"width_m": width_m, "height_m": height_m},
status_code=422,
)
width = max(1, math.ceil(width_m / resolution_m))
height = max(1, math.ceil(height_m / resolution_m))
if width * height > settings.flood_hazard_max_pixels:
raise AppError(
code="FLOOD_HAZARD_SELECTION_TOO_LARGE",
message="Flood-hazard selection exceeds the configured raster cell limit",
details={"pixel_count": width * height, "max_pixels": settings.flood_hazard_max_pixels},
status_code=422,
)
bbox_4326 = [float(value) for value in values]
bbox_31370 = [float(value) for value in metric_bounds]
identity = {
"provider": FloodHazardAcquisitionService.PROVIDER,
"coverage_id": product.coverage_id,
"bbox_epsg4326": [round(value, 8) for value in bbox_4326],
"bbox_epsg31370": [round(value, 3) for value in bbox_31370],
"resolution_m": resolution_m,
"area_id": str(payload.area_id) if payload.area_id else None,
}
request_hash = hashlib.sha256(json.dumps(identity, sort_keys=True).encode()).hexdigest()
return {
**identity,
"product": product,
"request_hash": request_hash,
"bbox_epsg4326": bbox_4326,
"bbox_epsg31370": bbox_31370,
"width": width,
"height": height,
}
@staticmethod
def _wcs_request_url(settings: Settings, product: FloodHazardProduct, bounds: tuple[float, float, float, float], resolution_m: float) -> str:
crs = "urn:ogc:def:crs:EPSG::31370"
query = [
("SERVICE", "WCS"),
("VERSION", "1.1.0"),
("REQUEST", "GetCoverage"),
("IDENTIFIER", product.coverage_id),
("BOUNDINGBOX", f"{bounds[0]:.3f},{bounds[1]:.3f},{bounds[2]:.3f},{bounds[3]:.3f},{crs}"),
("FORMAT", "image/tiff"),
("GRIDBASECRS", crs),
("GRIDCS", "urn:ogc:def:cs:OGC:0.0:Grid2dSquareCS"),
("GRIDTYPE", "urn:ogc:def:method:WCS:1.1:2dSimpleGrid"),
("GRIDORIGIN", f"{bounds[0]:.3f},{bounds[3]:.3f}"),
("GRIDOFFSETS", f"{resolution_m:g},-{resolution_m:g}"),
]
return f"{settings.flood_hazard_wcs_url}?{urlencode(query)}"
@staticmethod
def _tile_bounds(prepared: dict[str, Any]) -> list[tuple[float, float, float, float]]:
min_x, min_y, max_x, max_y = prepared["bbox_epsg31370"]
tiles: list[tuple[float, float, float, float]] = []
y = min_y
while y < max_y:
tile_max_y = min(y + FloodHazardAcquisitionService.WCS_TILE_SIDE_M, max_y)
x = min_x
while x < max_x:
tile_max_x = min(x + FloodHazardAcquisitionService.WCS_TILE_SIDE_M, max_x)
tiles.append((x, y, tile_max_x, tile_max_y))
x = tile_max_x
y = tile_max_y
return tiles
@staticmethod
def _scope_geometry(db, project_id: UUID, area_id: UUID | None, bbox_epsg4326: list[float]):
if not db.get(Project, project_id):
raise AppError(code="PROJECT_NOT_FOUND", message="Project not found", status_code=404)
selection = box(*bbox_epsg4326)
if area_id is None:
return selection
area = db.get(Area, area_id)
if not area:
raise AppError(code="AREA_NOT_FOUND", message="Area not found", status_code=404)
if area.project_id != project_id:
raise AppError(code="INVALID_DATASET_SCOPE", message="Area does not belong to this project", status_code=400)
intersection = to_shape(area.geometry).intersection(selection)
if intersection.is_empty or intersection.area <= 0:
raise AppError(code="FLOOD_HAZARD_SELECTION_OUTSIDE_AREA", message="Selection does not overlap the selected work area", status_code=422)
return intersection
@staticmethod
def _fetch(request_url: str, settings: Settings, opener: Callable[..., Any] | None = None) -> tuple[bytes, str]:
request = Request(request_url, headers={"Accept": "*/*", "User-Agent": "GeoIntel/0.1 bounded-vmm-flood-hazard-acquisition"})
max_bytes = settings.flood_hazard_max_response_mb * 1024 * 1024
try:
with (opener or urlopen)(request, timeout=settings.flood_hazard_timeout_seconds) as response:
content_type = str(response.headers.get("Content-Type", ""))
