# API Contracts v1

This document freezes the first API shape. Codex may add implementation details but must not rename these routes without updating this file and the frontend API client.

## API principles

- Base path: `/api/v1`.
- JSON by default.
- GeoJSON accepted for geometries where possible.
- Long processing tasks return a job or analysis run record instead of blocking.
- Error responses use the shared `ApiError` schema.

## Shared schemas

### ApiError

```json
{
  "error": "string",
  "message": "human readable message",
  "details": {},
  "request_id": "optional string"
}
```

### GeoJsonGeometry

Any valid GeoJSON geometry object. V1 primarily expects `Polygon` and `MultiPolygon` for areas.

### BoundingBox

```json
{
  "min_x": 0.0,
  "min_y": 0.0,
  "max_x": 0.0,
  "max_y": 0.0,
  "crs": "EPSG:4326"
}
```

## Health

### GET `/health`

Returns service status.

```json
{
  "status": "ok",
  "service": "geointel-backend",
  "version": "0.1.0"
}
```

### GET `/api/v1/system/capabilities`

Returns enabled feature flags and tool availability.

```json
{
  "postgis": true,
  "rasterio": true,
  "geopandas": true,
  "yolo": false,
  "sam": false,
  "grb": "planned",
  "sentinel": "planned",
  "providers": [
    {
      "provider_name": "grb",
      "display_name": "GRB",
      "authority_level": "authoritative",
      "supported_layers": ["buildings", "roads", "parcels"],
      "supported_geometry_types": ["Polygon", "MultiPolygon", "LineString", "MultiLineString"],
      "supported_query_modes": ["area"],
      "fetch_signature": "POST /api/v1/external/grb/fetch",
      "configured": false,
      "status": "not_configured",
      "limitation_message": "GRB live WFS/download integration is not configured in Sprint 7B.",
      "attribution": "Digitaal Vlaanderen - Basiskaart Vlaanderen (GRB)",
      "license_note": "Use must follow Digitaal Vlaanderen open data and attribution terms.",
      "not_configured_reason": "Provider integration is not configured yet"
    }
  ]
}
```

## Projects

### GET `/api/v1/projects`

Returns all projects.

### POST `/api/v1/projects`

Request:

```json
{
  "name": "Geel building detection demo",
  "description": "Detect buildings and validate against GRB",
  "region": "Kempen"
}
```

Response: `ProjectRead`.

### GET `/api/v1/projects/{project_id}`

Returns one project with summary counts.

### PATCH `/api/v1/projects/{project_id}`

Updates name/description/region.

### DELETE `/api/v1/projects/{project_id}`

Soft-delete in V1 preferred. Hard-delete only if storage cleanup is also implemented.

## Areas

### GET `/api/v1/projects/{project_id}/areas`

Returns areas for a project. Area responses include persisted AOI geometry as
GeoJSON so the frontend can display the selected area in the map workbench.

```json
{
  "id": "uuid",
  "project_id": "uuid",
  "name": "Geel Centrum AOI",
  "original_crs": "EPSG:4326",
  "area_m2": 1234.5,
  "created_at": "timestamp",
  "geometry_type": null,
  "geometry": {
    "type": "MultiPolygon",
    "coordinates": []
  }
}
```

### POST `/api/v1/projects/{project_id}/areas`

Request:

```json
{
  "name": "Geel Centrum AOI",
  "geometry": {"type": "Polygon", "coordinates": []},
  "crs": "EPSG:4326"
}
```

Backend responsibilities:

- Validate geometry.
- Repair trivial polygon issues if safe.
- Store geometry in PostGIS.
- Calculate area in square meters using projected CRS.
- Store bbox.

### GET `/api/v1/projects/{project_id}/areas/{area_id}`

Returns one project area. The payload uses the same `AreaRead` shape as the
area list endpoint and includes persisted GeoJSON geometry for map display.

### PATCH `/api/v1/projects/{project_id}/areas/{area_id}`

Updates the area name and/or geometry. Geometry updates follow the same
validation, repair and metric-calculation rules as area creation.

## Datasets

### POST `/api/v1/projects/{project_id}/datasets/upload`

Multipart upload.

Fields:

- `file`: dataset file.
- `dataset_type`: `vector`, `geojson` (legacy), `raster`.
- `source`: free text, e.g. `user_upload`, `grb`, `osm`.
- `dataset_role`: `source`, `derived`, or `reference` (default `source`).
- `source_name`: optional source identity, e.g. `manual`, `grb`, `osm`; reference uploads default to `manual` when omitted.
- `reference_layer_name`: optional reference layer label, e.g. `buildings`; only retained for reference datasets.
- `area_id`: optional.

Response: `DatasetRead` with extracted metadata if supported.

Vector uploads remain stored as original files and are also persisted into `vector_features` as queryable PostGIS state.

### GET `/api/v1/projects/{project_id}/datasets/orthophoto/products`

Return the governed Digitaal Vlaanderen orthophoto product allowlist in the
canonical envelope. Every product reports its key, display/observation label,
temporal granularity, native resolution, colour mode, catalogue URL,
limitations and whether current configured-YOLO detection is allowed.

### POST `/api/v1/projects/{project_id}/datasets/orthophoto/acquire`

Explicitly acquire a bounded orthophoto selection from a governed official
Digitaal Vlaanderen WMS product. Arbitrary WMS URLs and layer names are not
accepted.

```json
{
  "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",
  "force_refresh": false
}
```

The canonical envelope contains a synchronous Job. Its `output_dataset_id`
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.

### GET `/api/v1/projects/{project_id}/datasets/dhmv/products`

Returns the fixed official DHMV II product registry in the canonical envelope.
The registry contains only `dtm_1m` (`DHMVII_DTM_1m`) and `dsm_1m`
(`DHMVII_DSM_1m`). Each item records native 1 m resolution, EPSG:31370, TAW,
the 2013-2015 acquisition period, attribution, catalogue and limitations.

### POST `/api/v1/projects/{project_id}/datasets/dhmv/acquire`

Runs a bounded WCS 2.0.1 `GetCoverage` request behind the existing synchronous
Job abstraction. Arbitrary coverage identifiers are rejected.

```json
{
  "bbox": {"min_x": 5.0, "min_y": 51.1, "max_x": 5.2, "max_y": 51.3, "crs": "EPSG:4326"},
  "area_id": "optional-project-area-uuid",
  "product_key": "dtm_1m",
  "resolution_m": 5.0,
  "force_refresh": false
}
```

The service extracts the GeoTIFF from the official multipart response, clips
to the exact persisted Area when supplied, validates EPSG:31370, one band,
resolution, nodata and valid cells, then persists through `DatasetService`.
The default 5 m file is an analysis copy of the retained 1 m source product;
both resolutions and all request/response/output checksums remain provenance.

### POST `/api/v1/projects/{project_id}/datasets/{dataset_id}/raster/terrain/select`

Accepts an EPSG:4326 rectangle and optional Area id. It reads only a governed,
ready DHMV Dataset and returns a canonical envelope with valid-cell coverage,
mean/min/max/P10/P90 height in `m TAW`, relief in metres and mean/P90/max slope
in degrees. Area geometry is an exact mask, not only a bounding box.

The response always lists `water_depth_m` and `water_volume_m3` under
`unsupported_metrics`. Drainage is not calculated by this endpoint.

### POST `/api/v1/projects/{project_id}/datasets/raster/terrain/select`

Runs the same exact terrain calculation over every persisted municipal DHMV
partition intersecting one bounded EPSG:4326 rectangle. The request adds the
governed `product_key` (`dtm_1m` or `dsm_1m`) to the ordinary selection bbox
and optional Area id. The backend mosaics only the intersecting windows in
EPSG:31370, enforces the existing 12-million-cell limit and calculates global
cell statistics. The canonical response includes `dataset_ids` and
`partition_count`; percentiles are calculated from the combined cells and are
not averages of municipal summaries.

### GET `/api/v1/projects/{project_id}/datasets/{dataset_id}/raster/terrain/image`

Returns a browser-safe PNG colour relief for the persisted governed DHMV
Dataset. This binary MapLibre source never accepts an arbitrary file path.

