The TSYS-AIOS-GIS-Tools-GIS-Base container is designed for GIS data processing and weather data analysis tasks. It includes essential tools for handling geospatial data formats and weather datasets with a focus on self-hosted GIS stack capabilities.

Tools Included

Core Tools

Base OS: Debian Bookworm slim
Shell: Bash
Programming Languages:
- Python 3 with geospatial libraries
- R with spatial packages

GIS Libraries

GDAL/OGR: Geospatial Data Abstraction Library for format translation and processing
PROJ: Coordinate transformation software
PostGIS: Client tools for spatial database operations
DuckDB: With spatial extensions for efficient data processing
GeoPandas: Python geospatial data handling
Shapely: Python geometric operations
Rasterio: Raster processing in Python

Weather Data Processing

xarray: Multi-dimensional data in Python
cfgrib: GRIB format handling
netCDF4: NetCDF file handling
MetPy: Meteorological calculations (via Python libraries)

Visualization

Folium: Interactive maps
Plotly: Time series visualization
Matplotlib/Seaborn: Statistical plots
R visualization packages: For statistical analysis

Additional Tools

Dask: For large data processing
FTP client: For bulk data downloads

Usage

Building the Base Container

# From this directory
cd /home/localuser/AIWorkspace/TSYS-AIOS-GIS/Docker/TSYS-AIOS-GIS-Tools-GIS-Base

# Use the wrapper script to automatically detect and set user IDs
./docker-compose-wrapper.sh build

# Or run commands in the base container with automatic user mapping
./docker-compose-wrapper.sh run tsys-gis-base [command]

# Example: Process a shapefile with GDAL
./docker-compose-wrapper.sh run tsys-gis-base ogrinfo /workspace/path/to/shapefile.shp

# Example: Start Python with geospatial libraries
./docker-compose-wrapper.sh run tsys-gis-base python3

# Example: Start R with spatial packages
./docker-compose-wrapper.sh run tsys-gis-base R

Using with docker-compose directly

# Set environment variables and run docker-compose directly
LOCAL_USER_ID=$(id -u) LOCAL_GROUP_ID=$(id -g) docker-compose up --build

# Or export variables first
export LOCAL_USER_ID=$(id -u)
export LOCAL_GROUP_ID=$(id -g) 
docker-compose up

Using the wrapper script

# Build and start the base GIS container with automatic user mapping
./docker-compose-wrapper.sh up --build

# Start without rebuilding
./docker-compose-wrapper.sh up

# View container status
./docker-compose-wrapper.sh ps

# Stop containers
./docker-compose-wrapper.sh down

User ID Mapping (For File Permissions)

The container automatically detects and uses the host user's UID and GID to ensure proper file permissions. This means:

Files created inside the container will have the correct ownership on the host
No more root-owned files after container operations
Works across different environments (development, production servers)

The container detects the user ID from the mounted workspace volume. If needed, you can override the default values by setting environment variables:

# Set specific user ID and group ID before running docker-compose
export LOCAL_USER_ID=1000
export LOCAL_GROUP_ID=1000
docker-compose up

Or run with inline environment variables:

LOCAL_USER_ID=1000 LOCAL_GROUP_ID=1000 docker-compose up

The container runs as a non-root user named TSYS-Tools with the detected host user's UID/GID.

Data Processing Workflows

This container is designed to handle both:

GIS data processing (shapefiles, GeoJSON, Parquet, etc.)
Weather data processing (GRIB, NetCDF formats)
ETL workflows for geospatial and meteorological datasets
Integration with PostGIS for spatial database operations
Output to MinIO buckets for business use

Integration

Can be used in CTO mode for R&D activities
Compatible with existing documentation containers for report generation
Designed for both workstation prototyping and server deployment