content_length = response.headers.get("Content-Length")
if content_length and int(content_length) > max_bytes:
raise AppError(code="FLOOD_HAZARD_RESPONSE_TOO_LARGE", message="Official VMM response exceeds the configured size limit", status_code=502)
content = response.read(max_bytes + 1)
except AppError:
raise
except HTTPError as exc:
preview = exc.read(300).decode("utf-8", errors="replace")
raise AppError(
code="FLOOD_HAZARD_PROVIDER_UNAVAILABLE",
message="The official VMM WCS could not complete the bounded request",
details={"reason": str(exc), "provider_status_code": int(exc.code), "response_preview": preview},
status_code=502,
) from exc
except (URLError, TimeoutError, OSError) as exc:
raise AppError(
code="FLOOD_HAZARD_PROVIDER_UNAVAILABLE",
message="The official VMM WCS could not complete the bounded request",
details={"reason": str(exc)},
status_code=502,
) from exc
if len(content) > max_bytes:
raise AppError(code="FLOOD_HAZARD_RESPONSE_TOO_LARGE", message="Official VMM response exceeds the configured size limit", status_code=502)
return content, content_type
@staticmethod
def _extract_geotiff(content: bytes, content_type: str) -> bytes:
if content.startswith((b"II*\x00", b"MM\x00*")):
return content
if "multipart" not in content_type.lower():
raise AppError(
code="FLOOD_HAZARD_PROVIDER_INVALID_RESPONSE",
message="The official VMM service did not return a GeoTIFF coverage",
details={"content_type": content_type, "response_preview": content[:300].decode("utf-8", errors="replace")},
status_code=502,
)
message = BytesParser(policy=default).parsebytes(f"Content-Type: {content_type}\r\nMIME-Version: 1.0\r\n\r\n".encode() + content)
for part in message.walk():
payload = part.get_payload(decode=True) or b""
if part.get_content_type() == "image/tiff" and payload.startswith((b"II*\x00", b"MM\x00*")):
return payload
raise AppError(
code="FLOOD_HAZARD_PROVIDER_INVALID_RESPONSE",
message="The official VMM multipart response contains no valid GeoTIFF coverage",
status_code=502,
)
@staticmethod
def _mosaic_geotiffs(coverages: list[bytes], expected_resolution_m: float) -> bytes:
if len(coverages) == 1:
return coverages[0]
try:
from rasterio.io import MemoryFile
from rasterio.merge import merge
except ImportError as exc:
raise AppError(code="RASTER_PROCESSING_UNAVAILABLE", message="Rasterio is required to assemble VMM flood-hazard tiles", status_code=503) from exc
memories = [MemoryFile(content) for content in coverages]
sources = []
try:
sources = [memory.open() for memory in memories]
for source in sources:
if source.crs is None or source.crs.to_epsg() != 31370 or source.count != 1:
raise AppError(code="FLOOD_HAZARD_TILE_MISMATCH", message="VMM coverage tiles do not share the governed CRS and band layout", status_code=502)
if not all(math.isclose(abs(float(value)), expected_resolution_m, rel_tol=0.02, abs_tol=0.05) for value in source.res):
raise AppError(code="FLOOD_HAZARD_TILE_MISMATCH", message="VMM coverage tile resolution differs from the governed request", status_code=502)
mosaic, transform = merge(sources, res=(expected_resolution_m, expected_resolution_m), nodata=0.0, dtype="float32")
profile = sources[0].profile.copy()
profile.pop("blockxsize", None)
profile.pop("blockysize", None)
profile.update(driver="GTiff", width=mosaic.shape[2], height=mosaic.shape[1], count=1, dtype="float32", crs=FloodHazardAcquisitionService.SOURCE_CRS, transform=transform, nodata=0.0, compress="deflate", predictor=3)
with MemoryFile() as output_memory:
with output_memory.open(**profile) as output:
output.write(mosaic)
return output_memory.read()
except AppError:
raise