Safety contract:

- every side must measure between 128 m and 1,024 m in EPSG:31370;
- an optional `area_id` must belong to the project and cover at least 99% of
  the rectangle;
- defaults are 1 m/pixel, a 32 MiB response limit and 24-hour exact-request
  reuse;
- WMS bytes are georeferenced to EPSG:31370 and persisted only through
  `DatasetService`; no fetch runs on startup;
- only `most_recent` can enter the current configured-YOLO plus GRB-QA path;
  historical products are visual evidence and are never validated against the
  current GRB state;
- product periods such as `1979_1990` remain explicitly multi-year and are not
  presented as exact annual observations.

### GET `/api/v1/projects/{project_id}/datasets/flood-hazard/products`

Returns the fixed twelve-product VMM flood-depth registry in the canonical
envelope. Products combine `pluviaal`/`fluviaal`, current climate/climate
projection 2050 and T10/T100/T1000. Each product keeps the official WCS
coverage id, probability class, source unit centimetres, normalized unit
metres, publication metadata, attribution and limitation.

### POST `/api/v1/projects/{project_id}/datasets/flood-hazard/acquire`

Acquires one bounded official VMM OGRK WCS 1.1 coverage behind the synchronous
Job abstraction. Arbitrary coverage identifiers and service URLs are rejected.

```json
{
  "bbox": {"min_x": 5.0, "min_y": 51.1, "max_x": 5.2, "max_y": 51.3, "crs": "EPSG:4326"},
  "area_id": "optional-project-area-uuid",
  "product_key": "pluviaal_current_t100",
  "resolution_m": 5.0,
  "force_refresh": false
}
```

The service tiles municipality-size requests, validates EPSG:31370 and one
Float32 depth band, converts positive source centimetres to metres, clips to
the exact persisted Area and stores an ordinary raster Dataset and
DatasetVersion. Zero/null source cells become transparent nodata. The scenario
is not a temporal observation and receives no fabricated `observed_at` value.

### POST `/api/v1/projects/{project_id}/datasets/{dataset_id}/raster/flood-hazard/select`

Returns mapped positive-depth area in hectares, share of the selection, mean,
P90 and maximum modeled local depth and `modelled_max_depth_area_integral_m3`.
Every result identifies mechanism, climate context, probability class and
return period. The integral sums local modeled maximum depth times cell area;
it is explicitly not concurrent flood storage, permanent waterbody content,
current water level or bathymetry. These unsupported metrics remain listed in
the response.

### POST `/api/v1/projects/{project_id}/datasets/raster/flood-hazard/select`

Runs exact bounded analysis over the persisted municipal VMM partitions for
one governed `product_key`. Only partitions intersecting the selection are
opened, the normalized metre grids are combined at their common 5 m analysis
resolution and the global area/depth metrics are calculated from the combined
cells. The canonical response includes every contributing Dataset id in
`dataset_ids` plus `partition_count`. The existing flood-volume and bathymetry
prohibitions are unchanged.

### GET `/api/v1/projects/{project_id}/datasets/{dataset_id}/raster/flood-hazard/image`

Returns a constrained transparent PNG for a persisted governed VMM flood-depth
Dataset. It never accepts an arbitrary path or coverage id and is used by the
existing MapLibre image-overlay path.

### GET `/api/v1/projects/{project_id}/datasets/thematic-raster/products`

Returns the fixed MercatorNet registry for `space_occupation_2025`,
`open_space_2022`, `population_density_2019`, `node_value_2022` and
`service_level_2022`. Every item includes the governed WCS coverage id, native
resolution, source unit, observation year, legend, attribution and limitation.

### POST `/api/v1/projects/{project_id}/datasets/thematic-raster/acquire`

Acquires one allowlisted official coverage behind the synchronous Job
abstraction. The request accepts only an EPSG:4326 bbox, optional project Area,
one registry product key and an explicit refresh flag:

```json
{
  "bbox": {"min_x": 5.03, "min_y": 51.15, "max_x": 5.25, "max_y": 51.33, "crs": "EPSG:4326"},
  "area_id": "optional-project-area-uuid",
  "product_key": "population_density_2019",
  "force_refresh": false
}
```

The backend uses native 10 m or 100 m resolution, splits requests into bounded
WCS 1.0 tiles, validates EPSG:31370 and documented source values, masks the
exact Area and persists an ordinary raster Dataset and DatasetVersion. It does
not accept arbitrary URLs, coverage ids, resolutions or expressions.

### POST `/api/v1/projects/{project_id}/datasets/{dataset_id}/raster/thematic/select`

Returns source-correct metrics for a bbox and optional exact Area mask:

- occupied/open hectares, share and valid raster area for binary products;
- estimated inhabitants plus mean/P90 inhabitants per hectare for the 2019
  population raster;
- mean, P10, median and P90 source score for node value and service level.

The response names estimate status, aggregation method, source unit,
observation year, attribution, unsupported metrics and product limitation.
Current register population, live public-transport availability and causal
interpretations are not produced.

### GET `/api/v1/projects/{project_id}/datasets/{dataset_id}/raster/thematic/image`

Returns a constrained transparent PNG generated from the persisted governed
raster. It accepts neither an arbitrary file path nor a provider URL and feeds
the existing MapLibre image-overlay path.

### GET `/api/v1/projects/{project_id}/datasets`

List datasets.

### GET `/api/v1/projects/{project_id}/datasets/source-freshness`

Returns one read-only, canonical source-governance report for all persisted
project datasets. Datasets are grouped by `source_name` (falling back to
`source`) and classified as a rolling snapshot, annual release, fixed edition,
scenario, historical archive or local artifact.

Each source item reports dataset/version counts, latest import and observation
evidence, latest source version, next review date where meaningful, historical
series availability and local integrity counts for missing DatasetVersions,
checksum mismatches, missing storage files and size mismatches. Status is one
of `current`, `due`, `review_required` or `local`.

This endpoint never contacts an external provider, downloads data, mutates a
Dataset or silently refreshes a publication. Fixed editions and scenarios are
not marked stale merely because their source date is old. Unknown sources are
`review_required` until an explicit publication policy is defined.

### GET `/api/v1/projects/{project_id}/datasets/source-catalog-probes`

Performs an explicit, read-only release probe for the allowlisted GRB WFS,
most-recent orthophoto WMS, Statbel population DCAT catalog and ALZ
agricultural-use parcel publication page.
For OGC services, the endpoint reads bounded `GetCapabilities` responses,
confirms the expected layers and follows only HTTPS ISO 19139 `GetRecordById`
links on `metadata.vlaanderen.be`. For Statbel, it reads the bounded official
RDF/Turtle catalog and selects the latest uniquely identified Dutch
`Bevolking per statistische sector` release. It requires the official landing
page, CC BY 4.0 license and allowlisted distribution identities but never
requests a ZIP or XLSX file. For ALZ, it reads only the bounded official
HTML release page and accepts only exact
`www.landbouwvlaanderen.be/bestanden/gis/agpa_<year>_<date>_public.zip` link
identities. It does not request those archives. Query parameter `refresh=true`
bypasses the short in-memory response cache.

Each provider item returns service reachability, matched/missing layers, the
official metadata identifier, title, edition, publication/metadata dates,
local `source_version` and one comparison status: `same`, `different`,
`not_comparable`, `no_local_data` or `unavailable`. Provider status is
`available`, `degraded`, `unavailable` or `disabled`. A difference means only
that an operator should review provenance; it is not an update instruction.

ALZ comparisons use only the latest definitive third snapshot, normalized as
`<campaign>-v3`. A newer first or second snapshot is reported in the item title
and message as provisional but cannot mark a local definitive historical
edition as outdated. `service_type=HTML` uses `definitive_archive` and
`current_snapshot` as evidence markers in the existing expected/matched/missing
arrays; no parallel response shape is introduced.

Statbel comparisons use the four-digit population reference year. The 2025
release requires the new REDEGEO TXT/ZIP variant; its old-sector-layout file is
reported only as transition evidence. `service_type=DCAT` uses
`population_txt_current`, `landing_page` and `cc_by_4_0` as evidence markers.
A newer statistical-sector geometry edition is not interpreted as a newer
population release.

The endpoint accepts no arbitrary URL, feature query, area or layer. It does
not fetch vector features, raster pixels or models, create jobs/datasets, write
to PostGIS or trigger an import. The normal `source-freshness` endpoint remains
local-only and never invokes this probe implicitly.

