Hbnyoni/uganda

Interpolation of machine learning variables # CHEAQI Uganda Spatial Analysis Workflow 🌍 **Comprehensive Environmental Health and Air Quality Indicators (CHEAQI) - Uganda Focus** Complete Docker-based spatial analysis workflow for processing environmental and health indicators across Uganda using advanced interpolation techniques and multi-temporal geostack creation. ## Features ### 🌟 Core Capabilities - **Web-based CSV Processing** - Simple interface for spatial interpolation - **Variable Selection Interface** - Choose coordinates and variables to interpolate - **Advanced Spatial Interpolation** - Kriging and IDW algorithms - **Interactive Configuration** - Point-and-click setup with validation - **Multiple Output Formats** - GeoTIFF files compatible with GIS software ### 📊 Supported Interpolation Methods - **Ordinary Kriging** - Optimal for spatially correlated data (recommended) - **Inverse Distance Weighting (IDW)** - Fast and robust for irregular data ### 🗂️ Input Data Requirements - CSV files with latitude/longitude coordinates - Numeric variables for interpolation - Geographic coordinate system (WGS84 recommended) - Minimum 10 data points for reliable interpolation ## Quick Start ### Option A: Local Development 1. **Build and start the service:** ```bash docker-compose up -d ``` ### Option B: Run from Dockstore ```bash # Install Dockstore CLI curl -L github.com -o dockstore chmod +x dockstore && sudo mv dockstore /usr/local/bin/ # Launch workflow from Dockstore dockstore workflow launch --entry github.com \ --json test-parameters.json ``` ### Option C: Direct Nextflow from Dockstore ```bash nextflow run dockstore.org \ -c uganda.config --input_csv data/Uganda_Daily.csv ``` ## Using the Web Interface 2. **Access the web interface:** - Open localhost in your browser 3. **Add your CSV data:** - Pla …