except Exception as exc:
raise AppError(code="FLOOD_HAZARD_TILE_MOSAIC_FAILED", message="VMM flood-hazard tiles could not be assembled", details={"reason": str(exc)}, status_code=502) from exc
finally:
for source in sources:
source.close()
for memory in memories:
memory.close()
@staticmethod
def _fetch_coverage(prepared: dict[str, Any], settings: Settings, opener: Callable[..., Any] | None = None) -> tuple[bytes, dict[str, Any]]:
product: FloodHazardProduct = prepared["product"]
request_urls = [
FloodHazardAcquisitionService._wcs_request_url(settings, product, bounds, prepared["resolution_m"])
for bounds in FloodHazardAcquisitionService._tile_bounds(prepared)
]
raw_hash = hashlib.sha256()
coverage_hash = hashlib.sha256()
content_types: list[str] = []
coverages: list[bytes] = []
for index, request_url in enumerate(request_urls):
if index > 0 and opener is None:
time.sleep(FloodHazardAcquisitionService.WCS_REQUEST_INTERVAL_SECONDS)
try:
raw_content, content_type = FloodHazardAcquisitionService._fetch(request_url, settings, opener)
except AppError as exc:
provider_status = (exc.details or {}).get("provider_status_code")
if opener is not None or provider_status not in FloodHazardAcquisitionService.WCS_TRANSIENT_STATUS_CODES:
raise
time.sleep(FloodHazardAcquisitionService.WCS_RETRY_DELAY_SECONDS)
raw_content, content_type = FloodHazardAcquisitionService._fetch(request_url, settings, opener)
coverage = FloodHazardAcquisitionService._extract_geotiff(raw_content, content_type)
raw_hash.update(len(raw_content).to_bytes(8, "big")); raw_hash.update(raw_content)
coverage_hash.update(len(coverage).to_bytes(8, "big")); coverage_hash.update(coverage)
content_types.append(content_type)
coverages.append(coverage)
return FloodHazardAcquisitionService._mosaic_geotiffs(coverages, prepared["resolution_m"]), {
"tile_count": len(request_urls),
"request_urls": request_urls,
"response_content_types": content_types,
"response_sha256": raw_hash.hexdigest(),
"coverage_sha256": coverage_hash.hexdigest(),
}
@staticmethod
def _normalize_raster(content: bytes, scope_geometry_4326, prepared: dict[str, Any]) -> tuple[bytes, dict[str, Any]]:
try:
import numpy as np
from rasterio.io import MemoryFile
from rasterio.mask import mask
except ImportError as exc:
raise AppError(code="RASTER_PROCESSING_UNAVAILABLE", message="Rasterio and numpy are required for flood-hazard validation", status_code=503) from exc
try:
with MemoryFile(content) as source_memory, source_memory.open() as source:
if source.crs is None or source.crs.to_epsg() != 31370:
raise AppError(code="FLOOD_HAZARD_INVALID_CRS", message="VMM flood-hazard coverage must use EPSG:31370", status_code=502)
if source.count != 1:
raise AppError(code="FLOOD_HAZARD_INVALID_BANDS", message="VMM flood-hazard coverage must contain one depth band", status_code=502)
resolution = max(abs(float(source.res[0])), abs(float(source.res[1])))
if not math.isclose(resolution, prepared["resolution_m"], rel_tol=0.02, abs_tol=0.05):
raise AppError(code="FLOOD_HAZARD_INVALID_RESOLUTION", message="VMM coverage resolution differs from the governed request", status_code=502)
transformer = Transformer.from_crs("EPSG:4326", FloodHazardAcquisitionService.SOURCE_CRS, always_xy=True)
scope_metric = shapely_transform(transformer.transform, scope_geometry_4326)
clipped, transform = mask(source, [mapping(scope_metric)], crop=True, filled=False, indexes=[1])
source_values = np.ma.asarray(clipped[0], dtype="float32")
raw_cm = np.asarray(source_values.filled(0.0), dtype="float32")
positive = (~np.ma.getmaskarray(source_values)) & np.isfinite(raw_cm) & (raw_cm > 0.0)