### GET `/api/v1/projects/{project_id}/datasets/grb-refresh-plan`

Builds a read-only refresh decision for the governed
`kempen-transport-region` GRB snapshot series. Query parameter
`refresh_catalog=true` explicitly bypasses the catalog cache. The response
maps the official dated edition to `buildings`, `roads`, `water` and `parcels`
and reports each latest local Dataset, source version, observation date,
feature count, artifact size and refresh state.

Layer state is `current`, `update_available`, `not_loaded`, `review_required`
or `remote_unavailable`. The summary reports how many new immutable Datasets
would be created and how many existing snapshots remain retained. The endpoint
does not fetch GRB features, stage files, create a Job, write to PostGIS or
start an operator process. Exact remote deltas remain unavailable until every
municipality partition has been staged and validated.

Regional execution uses `scripts/manage_grb_refresh.py` outside the request
cycle. `stage` requires the exact official ISO edition, invokes the existing
regional GRB operators with `--fetch-only`, validates all artifact/partition
checksums and emits a SHA-256-bound plan. `apply` requires that exact plan hash,
revalidates every staged byte and delegates persistence to DatasetService and
VectorFeatureService. It creates new temporal snapshots and never deletes or
overwrites an older Dataset.

### GET `/api/v1/projects/{project_id}/datasets/{dataset_id}`

Return metadata.

### POST `/api/v1/projects/{project_id}/datasets/{dataset_id}/metadata/refresh`

Re-extract metadata.

### GET `/api/v1/projects/{project_id}/datasets/{dataset_id}/vector/inspect`

Return a wrapped vector inspection payload with metadata, storage summary and feature summary.

### GET `/api/v1/projects/{project_id}/datasets/{dataset_id}/vector/summary`

Return vector summary data only.

### GET `/api/v1/projects/{project_id}/datasets/{dataset_id}/raster/metadata`

Return raster metadata profile for supported raster uploads.

If raster processing is unavailable:

```text
code: RASTER_PROCESSING_UNAVAILABLE
message: Raster processing unavailable. Install rasterio and GDAL-compatible drivers to enable raster metadata extraction.
```

### GET `/api/v1/projects/{project_id}/datasets/{dataset_id}/raster/inspect`

Return raster inspect wrapper payload.

### GET `/api/v1/projects/{project_id}/datasets/{dataset_id}/raster/stats`

Return raster band statistics payload.

If raster processing dependencies are unavailable:

- code: `RASTER_PROCESSING_UNAVAILABLE`
- message: dependency-specific unavailable message.

### GET `/api/v1/projects/{project_id}/datasets/{dataset_id}/raster/preview`

Preview readiness for raster layers.

If preview dependencies are unavailable:

- code: `RASTER_PROCESSING_UNAVAILABLE`
- message: `Raster preview unavailable...`

### GET `/api/v1/projects/{project_id}/datasets/{dataset_id}/raster/image`

Return a persisted orthophoto Dataset as a bounded browser-safe PNG. This is an
explicit binary non-envelope endpoint used by the MapLibre image source. It
accepts only ready datasets from the governed orthophoto provider and never
reads arbitrary filesystem paths.

### POST `/api/v1/projects/{project_id}/datasets/{dataset_id}/raster/clip`

Clip raster by selected area. Returns a `202`-style accepted job payload through the job wrapper (`jobs` create/read flow).

If raster processing dependencies are unavailable:

- code: `RASTER_PROCESSING_UNAVAILABLE`
- message: `Raster processing unavailable. Install rasterio and GDAL-compatible drivers to enable raster processing operations.`

### POST `/api/v1/projects/{project_id}/datasets/{dataset_id}/raster/reproject`

Reproject raster dataset to another CRS.

Input:

- `target_crs` (default: `EPSG:31370`)
- `resampling` (`nearest`, `bilinear`, `cubic`; default `nearest`)
- `output_name`

Returns a job payload with derived dataset id in `result.output_dataset_id`.

Failure modes:

- code: `INVALID_PARAMETERS` for bad CRS or resampling
- code: `INVALID_DATASET_CRS` when source raster CRS is missing
- code: `RASTER_PROCESSING_UNAVAILABLE` when rasterio is unavailable

### POST `/api/v1/projects/{project_id}/datasets/{dataset_id}/raster/indices/ndvi`

Compute NDVI from raster band pairs.

Input:

- `nir_band` (positive integer, 1-based)
- `red_band` (positive integer, 1-based)
- `output_name` (optional)

Returns a job payload with derived dataset id in `result.output_dataset_id`.

Failure modes:

- code: `INVALID_PARAMETERS` for non-positive/non-integer band indices
- code: `INVALID_PARAMETERS` for band index outside source band count
- code: `INVALID_DATASET_TYPE` when source is not raster
- code: `RASTER_PROCESSING_UNAVAILABLE` when rasterio or numpy is unavailable

### POST `/api/v1/projects/{project_id}/datasets/{dataset_id}/raster/indices/ndwi`

Compute NDWI from raster band pairs.

Input:

- `nir_band` (positive integer, 1-based)
- `green_band` (positive integer, 1-based)
- `output_name` (optional)

Returns a job payload with derived dataset id in `result.output_dataset_id`.

Failure modes:

- code: `INVALID_PARAMETERS` for non-positive/non-integer band indices
- code: `INVALID_PARAMETERS` for band index outside source band count
- code: `INVALID_DATASET_TYPE` when source is not raster
- code: `RASTER_PROCESSING_UNAVAILABLE` when rasterio or numpy is unavailable

### POST `/api/v1/projects/{project_id}/datasets/{dataset_id}/raster/indices/ndbi`

Compute NDBI from raster band pairs.

Input:

- `nir_band` (positive integer, 1-based)
- `swir_band` (positive integer, 1-based)
- `output_name` (optional)

Returns a job payload with derived dataset id in `result.output_dataset_id`.

Failure modes:

- code: `INVALID_PARAMETERS` for non-positive/non-integer band indices
- code: `INVALID_PARAMETERS` for band index outside source band count
- code: `INVALID_DATASET_TYPE` when source is not raster
- code: `RASTER_PROCESSING_UNAVAILABLE` when rasterio or numpy is unavailable

### POST `/api/v1/projects/{project_id}/datasets/{dataset_id}/raster/tile`

Generate raster tiles and a manifest for downstream processing. Returns a job payload with `tile_set_id` and manifest metadata.

If raster processing dependencies are unavailable:

- code: `RASTER_PROCESSING_UNAVAILABLE`
- message: `Raster processing unavailable. Install rasterio and GDAL-compatible drivers to enable raster processing operations.`

### POST `/api/v1/projects/{project_id}/datasets/{dataset_id}/vector/clip`

Clip vector dataset to selected area.

### POST `/api/v1/projects/{project_id}/datasets/{dataset_id}/vector/buffer`

Apply buffer distance to vector features.

### POST `/api/v1/projects/{project_id}/datasets/{dataset_id}/vector/intersect`

Intersect source vector dataset with another vector dataset.

### GET `/api/v1/projects/{project_id}/datasets/{dataset_id}/vector/stats`

Return vector stats (feature counts and geometry summary).

### GET `/api/v1/projects/{project_id}/datasets/{dataset_id}/vector/bbox`

Return vector bounds and feature count.

### POST `/api/v1/projects/{project_id}/datasets/{dataset_id}/vector/select`

Read-only spatial selection over persisted `vector_features`.

