GeoIntel combines official geospatial sources, map-based analysis, computer vision, QA/QC and reproducible exports. A saved result carries its source, spatial context, model revision and review evidence. The application covers Belgium and the legally distinct Belgian North Sea zones without hiding differences between regional source datasets.

Mol and the Kempen remain golden regression areas for the Belgium-wide workbench; they do not limit its geographic scope.

Explore the workbench

The following captures use public or synthetic demonstration content. Select an official boundary or draw an area of interest, choose compatible layers, run an analysis, inspect object-level evidence, and export the reviewed result.

Map workbench	Quality review

The mobile workbench keeps the same analysis context on a narrow screen. Asset provenance describes these captures and project artwork.

What it does

Source-aware mapping: official boundaries, vector and raster layers, orthophotos, regional and maritime sources, and explicit coverage.
Spatial analysis: coordinate-system normalization, clipping, buffering, joins and raster statistics.
Governed GeoAI: PyTorch, YOLO and SAM-compatible model workflows with immutable revisions and release gates.
Quality before publication: precision, recall, F1, IoU, false-positive and false-negative evidence, plus human review.
Traceable output: reproducible GeoJSON and artifacts linked to the selected area, input versions and model revision.

Model detections are reviewable proposal evidence until the relevant release gate passes. Official footprints are not assumed to be perfect image labels; temporal validity and spatial leakage are checked during training and calibration.

Quick start

Requirements: Docker Engine with Compose. From the repository root:

docker compose up --build

Open http://localhost:1202. The development stack uses Python 3.11+, Node 20.19+ or 22.12+, and PostgreSQL/PostGIS. Set GEOINTEL_AUTH_ENABLED=true and explicitly opt in with GEOINTEL_GUEST_ACCESS_ENABLED=true only for a dedicated public-data demo. Guest sessions are short-lived and project-bound; administration and uploads remain restricted.

Technical overview

flowchart LR
    Web[React, TypeScript and MapLibre] --> API[FastAPI]
    API --> GIS[GeoPandas, Shapely and Rasterio]
    API --> Jobs[PostgreSQL job queue]
    Jobs --> AI[PyTorch inference]
    GIS --> DB[(PostgreSQL and PostGIS)]
    AI --> DB
    DB --> QA[QA and provenance]
    QA --> Web

Configured AI inference can use NVIDIA/CUDA and fails closed when a required accelerator is unavailable. A deployment needs persistent PostGIS and artifact storage, authentication, HTTPS, health checks, backups and a tested restore path. Do not place private model weights, credentials or operational exports in this repository.

For source checks, run python -m compileall backend/app, the backend pytest suite, and the frontend typecheck, unit tests and build. backend/ contains the API and spatial workflows; frontend/ contains the UI; contracts/ contains shared interfaces; fixtures/ contains safe examples.

Public-source provenance

This is a reviewed content-only export from a private canonical repository. PUBLIC_SOURCE_MANIFEST.json records the source revision and hashes; private Git history is absent. GeoIntel is licensed under Apache 2.0. See SECURITY.md for vulnerability reporting.