normalized_m = np.full(raw_cm.shape, FloodHazardAcquisitionService.NODATA, dtype="float32")
normalized_m[positive] = raw_cm[positive] / 100.0
valid_values = normalized_m[positive].astype("float64")
profile = source.profile.copy()
profile.pop("blockxsize", None); profile.pop("blockysize", None)
profile.update(driver="GTiff", width=normalized_m.shape[1], height=normalized_m.shape[0], count=1, dtype="float32", crs=FloodHazardAcquisitionService.SOURCE_CRS, transform=transform, nodata=FloodHazardAcquisitionService.NODATA, compress="deflate", predictor=3)
with MemoryFile() as output_memory:
with output_memory.open(**profile) as output:
output.write(normalized_m, 1)
normalized_content = output_memory.read()
return normalized_content, {
"width": int(normalized_m.shape[1]),
"height": int(normalized_m.shape[0]),
"inundated_pixel_count": int(positive.sum()),
"nodata_value": FloodHazardAcquisitionService.NODATA,
"resolution_m": resolution,
"minimum_depth_m": float(valid_values.min()) if valid_values.size else None,
"maximum_depth_m": float(valid_values.max()) if valid_values.size else None,
"source_value_unit": FloodHazardAcquisitionService.SOURCE_VALUE_UNIT,
"normalized_value_unit": FloodHazardAcquisitionService.NORMALIZED_VALUE_UNIT,
}
except AppError:
raise
except Exception as exc:
raise AppError(code="FLOOD_HAZARD_RASTER_INVALID", message="The official VMM response is not a valid georeferenced flood-depth raster", details={"reason": str(exc)}, status_code=502) from exc
@staticmethod
def _cached_dataset(db, project_id: UUID, filename: str) -> Dataset | None:
candidate = (
db.query(Dataset)
.filter(Dataset.project_id == project_id, Dataset.name == filename, Dataset.source_name == FloodHazardAcquisitionService.PROVIDER, Dataset.status == "ready")
.order_by(Dataset.imported_at.desc())
.first()
)
if candidate and candidate.storage_path and Path(candidate.storage_path).is_file():
return candidate
return None
@staticmethod
def acquire(db, project_id: UUID, payload: FloodHazardAcquireRequest, *, settings: Settings | None = None, opener: Callable[..., Any] | None = None) -> dict[str, Any]:
resolved_settings = settings or get_settings()
prepared = FloodHazardAcquisitionService._prepared_request(payload, resolved_settings)
product: FloodHazardProduct = prepared["product"]
scope_geometry = FloodHazardAcquisitionService._scope_geometry(db, project_id, payload.area_id, prepared["bbox_epsg4326"])
resolution_token = f"{prepared['resolution_m']:g}".replace(".", "p")
filename = f"vmm_flood_depth_{product.key}_{resolution_token}m_{prepared['request_hash'][:12]}.tif"
if not payload.force_refresh:
cached = FloodHazardAcquisitionService._cached_dataset(db, project_id, filename)
if cached is not None:
metadata = cached.source_metadata or {}
raster = cached.metadata_json or {}
return FloodHazardAcquisitionResult(
output_dataset_id=cached.id,
reused=True,
provider=FloodHazardAcquisitionService.PROVIDER,
product_key=product.key,
display_name=product.display_name,
mechanism=product.mechanism,
climate_context=product.climate_context,
probability_class=product.probability_class,
return_period_years=product.return_period_years,
coverage_id=product.coverage_id,
resolution_m=float(metadata.get("analysis_resolution_m", prepared["resolution_m"])),
width=int(raster.get("width", prepared["width"])),
height=int(raster.get("height", prepared["height"])),
inundated_pixel_count=int(metadata.get("inundated_pixel_count", 0)),
bbox_epsg4326=prepared["bbox_epsg4326"],
bbox_epsg31370=prepared["bbox_epsg31370"],
attribution=FloodHazardAcquisitionService.ATTRIBUTION,
limitation_message=FloodHazardAcquisitionService.LIMITATION,
).model_dump(mode="json")