Request:

```json
{
  "bbox": {
    "min_x": 5.0,
    "min_y": 51.0,
    "max_x": 5.1,
    "max_y": 51.1,
    "crs": "EPSG:4326"
  },
  "area_id": "optional persisted area UUID",
  "limit": 250
}
```

Response:

```json
{
  "data": {
    "selection_bbox": {
      "min_x": 5.0,
      "min_y": 51.0,
      "max_x": 5.1,
      "max_y": 51.1,
      "crs": "EPSG:4326"
    },
    "selection_area_id": "present when area_id was requested",
    "feature_count": 2,
    "total_feature_count": 2,
    "limit": 250,
    "truncated": false,
    "geojson": {
      "type": "FeatureCollection",
      "features": []
    },
    "summary": {
      "metric_label": "Wateroppervlakte",
      "metric_value": 5.25,
      "metric_unit": "ha",
      "aggregation_method": "intersection_area",
      "primary_metric_key": "water_area",
      "feature_count": 23,
      "is_estimate": false,
      "warning": "Watervolume is niet berekenbaar zonder betrouwbare diepte- of bathymetrische gegevens.",
      "metrics": [
        {
          "metric_key": "water_area",
          "metric_label": "Wateroppervlakte",
          "metric_value": 5.25,
          "metric_unit": "ha",
          "aggregation_method": "intersection_area",
          "is_estimate": false
        },
        {
          "metric_key": "watercourse_length",
          "metric_label": "Lengte waterlopen",
          "metric_value": 12.75,
          "metric_unit": "km",
          "aggregation_method": "intersection_length",
          "is_estimate": false
        },
        {
          "metric_key": "feature_count",
          "metric_label": "Waterobjecten",
          "metric_value": 23,
          "metric_unit": "objecten",
          "aggregation_method": "feature_count",
          "is_estimate": false
        }
      ]
    }
  }
}
```

Rules:

- Only vector/GeoJSON datasets are supported.
- Coordinates are EPSG:4326 longitude/latitude.
- `area_id` is optional and must belong to the route project. When present, the bbox remains the bounded preview extent but PostGIS filtering and configured aggregations use the persisted Area geometry exactly. This prevents a municipal or regional full-work-area query from counting objects in the surrounding bbox corners.
- Results are generated from persisted PostGIS `vector_features`, not from client-side map data.
- `feature_count` is the number of GeoJSON features returned in the bounded preview. `total_feature_count` is the exact number of persisted rows intersecting the requested bbox or persisted Area geometry.
- `summary` keeps one backwards-compatible primary metric and exposes all relevant measurements in `metrics`. Known themes use metric PostGIS calculations: building/forest/water/parcel surfaces in hectares, road and watercourse lengths in kilometres, population in inhabitants and intersecting feature counts as supporting evidence.
- Governed datasets may declare additional `source_metadata.selection_metrics`.
  Each metric may constrain one persisted feature-property to an explicit value
  allowlist before the same PostGIS aggregation runs. The BWK/Natura 2000
  dataset uses this only for official `EVAL` classes; it does not collapse mixed
  classes into a made-up score.
- Area and length calculations transform geometry to Belgian Lambert 72 (`EPSG:31370`); they are never calculated in geographic degrees.
- Water volume is not inferred from 2D GRB geometry. It remains unavailable until a source provides reliable depth or bathymetry with compatible spatial coverage and provenance.
- The response is capped by `limit` and returns `truncated=true` when `total_feature_count` exceeds the returned preview.
- `limit` is bounded to `1..1000`. Municipality-scale clients must page spatially by viewport instead of requesting an unbounded municipality FeatureCollection.
- The Map workspace uses this existing endpoint for vector datasets above 5,000 features. It starts delivery at zoom level 14, debounces `moveend` requests and explicitly reports `truncated=true` as a request to zoom further in. This is a client delivery policy, not a second API or persistence path.

### POST `/api/v1/projects/{project_id}/datasets/{dataset_id}/vector/select/derive`

Persists a bbox selection as a new derived vector dataset and indexes the
selected output into `vector_features`.

Request:

```json
{
  "bbox": {
    "min_x": 5.0,
    "min_y": 51.0,
    "max_x": 5.1,
    "max_y": 51.1,
    "crs": "EPSG:4326"
  },
  "limit": 250,
  "output_name": "selected-buildings"
}
```

Response: `DatasetRead` in the canonical API envelope.

Rules:

- Only vector/GeoJSON datasets are supported.
- Coordinates are EPSG:4326 longitude/latitude.
- The new dataset uses `dataset_role="derived"`, `source="operation:selection"`,
  `source_name="map_selection"` and `derived_from_dataset_id` pointing to the
  source dataset.
- The persisted GeoJSON properties retain source provenance as
  `source_dataset_id` and `source_vector_feature_id`.
- Empty selections return `VECTOR_OPERATION_EMPTY_RESULT` and do not create a dataset.

### GET `/api/v1/projects/{project_id}/datasets/{dataset_id}/content`

Returns stored vector dataset content through the canonical API envelope.
Vector content is returned as GeoJSON/JSON payload data. Raster content is not
served through this endpoint.

## Jobs

### POST `/api/v1/projects/{project_id}/jobs`

Create a job.

### GET `/api/v1/projects/{project_id}/jobs`

List jobs.

### GET `/api/v1/projects/{project_id}/jobs/{job_id}`

Read job detail.

### GET `/api/v1/projects/{project_id}/jobs/{job_id}/status`

Read simplified job status payload.

## Provider registry

### GET `/api/v1/external/providers`

Returns all configured provider capability descriptors.

### GET `/api/v1/external/providers/capabilities`

Compatibility alias for listing provider capability descriptors.

### GET `/api/v1/external/providers/{provider_name}`

Returns one provider capability descriptor.

### GET `/api/v1/external/providers/{provider_name}/layers`

Returns the supported provider layers.

### GET `/api/v1/external/providers/{provider_name}/status`

Returns configured/status/limitation fields.

### POST `/api/v1/external/providers/{provider_name}/import`

Defines the future provider import contract. Sprint 7B does not perform live imports or write datasets.

Request:

```json
{
  "project_id": "uuid-or-local-id",
  "area_id": "optional uuid-or-local-id",
  "layers": ["buildings"],
  "dataset_role": "optional source|reference"
}
```

GRB/OSM response:

```json
{
  "provider_name": "grb",
  "status": "not_configured",
  "message": "No live GRB import is configured in Sprint 7B.",
  "requested_layers": ["buildings"],
  "dataset_id": null,
  "dataset_role": "reference",
  "source_name": "grb"
}
```

Manual and fixture providers point callers to existing upload/fixture flows. No provider writes directly to `vector_features`; all future provider output must flow through `DatasetService` and `VectorFeatureService`.

## External data fetchers

### POST `/api/v1/external/osm/fetch`

Request:

```json
{
  "project_id": "uuid",
  "area_id": "uuid",
  "layers": ["buildings", "roads", "water", "green"]
}
```

### POST `/api/v1/external/grb/fetch`

Request:

```json
{
  "project_id": "uuid",
  "area_id": "uuid",
  "layers": ["buildings"]
}
```

V1 may initially implement this as a service interface with a clear `not_configured` response until the exact WFS endpoint is wired.

Sprint 7B provider contract responses expose capabilities only. Providers must report:

```json
{
  "provider_name": "osm",
  "display_name": "OpenStreetMap",
  "authority_level": "contextual",
  "supported_layers": ["buildings", "roads", "water", "landuse"],
  "supported_geometry_types": ["Polygon", "MultiPolygon", "LineString", "MultiLineString"],
  "supported_query_modes": ["area"],
  "configured": false,
  "status": "not_configured",
  "limitation_message": "OSM live Overpass/download integration is not configured in Sprint 7B.",
  "attribution": "OpenStreetMap contributors",
  "license_note": "OpenStreetMap data is available under ODbL; attribution is required."
}
```

No GRB WFS, OSM Overpass or provider downloads are implemented in Sprint 7B.

## Demo workflow

### POST `/api/v1/demo/workflow`

Seeds an explicit offline demo workflow from local fixture files. This endpoint
does not fetch live GRB/OSM data and does not run AI inference. It creates or
returns:

- one demo project
- one demo AOI
- one fixture reference building dataset
- one fixture candidate/predicted building dataset
- one persisted QA/QC result with metric rows

The endpoint is idempotent for the named demo project.

Response:

```json
{
  "project_id": "uuid",
  "area_id": "uuid",
  "reference_dataset_id": "uuid",
  "candidate_dataset_id": "uuid",
  "quality_check_id": "uuid",
  "metric_count": 6,
  "status": "ready",
  "message": "Demo workflow seeded from explicit local fixtures.",
  "created": true
}
```

## Analysis

## Detection Lab

Sprint 8 implements Detection Lab foundation only. YOLO/PyTorch real inference is not enabled, no model is downloaded, and fixture detections require explicit fixture mode.

### Guided browser orchestration

The current frontend offers one guided building-analysis action, but does not add a parallel backend workflow endpoint. It deliberately composes the canonical contracts in this order:

1. optional explicit `POST /api/v1/projects/{project_id}/datasets/upload` for a georeferenced GeoTIFF;
2. `POST /api/v1/projects/{project_id}/datasets/{dataset_id}/raster/tile` with 512 px tiles and 64 px overlap;
3. `GET /api/v1/detection/yolo/preflight` with the returned manifest and selected local model asset;
4. `POST /api/v1/detection/run` only after successful preflight;
5. persisted run, Detection list and Detection GeoJSON reads;
6. optional persisted reference QA through the existing detection QA endpoint.

