n8n-geospatial

n8n workflow automation platform enhanced with comprehensive geospatial capabilities including QGIS, GDAL, PDAL, and Tippecanoe.

Features

• n8n 1.123.0 - Workflow automation platform
• QGIS 3.44.2 - Geographic Information System with Python bindings
• GDAL - Geospatial Data Abstraction Library for raster/vector data
• PDAL - Point Data Abstraction Library for LiDAR/point cloud processing
• Tippecanoe - Build vector tilesets from large collections of GeoJSON features
• MinIO Client - High-performance object storage client
• GraphicsMagick - Image processing capabilities
• Node.js 20.x - JavaScript runtime

Quick Start

Using Docker Compose (Recommended)

# Clone the repository
git clone https://github.com/your-username/n8n-geospatial.git
cd n8n-geospatial

# Start the service
docker-compose up -d

# Access n8n at http://localhost:5678

Using Docker directly

# Build the image
docker build -t n8n-geospatial .

# Run the container
docker run -d \
  --name n8n-geospatial \
  -p 5678:5678 \
  -v ./n8n-data:/home/node/.n8n \
  n8n-geospatial

Geospatial Capabilities

QGIS Integration

• Full QGIS 3.44.2 installation with Python bindings
• Access via Python scripts in n8n workflows
• Support for vector and raster processing

GDAL Tools

• Command-line tools: gdalinfo, gdal_translate, ogr2ogr
• Python bindings for programmatic access
• Support for 200+ geospatial formats

PDAL Tools

• Point cloud processing and analysis
• LiDAR data manipulation
• Python bindings for workflow integration

Tippecanoe

• Build vector tilesets from large collections of GeoJSON features
• Command-line tools: tippecanoe, tile-join, tippecanoe-enumerate, tippecanoe-decode
• Optimize GeoJSON data for web mapping applications
• Create efficient MBTiles for Mapbox, MapLibre, and other tile servers

Other utilities

MinIO Client

• High-performance object storage client (mc)
• S3-compatible API for object storage operations
• Manage buckets, objects, and policies
• Useful for storing and retrieving geospatial data files

Example Workflows

1. Geospatial Data Processing

# In n8n Python node
import qgis.core
from osgeo import gdal

# Load and process vector data
layer = qgis.core.QgsVectorLayer("path/to/data.shp", "layer", "ogr")
# Process data...

2. Raster Analysis

# GDAL raster operations
dataset = gdal.Open("input.tif")
# Perform analysis...

3. Point Cloud Processing

# PDAL point cloud operations
import pdal
pipeline = pdal.Pipeline("pipeline.json")
pipeline.execute()

4. Vector Tile Generation

# In n8n Execute Command node
# Convert GeoJSON to vector tiles
tippecanoe -o output.mbtiles input.geojson

# Join attributes from CSV to existing tiles
tile-join -o joined.mbtiles -c attributes.csv existing.mbtiles

# Decode tiles back to GeoJSON
tippecanoe-decode output.mbtiles

5. Object Storage Operations

# In n8n Execute Command node
# Configure MinIO client
mc alias set myminio https://minio.example.com ACCESS_KEY SECRET_KEY

# Upload geospatial data
mc cp data.geojson myminio/geospatial-bucket/

# Download data
mc cp myminio/geospatial-bucket/data.geojson ./

# List objects
mc ls myminio/geospatial-bucket/

Development

Building Locally

# Build for testing
docker build -t n8n-geospatial:test .

# Run tests
./build.sh

Testing

The automated workflow tests:

• QGIS accessibility and Python bindings
• n8n web interface accessibility
• GDAL command-line tools and Python bindings
• PDAL command-line tools and Python bindings
• Tippecanoe command-line tools
• MinIO Client accessibility

Logs

# View container logs
docker-compose logs n8n

# Access container shell
docker exec -it n8n-geospatial bash

Upgrading

n8n

# In Dockerfile, line 61
RUN npm install -g n8n@1.123.0  # Change version here

QGIS

# In Dockerfile, lines 1 and 37
FROM qgis/qgis:3.44.2-bookworm AS builder  # Change version here
FROM qgis/qgis:3.44.2-bookworm             # And here

Rebuild

docker-compose down
docker-compose build --no-cache
docker-compose up -d

License

MIT License - see LICENSE file for details.