content, transfer = FloodHazardAcquisitionService._fetch_coverage(prepared, resolved_settings, opener)
normalized, validation = FloodHazardAcquisitionService._normalize_raster(content, scope_geometry, prepared)
acquired_at = datetime.now(UTC)
dataset = DatasetService.import_raster_bytes(
db,
project_id=project_id,
area_id=payload.area_id,
filename=filename,
content=normalized,
source=f"VMM OGRK WCS {product.coverage_id}",
source_name=FloodHazardAcquisitionService.PROVIDER,
source_version=FloodHazardAcquisitionService.SOURCE_VERSION,
content_type="image/tiff",
source_metadata={
"provider": FloodHazardAcquisitionService.PROVIDER,
"service": "WCS",
"service_version": "1.1.0",
"product_key": product.key,
"product_display_name": product.display_name,
"mechanism": product.mechanism,
"climate_context": product.climate_context,
"probability_class": product.probability_class,
"return_period_years": product.return_period_years,
"coverage_id": product.coverage_id,
"native_resolution_m": FloodHazardAcquisitionService.NATIVE_RESOLUTION_M,
"analysis_resolution_m": validation["resolution_m"],
"source_crs": FloodHazardAcquisitionService.SOURCE_CRS,
"source_value_unit": FloodHazardAcquisitionService.SOURCE_VALUE_UNIT,
"normalized_value_unit": FloodHazardAcquisitionService.NORMALIZED_VALUE_UNIT,
"inundated_pixel_count": validation["inundated_pixel_count"],
"minimum_depth_m": validation["minimum_depth_m"],
"maximum_depth_m": validation["maximum_depth_m"],
"bbox_epsg4326": prepared["bbox_epsg4326"],
"bbox_epsg31370": prepared["bbox_epsg31370"],
"published_on": product.published_on,
"catalog_url": product.catalog_url,
"service_catalog_url": FloodHazardAcquisitionService.SERVICE_CATALOG_URL,
"attribution": FloodHazardAcquisitionService.ATTRIBUTION,
"license_note": FloodHazardAcquisitionService.LICENSE_NOTE,
"theme": "flood_hazard",
"layer_name": "modelled_flood_depth",
"coverage_scope": "municipality" if payload.area_id else "bounded_selection",
},
provenance_metadata={
"acquisition": "explicit_bounded_tiled_wcs_coverage",
"acquired_at": acquired_at.isoformat(),
"request_hash": prepared["request_hash"],
"tile_count": transfer["tile_count"],
"tile_request_urls": transfer["request_urls"],
"response_content_types": transfer["response_content_types"],
"response_sha256": transfer["response_sha256"],
"coverage_sha256": transfer["coverage_sha256"],
"normalized_sha256": hashlib.sha256(normalized).hexdigest(),
"bbox_epsg4326": prepared["bbox_epsg4326"],
"bbox_epsg31370": prepared["bbox_epsg31370"],
"requested_resolution_m": prepared["resolution_m"],
"clipped_to_area_id": str(payload.area_id) if payload.area_id else None,
"validation": validation,
"limitation_message": FloodHazardAcquisitionService.LIMITATION,
"bathymetry_available": False,
"permanent_water_depth_available": False,
"permanent_water_volume_available": False,
"concurrent_flood_volume_available": False,
},
)
return FloodHazardAcquisitionResult(
output_dataset_id=dataset.id,
reused=False,
provider=FloodHazardAcquisitionService.PROVIDER,
product_key=product.key,
display_name=product.display_name,
mechanism=product.mechanism,
climate_context=product.climate_context,
probability_class=product.probability_class,
return_period_years=product.return_period_years,
coverage_id=product.coverage_id,
resolution_m=validation["resolution_m"],
width=validation["width"],
height=validation["height"],
inundated_pixel_count=validation["inundated_pixel_count"],
bbox_epsg4326=prepared["bbox_epsg4326"],
bbox_epsg31370=prepared["bbox_epsg31370"],
attribution=FloodHazardAcquisitionService.ATTRIBUTION,
limitation_message=FloodHazardAcquisitionService.LIMITATION,
).model_dump(mode="json")