The strict `POST /api/v1/detection/run` contract still requires `tile_manifest_path` for configured YOLO. The frontend does not create fake tiles, bypass tile limits, fetch external imagery or download model weights.

### GET `/api/v1/detection/models`

Returns object-detection model capability descriptors.

```json
{
  "models": [
    {
      "model_id": "yolo-placeholder",
      "display_name": "YOLO detector placeholder",
      "framework": "ultralytics/pytorch",
      "task_type": "object_detection",
      "supported_classes": ["building", "road", "water", "landuse"],
      "configured": false,
      "status": "not_configured",
      "limitation_message": "YOLO/PyTorch inference is not configured in Sprint 8; no model is downloaded or executed.",
      "version": null
    },
    {
      "model_id": "yolo-configured",
      "display_name": "Configured YOLO detector",
      "framework": "ultralytics/pytorch",
      "task_type": "object_detection",
      "supported_classes": ["building", "road", "water", "landuse"],
      "configured": false,
      "status": "not_configured",
      "limitation_message": "YOLO is disabled. Set YOLO_ENABLED=true and YOLO_MODEL_PATH to a local model file to enable inference.",
      "version": null
    }
  ]
}
```

### GET `/api/v1/detection/model-assets`

Returns local runtime model files discovered in the configured model directory.
This is a read-only catalog. GeoIntel never downloads, creates, mutates or
deletes model weights from this endpoint.

The backend scans `YOLO_MODELS_DIR` (default `/app/models`) and reports
supported local model files such as `.pt`, `.onnx` and `.engine`. The active
model is the file matching `YOLO_MODEL_PATH`.

Response data:

```json
{
  "items": [
    {
      "model_asset_id": "building-detector-pt",
      "filename": "building-detector.pt",
      "display_name": "building-detector",
      "model_path": "/app/models/building-detector.pt",
      "suffix": ".pt",
      "framework": "ultralytics/pytorch",
      "task_type": "object_detection",
      "size_bytes": 123456,
      "sha256": "sha256hex",
      "active": true,
      "status": "available",
      "limitation_message": "Local runtime model asset. GeoIntel will not download or mutate model weights.",
      "will_download_models": false
    }
  ],
  "total": 1,
  "model_directory": "/app/models"
}
```

### GET `/api/v1/detection/yolo/preflight`

Returns a canonical envelope with read-only configured-YOLO runtime preflight
state. Optional query parameters:

- `tile_manifest_path`: existing raster tile manifest path to validate.
- `model_asset_id`: optional local model asset ID from
  `GET /api/v1/detection/model-assets`; when supplied, preflight validates that
  asset path instead of the default `YOLO_MODEL_PATH`.
- `check_model_load`: default `false`; when `true`, explicitly loads only the
  configured local model file for compatibility smoke. It never downloads
  weights and never runs inference.

Response data:

```json
{
  "model_id": "yolo-configured",
  "model_asset_id": null,
  "model_path": null,
  "tile_manifest_path": null,
  "status": "not_configured",
  "message": "YOLO_MODEL_PATH is not set. GeoIntel will not download model weights automatically.",
  "checks": {
    "enabled": true,
    "dependencies_available": true,
    "model_path_set": false,
    "model_file_exists": null,
    "model_load_requested": false,
    "model_load_ok": null,
    "manifest_path_set": null,
    "manifest_valid": null,
    "tile_paths_exist": null,
    "tile_limit_ok": null
  },
  "runtime": {
    "dependencies_assumed": false,
    "model_directory": null,
    "yolo_config_dir": "/app/storage/ultralytics",
    "torch_version": "2.12.1",
    "ultralytics_version": "8.4.88",
    "cuda_available": false
  },
  "tile_count": 0,
  "max_tiles": 100,
  "will_download_models": false,
  "will_run_inference": false
}
```

### POST `/api/v1/detection/run`

Creates a detection job and detection analysis run. If the requested model is unavailable, the job and analysis run are marked `failed` with `DETECTION_MODEL_UNAVAILABLE` or `DETECTION_DEPENDENCY_UNAVAILABLE`.

Request:

```json
{
  "project_id": "uuid",
  "dataset_id": "uuid",
  "model_id": "yolo-placeholder",
  "model_asset_id": null,
  "confidence_threshold": 0.5,
  "class_filter": ["building"],
  "tile_manifest_path": null,
  "parameters_json": {}
}
```

Sprint 8B configured YOLO mode uses `model_id: "yolo-configured"`. It requires:

- `YOLO_ENABLED=true`
- `YOLO_MODEL_PATH` pointing to an existing local model file
- backend optional AI dependencies installed with `geointel-backend[ai]`
- `tile_manifest_path` pointing to an existing raster tile manifest generated by the raster tile operation

`model_asset_id` may be supplied with `model_id: "yolo-configured"` to select a
specific local model file from the read-only model asset catalog. The backend
resolves the ID to a file inside the configured model directory and persists the
asset ID, path and SHA-256 in the job and analysis-run parameters for
reproducibility. Clients must not submit arbitrary model paths.

GeoIntel does not download model weights automatically. Configured YOLO runs read existing tile files from the manifest, convert YOLO pixel-space boxes to EPSG:4326 detection polygons and persist detections as first-class records.

Unavailable model response:

```json
{
  "analysis_run_id": "uuid",
  "job_id": "uuid",
  "project_id": "uuid",
  "dataset_id": "uuid",
  "model_id": "yolo-placeholder",
  "status": "failed",
  "detection_count": 0,
  "error_code": "DETECTION_MODEL_UNAVAILABLE",
  "message": "YOLO/PyTorch inference is not configured in Sprint 8; no model is downloaded or executed."
}
```

Validation errors:

- `INVALID_DATASET_TYPE` when the dataset is not raster.
- `DETECTION_MODEL_NOT_FOUND` when the model id is unknown.
- `DETECTION_MODEL_ASSET_NOT_FOUND` when `model_asset_id` is not present in the configured model directory.
- `FIXTURE_MODE_REQUIRED` when `manual-fixture-detector` is requested without `parameters_json.fixture_mode=true`.
- `DETECTION_TILE_MANIFEST_REQUIRED` when `yolo-configured` is requested without `tile_manifest_path`.
- `DETECTION_TILE_MANIFEST_NOT_FOUND` when the provided manifest path does not exist.
- `DETECTION_TILE_MANIFEST_INVALID` when the manifest cannot be parsed or lacks tile metadata.
- `DETECTION_TILE_LIMIT_EXCEEDED` when the manifest exceeds `YOLO_MAX_TILES`.
- Configured YOLO inference forwards `YOLO_MAX_DETECTIONS` to Ultralytics
  `max_det` and defaults to `1000` so dense building AOIs are not silently
  limited by the upstream default of 300 detections before persisted QA/QC.
- Configured YOLO applies cross-tile duplicate suppression after pixel boxes are
  converted to EPSG:4326 geometries and before `Detection` rows are persisted.
  Same-class candidates are confidence-sorted and lower-confidence candidates
  with geometry IoU greater than or equal to
  `YOLO_DUPLICATE_IOU_THRESHOLD` are suppressed. The default is `0.5`; `0`
  disables this GeoIntel-side post-processing for debugging.
- `DETECTION_DEPENDENCY_UNAVAILABLE` when YOLO dependencies are not installed.
- `DETECTION_MODEL_LOAD_FAILED` when the local model file exists but cannot be loaded.

Fixture detector mode is test/demo-only. It persists only explicit `parameters_json.fixture_detections` entries and is never invoked automatically.

### GET `/api/v1/detection/runs/{analysis_run_id}`

Returns one detection analysis run.

### GET `/api/v1/detection/runs`

Returns detection analysis runs, optionally filtered by `project_id` and `dataset_id`.

### GET `/api/v1/detection/runs/{analysis_run_id}/detections`

Returns persisted detections for a detection analysis run. Optional filters:

- `dataset_id`
- `class_name`
- `min_confidence`

### GET `/api/v1/detection/datasets/{dataset_id}/detections`

Returns persisted detections for a raster dataset. Optional filters:

- `analysis_run_id`
- `class_name`
- `min_confidence`

### GET `/api/v1/detection/detections/{detection_id}`

Returns one persisted detection.

