6.4 KiB
GeoIntel Kempen — Data Catalog v1.0
This catalog is the implementation reference for every dataset that GeoIntel may ingest, cache, analyse, validate against, or export. Codex must treat this file as source-of-truth when implementing data ingestion and analysis modules.
Data strategy
GeoIntel is built around a professional reference-data-first strategy:
- Use official Flemish geodata where available.
- Use OpenStreetMap as a supplemental and fallback source.
- Use raster/satellite/aerial imagery for AI and remote-sensing pipelines.
- Cache all expensive or external requests in PostGIS and/or filesystem storage.
- Store provenance metadata for every derived result.
Priority sources
| Priority | Source | Role | Data type | V1 status |
|---|---|---|---|---|
| P0 | GRB / Basiskaart Vlaanderen | official reference geometry | vector | required as primary reference target |
| P0 | User uploaded GeoTIFF / imagery | model input | raster | required |
| P0 | User uploaded GeoJSON/Shapefile/GPKG | vector input/reference | vector | required |
| P1 | OpenStreetMap | fallback and additional context | vector | required in V1 if GRB connector is not ready |
| P1 | Gebouwenregister | building identifiers and metadata | vector/API | prepare architecture |
| P2 | Sentinel-2 | NDVI/NDWI/NDBI and temporal analysis | raster | roadmap |
| P2 | DHMV / height products | DEM/DSM/slope/height analysis | raster/point cloud | roadmap |
| P3 | LAS/LAZ point clouds | LiDAR workbench | point cloud | roadmap |
GRB — Basiskaart Vlaanderen
Purpose
GRB is the main official reference layer for GeoIntel Kempen. It is used for QA/QC, validation, feature comparison, and map context. It contains accurately measured reference objects such as buildings, parcels, roads and road inrichting, watercourses, railway beds and road networks. It is a cost-free authentic source managed by Digitaal Vlaanderen.
Implementation role
GRB is not just a background map. It must become a validation and reference backbone:
- Compare AI building detections with official building footprints.
- Identify false positives and false negatives.
- Create QA/QC dashboards.
- Provide high-quality vector context for map overlays.
- Support change-detection workflows where official snapshots are available.
Required layer groups
The exact service layer names must be discovered during implementation through the GRB WFS/WMS capabilities endpoint or downloaded package metadata. The application-level canonical layer groups are:
| Canonical group | Expected geometry | Usage |
|---|---|---|
grb_buildings |
polygon | building reference, QA/QC, footprint analysis |
grb_roads |
line/polygon | road/infrastructure context, pressure metrics |
grb_water |
line/polygon | water context, water proximity, hydro overlays |
grb_railways |
line/polygon | infrastructure barrier/context |
grb_parcels |
polygon | optional parcel context, not required for V1 |
Required normalized fields
For every imported GRB feature, normalize at least:
id: internal UUID
source: "GRB"
source_layer: original layer name
source_feature_id: original feature identifier when available
canonical_group: grb_buildings | grb_roads | grb_water | grb_railways | grb_parcels
geometry: PostGIS geometry
geometry_type: Polygon | MultiPolygon | LineString | MultiLineString
crs_original: original CRS
crs_storage: EPSG:31370 or EPSG:4326 depending DB policy
attributes_json: raw attributes
fetched_at: timestamp
source_updated_at: timestamp when available
bbox: calculated bounds
area_m2: calculated for polygon features
length_m: calculated for linear features
Access strategy
V1 may implement either:
- WFS area-of-interest fetch, preferred for targeted analysis.
- Downloaded package import for cached offline analysis.
- OSM fallback when GRB access is not implemented yet.
Codex may build an abstraction ReferenceDataProvider so GRB and OSM can both satisfy the same downstream analysis contracts.
User uploaded raster imagery
Supported formats
- GeoTIFF
.tif,.tiff - Cloud Optimized GeoTIFF if possible
- JPEG/PNG only if accompanied by georeferencing metadata or used as non-geospatial demo input
Required metadata
dataset_id
file_path
file_size_bytes
raster_driver
width
height
band_count
crs
transform
bounds
resolution_x
resolution_y
nodata_values
dtype_per_band
statistics_per_band
color_interpretation
is_georeferenced
created_at
Required uses
- Map overlay preview.
- Raster metadata inspection.
- Clipping to area of interest.
- Tiling for object detection and segmentation.
- Remote sensing index calculations when bands support it.
User uploaded vector data
Supported formats
- GeoJSON
- Shapefile ZIP
- GeoPackage
.gpkg - KML/KMZ later
Required metadata
dataset_id
source_filename
format
layer_names
feature_count
geometry_types
crs
bounds
attributes_schema
created_at
Required uses
- Reference data.
- Manual annotations.
- User-supplied areas of interest.
- Comparison layers for QA/QC.
OpenStreetMap
Purpose
OSM is used for fast open-data enrichment and fallback when official sources are not yet implemented.
Canonical groups
osm_buildingsosm_roadsosm_waterosm_greenosm_landuseosm_poi
Required fields
osm_id
tags_json
canonical_group
geometry
area_m2
length_m
fetched_at
Sentinel-2
Purpose
Sentinel-2 supports remote sensing indices and temporal change analysis.
Required indices later
- NDVI =
(NIR - Red) / (NIR + Red) - NDWI =
(Green - NIR) / (Green + NIR) - NDBI =
(SWIR - NIR) / (SWIR + NIR)
V1 rule
Prepare architecture, but do not block V1 on a full Sentinel downloader.
DHMV / DEM / DSM
Purpose
Height intelligence: slope, low points, terrain context, DSM minus DEM for object height approximations.
Required outputs later
min_elevation_mmax_elevation_mmean_elevation_mslope_mean_deglow_point_polygonsheight_profile_samples
Data provenance requirements
Every derived dataset must keep:
source_dataset_ids
processing_pipeline
parameters_json
software_versions
created_at
created_by_job_id
crs
quality_flags
V1 non-negotiables
- Do not hardcode temporary demo assumptions into data models.
- Every dataset must have metadata.
- Every derived output must reference its source dataset and analysis run.
- AI outputs must be stored as geospatial outputs, not only image overlays.