### GET `/api/v1/detection/runs/{analysis_run_id}/geojson`

Returns persisted detections for a run as a GeoJSON FeatureCollection. Geometry comes from persisted PostGIS detection geometry in EPSG:4326.

Each feature includes:

- `detection_id`
- `class_name`
- `confidence`
- `model_name`
- `model_version`
- `analysis_run_id`
- `dataset_id`
- `job_id`
- `source_tile_path`
- `bbox_json`

### GET `/api/v1/detection/datasets/{dataset_id}/geojson`

Returns persisted detections for a dataset as a GeoJSON FeatureCollection. Optional filters match the detection list endpoint.

### POST `/api/v1/detection/runs/{analysis_run_id}/qa/reference`

Compares persisted detection geometries from an analysis run against persisted `vector_features` from a reference vector dataset.

Request:

```json
{
  "reference_dataset_id": "uuid",
  "iou_threshold": 0.5,
  "class_name": "building",
  "min_confidence": 0.5
}
```

Response persists a `quality_check` and `metrics` rows through the existing QA/QC persistence architecture and returns:

- `precision`
- `recall`
- `f1_score`
- `mean_iou`
- `false_positives`
- `false_negatives`
- `quality_check_id`

Configured-YOLO QA automatically reads `tile_manifest_path` from the persisted
`AnalysisRun.parameters_json`. Candidate and reference geometries are clipped
to the union of the manifest's tile bounds after explicit CRS transformation to
EPSG:4326. Before reference geometries are materialized, the service applies
that coverage with an indexed PostGIS `ST_Intersects` predicate. The full
dataset count is retained separately so raw/evaluated/excluded counts remain
auditable without transferring a regional reference dataset to Python. The
response additionally returns:

- `candidate_feature_count_raw` and `reference_feature_count_raw`;
- `coverage`, including raw/evaluated/excluded/boundary-clipped population
  counts, tile count, source CRS values and coverage mode;
- `box_to_footprint_diagnostics`, which compares candidate boxes with reference
  envelopes at the same IoU threshold.

The canonical precision, recall, F1 and mean IoU always remain based on
candidate geometry versus the persisted reference footprint. Envelope results
are explicitly `diagnostic_only` and are persisted in
`quality_checks.findings_json`; they never replace or inflate canonical metrics.

Configured-YOLO QA fails closed with `DETECTION_QA_COVERAGE_UNAVAILABLE` when
manifest provenance is absent, `DETECTION_QA_COVERAGE_MISMATCH` when it belongs
to another raster, `DETECTION_QA_COVERAGE_INVALID` when bounds/CRS are invalid,
or `REFERENCE_FEATURES_OUTSIDE_COVERAGE` when no reference polygons overlap the
actual inference coverage. Explicit fixture/legacy runs without a manifest keep
the documented unbounded comparison behavior.

If the reference dataset has no persisted vector features, the endpoint returns `REFERENCE_FEATURES_NOT_FOUND`. It does not calculate fake QA metrics.

#### Future analysis route: `/api/v1/analysis/building-stats`

Not implemented in the active API surface. Future input is expected to combine
an area with a vector building layer.

#### Future analysis route: `/api/v1/analysis/object-detection`

Request:

```json
{
  "project_id": "uuid",
  "area_id": "uuid",
  "dataset_id": "uuid",
  "model_id": "optional uuid",
  "classes": ["building"],
  "confidence_threshold": 0.35,
  "tile_size": 640,
  "overlap": 64
}
```

Response: `AnalysisRunRead`.

#### Future analysis route: `/api/v1/analysis/segmentation`

Same pattern as object detection, but output includes masks and polygonized geometries.

## Segmentation Lab

Sprint 9 implements Segmentation Lab foundation only. Real SAM and YOLO-seg inference are not enabled, no model is downloaded, and fixture segmentations require explicit fixture mode.

### GET `/api/v1/segmentation/models`

Returns segmentation model capability descriptors:

- `segmentation-placeholder`: `not_configured`
- `fixture-segmenter`: configured for explicit test/demo fixtures only
- `yolo-seg-configured`: `not_configured`
- `sam-configured`: `not_configured`

### POST `/api/v1/segmentation/run`

Creates a segmentation job and segmentation analysis run. If the requested model is unavailable, the job and analysis run are marked `failed` with `SEGMENTATION_MODEL_UNAVAILABLE`.

Request:

```json
{
  "project_id": "uuid",
  "dataset_id": "uuid",
  "model_id": "segmentation-placeholder",
  "confidence_threshold": 0.5,
  "class_filter": ["vegetation"],
  "tile_manifest_path": null,
  "parameters_json": {}
}
```

Fixture segmenter mode is test/demo-only. It persists only explicit `parameters_json.fixture_segmentations` entries when `parameters_json.fixture_mode=true`; it is never invoked automatically and does not represent production inference.

Validation errors:

- `INVALID_DATASET_TYPE` when the dataset is not raster.
- `SEGMENTATION_MODEL_NOT_FOUND` when the model id is unknown.
- `FIXTURE_MODE_REQUIRED` when `fixture-segmenter` is requested without `parameters_json.fixture_mode=true`.
- `INVALID_FIXTURE_SEGMENTATIONS` when fixture payloads are not a list.
- `INVALID_FIXTURE_GEOMETRY` when fixture geometry is empty, invalid or not Polygon/MultiPolygon.

### GET `/api/v1/segmentation/runs`

Returns segmentation analysis runs, optionally filtered by `project_id` and `dataset_id`.

### GET `/api/v1/segmentation/runs/{analysis_run_id}`

Returns one segmentation analysis run.

### GET `/api/v1/segmentation/runs/{analysis_run_id}/segmentations`

Returns persisted segmentation records for a segmentation analysis run. Optional filters:

- `dataset_id`
- `class_name`
- `min_confidence`

### GET `/api/v1/segmentation/datasets/{dataset_id}/segmentations`

Returns persisted segmentation records for a raster dataset. Optional filters:

- `analysis_run_id`
- `class_name`
- `min_confidence`

### GET `/api/v1/segmentation/segmentations/{segmentation_id}`

Returns one persisted segmentation record.

### GET `/api/v1/segmentation/runs/{analysis_run_id}/geojson`

Returns persisted segmentations for a run as a GeoJSON FeatureCollection. Geometry comes from persisted PostGIS segmentation geometry in EPSG:4326.

Each feature includes:

- `segmentation_id`
- `class_name`
- `confidence`
- `area_m2`
- `model_name`
- `model_version`
- `analysis_run_id`
- `dataset_id`
- `job_id`
- `source_tile_path`
- `tile_index`
- `mask_path`
- `bbox_json`
- `provenance_json`

### GET `/api/v1/segmentation/datasets/{dataset_id}/geojson`

Returns persisted segmentations for a dataset as a GeoJSON FeatureCollection. Optional filters match the segmentation list endpoint.

### POST `/api/v1/segmentation/runs/{analysis_run_id}/qa/reference`

Compares persisted segmentation geometries from an analysis run against persisted `vector_features` from a reference vector dataset.

Request:

```json
{
  "reference_dataset_id": "uuid",
  "iou_threshold": 0.5,
  "class_name": "vegetation",
  "min_confidence": 0.5
}
```

Response persists a `quality_check` and `metrics` rows through the existing QA/QC persistence architecture and returns precision, recall, F1, mean IoU and false positive/negative counts.

If the segmentation run has no persisted geometries, the endpoint returns `SEGMENTATIONS_NOT_FOUND`. If the reference dataset has no persisted vector features, it returns `REFERENCE_FEATURES_NOT_FOUND`. It does not calculate fake QA metrics.

### POST `/api/v1/analysis/change-detection`

Compares two persisted vector datasets in the same project and returns a synchronous
job envelope. This is a lightweight V1 foundation for added/removed object review,
not a temporal run-history engine.

Request:

```json
{
  "source_dataset_id": "uuid",
  "target_dataset_id": "uuid",
  "iou_threshold": 0.8,
  "include_unchanged": true
}
```

Response is a canonical API envelope containing a `JobRead` payload. On success,
`result_json` contains:

```json
{
  "source_dataset_id": "uuid",
  "target_dataset_id": "uuid",
  "source_feature_count": 2,
  "target_feature_count": 2,
  "added_count": 1,
  "removed_count": 1,
  "unchanged_count": 1,
  "iou_threshold": 0.8,
  "warnings": [],
  "generated_at": "2026-06-16T00:00:00Z",
  "geojson": {
    "type": "FeatureCollection",
    "features": []
  }
}
```

Change detection prefers persisted `vector_features`. If an older vector dataset
has no persisted vector rows, it falls back to the stored GeoJSON artifact and
adds a warning to `result_json.warnings`. Supported comparable geometry types are
`Polygon` and `MultiPolygon`; point/line geometries return `UNSUPPORTED_GEOMETRY`.

GeoJSON feature properties include:

- `change_type`: `added`, `removed` or `unchanged`
- `source_dataset_id`
- `target_dataset_id`
- `source_feature_id`
- `target_feature_id`
- `iou`

Limitations:

- No live GRB/OSM/Sentinel fetching.
- No fake object lifecycle classification.
- No `changed` classification without durable object ids/versioning.
- No first-class change table yet; the current output is stored in job
  `result_json` and rendered in the frontend map.

## QA/QC

### POST `/api/v1/qa/detections-vs-reference`

Request:

```json
{
  "candidate_dataset_id": "uuid",
  "reference_dataset_id": "uuid",
  "iou_threshold": 0.5,
  "area_id": "optional uuid"
}
```

Response is wrapped in the job envelope. On success, `result_json` includes precision, recall, F1, mean IoU, false positives, false negatives and `quality_check_id`.

Sprint 111 also includes feature-level evidence arrays for map/review handoff:

- `match_evidence`: matched candidate/reference feature ids with IoU.
- `false_positive_evidence`: unmatched candidate feature ids.
- `false_negative_evidence`: unmatched reference feature ids.

These arrays are derived from the same persisted/source geometries used for IoU matching. They are not separate QA records yet; they are persisted inside `quality_checks.findings_json`.

Sprint 7A persists the QA/QC result as:

- `jobs`: execution state.
- `quality_checks`: domain result.
- `metrics`: individual measurements.

Future Detection and Segmentation flows may add an `analysis_run_id` path without replacing persisted quality checks.

### GET `/api/v1/projects/{project_id}/quality-checks`

Lists persisted QA/QC quality checks for a project with metric rows.

Response:

```json
{
  "items": [
    {
      "id": "uuid",
      "project_id": "uuid",
      "job_id": "uuid-or-null",
      "analysis_run_id": "uuid-or-null",
      "candidate_dataset_id": "uuid-or-null",
      "reference_dataset_id": "uuid",
      "check_type": "demo_candidate_vs_reference",
      "status": "ok",
      "score": 0.5,
      "parameters_json": {},
      "findings_json": {
        "matches": 1,
        "false_positives": 1,
        "false_negatives": 1,
        "match_evidence": [
          {
            "candidate_feature_id": "candidate-feature-id",
            "reference_feature_id": "reference-feature-id",
            "iou": 0.83
          }
        ],
        "false_positive_evidence": [
          {
            "candidate_feature_id": "candidate-extra-id"
          }
        ],
        "false_negative_evidence": [
          {
            "reference_feature_id": "reference-missing-id"
          }
        ]
      },
      "metrics": [
        {
          "metric_key": "precision",
          "metric_value": 0.5
        }
      ]
    }
  ],
  "total": 1,
  "limit": 50,
  "offset": 0
}
```

### GET `/api/v1/projects/{project_id}/quality-checks/{quality_check_id}/evidence/geojson`

Returns a canonical envelope containing a read-only QA/QC evidence overlay for a
persisted quality check. The endpoint reads feature ids from
`quality_checks.findings_json.match_evidence`,
`false_positive_evidence` and `false_negative_evidence`, resolves them against
persisted candidate/reference geometries and returns a GeoJSON FeatureCollection.

Supported resolution paths:

- dataset QA candidate/reference geometries from `vector_features`;
- detection QA candidate geometries from persisted `detections`;
- segmentation QA candidate geometries from persisted `segmentations`;
- reference geometries from persisted `vector_features`.

Response:

```json
{
  "data": {
    "quality_check_id": "uuid",
    "project_id": "uuid",
    "candidate_dataset_id": "uuid-or-null",
    "reference_dataset_id": "uuid",
    "analysis_run_id": "uuid-or-null",
    "feature_count": 4,
    "warnings": [],
    "geojson": {
      "type": "FeatureCollection",
      "features": [
        {
          "type": "Feature",
          "id": "match_candidate:feature-id",
          "geometry": {},
          "properties": {
            "qa_evidence_role": "match_candidate",
            "quality_check_id": "uuid",
            "candidate_feature_id": "candidate-feature-id",
            "reference_feature_id": "reference-feature-id",
            "iou": 0.83
          }
        }
      ]
    }
  }
}
```

`qa_evidence_role` is one of `match_candidate`, `match_reference`,
`false_positive` or `false_negative`. Missing persisted feature ids are reported
in `warnings`; no fake geometries are produced.

Detection-backed candidate evidence also exposes provenance read from the
persisted `detections` row: `detection_id`, `job_id`, `confidence`,
`model_name`, `model_version`, `source_tile_path` and `bbox_json`. Existing
`properties_json` fields such as `tile_index` remain present. Segmentation-backed
candidate evidence exposes the equivalent persisted model/source fields plus
`segmentation_id`, `mask_path` and `area_m2`. These are additive GeoJSON
properties; the canonical envelope and endpoint path are unchanged.

For detection QA, false-positive and false-negative evidence properties also
include `review_decision`, `review_notes`, `reviewed_by` and `reviewed_at`.
Missing review rows are represented as `review_decision=unreviewed`. Evidence
resolution is bounded to identifiers stored by the selected quality check.

### GET `/api/v1/projects/{project_id}/quality-checks/{quality_check_id}/reviews`

Returns the paginated operator review queue for a persisted
`detections_vs_reference` quality check. Optional query parameters are
`evidence_role=false_positive|false_negative`, `decision`, `reviewed=true|false`,
`limit` (1-200) and `offset`. Items derive only from persisted QA evidence.

```json
{
  "data": {
    "items": [{
      "id": null,
      "project_id": "uuid",
      "quality_check_id": "uuid",
      "analysis_run_id": "uuid",
      "evidence_role": "false_positive",
      "evidence_feature_id": "detection-uuid",
      "detection_id": "detection-uuid",
      "decision": "unreviewed",
      "confidence": 0.62,
      "class_name": "building"
    }],
    "total": 1,
    "limit": 50,
    "offset": 0,
    "summary": {
      "total": 73,
      "reviewed": 0,
      "remaining": 73,
      "false_positive_total": 17,
      "false_negative_total": 56,
      "decision_counts": {"unreviewed": 73}
    }
  }
}
```

### POST `/api/v1/projects/{project_id}/quality-checks/{quality_check_id}/reviews`

Creates or updates one durable operator decision. The evidence id must belong
to the quality check and resolve to the persisted Detection or reference
VectorFeature. False-positive and false-negative roles accept only their
role-specific decisions.

```json
{
  "evidence_role": "false_positive",
  "evidence_feature_id": "detection-uuid",
  "decision": "qa_alignment_mismatch",
  "notes": "The detection box overlaps the irregular GRB footprint.",
  "reviewed_by": "operator"
}
```

Allowed decisions are `confirmed_model_false_positive`,
`confirmed_model_false_negative`, `reference_gap_or_change`,
`qa_alignment_mismatch`, `imagery_obscured_or_uncertain`, `uncertain` and
`unreviewed`. Invalid role/decision combinations return
`INVALID_DETECTION_REVIEW_DECISION`.

## Exports

### POST `/api/v1/exports/geojson`

Export detections, segmentations or vector layer to GeoJSON.

Dataset vector export request:

```json
{
  "export_kind": "dataset",
  "dataset_id": "uuid",
  "name": "optional-basename"
}
```

Map vector selection export request:

```json
{
  "export_kind": "vector_selection",
  "dataset_id": "uuid",
  "bbox": {
    "min_x": 5.0,
    "min_y": 51.0,
    "max_x": 5.1,
    "max_y": 51.1,
    "crs": "EPSG:4326"
  },
  "limit": 250,
  "name": "optional-basename"
}
```

Detection run export request:

```json
{
  "export_kind": "detection_run",
  "analysis_run_id": "uuid",
  "name": "optional-basename"
}
```

Segmentation run export request:

```json
{
  "export_kind": "segmentation_run",
  "analysis_run_id": "uuid",
  "name": "optional-basename"
}
```

Response persists an `exports` row and writes a deterministic JSON artifact:

```json
{
  "export_id": "uuid",
  "path": "storage/exports/{project_id}/datasets/{target}/{name}.geojson",
  "status": "ready",
  "export_type": "dataset_geojson",
  "metadata_json": {
    "source": "dataset",
    "feature_count": 0
  }
}
```

Vector dataset exports use the stored dataset GeoJSON. Detection and
segmentation exports use persisted first-class geometry records and the
existing Detection/Segmentation GeoJSON conversion services. Vector selection
exports query persisted PostGIS `vector_features` with the supplied EPSG:4326
bbox, write the selected FeatureCollection as a `vector_selection_geojson`
artifact, and persist bbox/feature-count metadata in the export record. Raster
datasets are rejected for dataset and selection GeoJSON export.

### POST `/api/v1/exports/metadata`

Exports project metadata JSON for projects, datasets, persisted QA/QC summary
rows and existing export history.

```json
{
  "project_id": "uuid",
  "name": "optional-basename"
}
```

### GET `/api/v1/exports/projects/{project_id}/exports`

Lists persisted export records for a project.

### GET `/api/v1/exports/{export_id}`

Returns one persisted export record.

### GET `/api/v1/exports/{export_id}/content`

Returns the stored JSON artifact content through the standard API envelope.
HTML report artifacts are intentionally download-only through `/download`.
Calling `/content` for `project_report_html` returns:

```text
code: EXPORT_CONTENT_UNSUPPORTED
message: Export content preview is only available for JSON and GeoJSON artifacts. Download HTML report artifacts instead.
```

### GET `/api/v1/exports/{export_id}/download`

Downloads the stored JSON/GeoJSON/HTML export artifact as a raw file response
with a `Content-Disposition` attachment filename. JSON and GeoJSON artifacts
use `application/json`; HTML report artifacts use `text/html`. This endpoint
intentionally does not use the JSON envelope because it is a browser/file-download
path; callers that need canonical API JSON should use `/content` for JSON/GeoJSON
artifacts.

#### Future export route: `/api/v1/exports/yolo`

Export annotations/detections to YOLO format.

### POST `/api/v1/exports/report`

Creates a lightweight HTML project report artifact from persisted project,
dataset, V1 readiness summary, QA/QC summary, known limitations and export
history state. This does not create a PDF and does not introduce a report
designer.

```json
{
  "project_id": "uuid",
  "name": "optional-basename"
}
```

Response persists an `exports` row with `export_type:
project_report_html`. Download the report through:

```text
GET /api/v1/exports/{export_id}/download
```

PDF/report-designer functionality can be added after core GeoAI workflows work.

## Temporal datasets and area evolution

Temporal metadata describes the source observation, not API run history. A
snapshot is a normal persisted dataset grouped by `temporal_series_key` and
ordered by `observed_at`. Optional validity uses `valid_from` and `valid_to`;
`temporal_granularity` is `snapshot`, `day`, `month`, `year` or `period`.

Dataset upload accepts those temporal fields plus `source_version`. When a
dataset declares `source_metadata.selection_aggregation`, the vector bbox
selection response also contains a `summary` with metric label/value/unit,
aggregation method, feature count, estimate status and an optional warning.
Supported PostGIS aggregations are feature count, intersection area,
intersection length, numeric sum and area-weighted numeric sum. Area and length
are measured after transformation to EPSG:31370.
Configured supplemental metrics can use `filter_property` plus
`filter_values`. Filters are server-owned dataset metadata, not arbitrary
client SQL or request expressions.

### PATCH `/api/v1/projects/{project_id}/datasets/{dataset_id}/temporal`

Updates the temporal provenance of an existing dataset. Series key and
observation date are required together. It does not alter features or
manufacture a historical observation.

### GET `/api/v1/projects/{project_id}/datasets/{dataset_id}/versions`

Lists immutable storage/provenance versions. Uploads and derived datasets
create version 1 in the same persistence transaction.

### GET `/api/v1/projects/{project_id}/temporal/series`

Returns dated project series in the canonical envelope. Each item contains its
source/layer identity, first and last observations and ordered datasets.

### POST `/api/v1/projects/{project_id}/temporal/compare`

```json
{
  "earlier_dataset_id": "uuid",
  "later_dataset_id": "uuid",
  "bbox": {"min_x": 5.0, "min_y": 51.0, "max_x": 5.2, "max_y": 51.2, "crs": "EPSG:4326"},
  "area_id": "optional persisted Area uuid",
  "preview_limit": 500
}
```

Both datasets must belong to the project and the same temporal series, with
the earlier observation preceding the later one. The response contains source
snapshot references, selection bbox, earlier/later metric values,
absolute/percentage change, estimate status, warnings and GeoJSON evidence.
`metric` remains the backwards-compatible primary measurement. `metrics`
contains every aggregation that is compatible between both snapshots and
`timeline` contains the same persisted metric for every dated snapshot in the
series. When `area_id` is supplied it must belong to the project and the exact
persisted Area geometry is used; the bbox remains only the bounded map extent.
Added/removed/modified object changes are calculated only when source
provenance declares stable feature identities; otherwise
`object_changes.available=false` and no object history is inferred.

Governed regional GRB snapshots use the official OGC feature identifier as
their object identity. New imports declare the identity scheme and accepted
collection prefixes explicitly. Existing operator-managed GRB snapshots are
accepted only when their authoritative, complete and area-clipped provenance
matches an approved regional operator and every selected identifier is
present, unique and uses the expected prefix. Missing, duplicate or unexpected
identifiers fail closed to metric-only comparison. The existing 5,000-feature
selection limit also remains in force. Differences between daily GRB editions
describe changes in the official registration; they do not prove that a
physical change happened on the exact publication date.

For `reference_layer_name=agriculture`, the primary map metric is exact
intersected declared-use area in hectares. Supplemental metrics use
server-owned filters on the normalized official main-crop group. Annual ALZ
Datasets share one scope-specific temporal series, but declare
`identity_stable=false`; their temporal response compares area totals and
returns no parcel-level added/removed/modified claims.

For `reference_layer_name=building_registry`, the primary metric is exact
intersected building-footprint area in hectares. Supplemental server-owned
metrics expose register building/status counts, aggregate building-unit and
address-status counts, and confirmed GRB matches. Filtered `feature_count`
metrics apply their configured property filter in PostGIS just like filtered
area/sum metrics. Address labels and house/box numbers are never part of the
queryable Feature properties or response contract.

The governed snapshot is scoped to its persisted `area_id`. The frontend may
prefer it over the regional GRB building layer only when that exact Area is
active; another municipality or the full region must continue to use the
regional GRB Dataset. No new register-specific API endpoint exists: upload,
GeoJSON, exact selection and temporal provenance use the existing Dataset
contracts.

## Local GeoIntel assistant

The assistant is an optional read-only language interface over persisted
GeoIntel measurements. The browser never connects to Ollama directly and does
not choose an arbitrary provider URL.

### GET `/api/v1/assistant/status`

Returns `configured`, `not_configured` or `unavailable`, the configured default
model and the number of locally installed models. It never downloads a model.

### GET `/api/v1/assistant/models`

Returns the models reported by Ollama `GET /api/tags` in the canonical
envelope. A chat request can only select a model from this list.

### POST `/api/v1/projects/{project_id}/assistant/query`

```json
{
  "question": "Hoe evolueerde de bosoppervlakte?",
  "model": "qwen3.5:9b",
  "bbox": {"min_x": 5.0, "min_y": 51.0, "max_x": 5.2, "max_y": 51.2, "crs": "EPSG:4326"},
  "area_id": "optional persisted Area uuid",
  "history": []
}
```

The backend validates project/Area ownership, calculates current semantic
metrics from PostGIS and includes dated observations only for persisted
temporal series. Geometry is not sent to Ollama. The response contains the
answer, used model, scope label, context metrics, discovered temporal series,
source dataset ids and warnings. Missing measurements remain unavailable;
specifically, no water volume is inferred from 2D water geometry. The backend
sets an explicit Ollama context window and returns
`OLLAMA_RESPONSE_TRUNCATED` instead of accepting a response with
`done_reason=length` as a complete answer.