GIS Playground

GIS Playground is a comprehensive web-based GIS application that combines multiple data sources and provides advanced spatial data visualization and analysis capabilities. The application features real-time wildfire data integration, intelligent spatial data processing, and interactive mapping functionality, making it a versatile tool for geographic data exploration and analysis.

Features

Data Integration

• Real-time wildfire data from ESRI's feature services
• Support for multiple spatial file formats:
  • Shapefiles
  • GeoJSON
  • CSV (with spatial coordinates)
  • GeoPackage
• Custom Layer visualization
• Multiple base map options

Intelligent Processing

• AI-assisted layer naming and description generation
• Automated data quality analysis
• Spatial clustering for large datasets
• Smart attribute analysis and validation

Data Management

• Automated CRS standardization
• Geometry validation and repair
• Multi-layer GeoPackage support
• Comprehensive error handling and validation

Visualization

• Interactive map interface
• Dynamic layer toggling
• Feature property inspection
• Custom styling options

Prerequisites

• Python 3.8+
• PostgreSQL with PostGIS extension
• GDAL/OGR libraries

Installation

1. Clone the repository:

git clone https://github.com/yourusername/gis-playground.git
cd gis-playground

2. Create and activate a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install required packages:

pip install -r requirements.txt

Project Structure

• app/: Source code directory
  • database/: Data processing and management
  • models/: API interaction
  • routes/: API interaction
  • static/: Static files (CSS, JS, Images)
  • templates/: HTML templates
  • init.py: Package initialization
• config/: Configuration files
• data/: Raw and processed data storage
• logs/: Log files
• processors/: Data processing scripts
  • File type-specific processors (Shapefile, CSV, GeoJSON, GeoPackage)
• tools/: Geoprocessing tools
  • validation/: Geometry and attribute validation
  • conversion/: CRS and format conversion
  • analysis/: Spatial analysis tools
  • ai/: AI-assisted processing tools
• utils/: Utility functions
• requirements.txt: List of dependencies
• README.md: Project documentation
• manage.py: Database management commands
• run.py: Main Flask application

Key Components

Data Processors

• Shapefile Processor: Handles ESRI Shapefile processing
• CSV Processor: Processes CSV files with spatial coordinates
• GeoJSON Processor: Manages GeoJSON file processing
• GeoPackage Processor: Handles multi-layer GeoPackage files

Tools

• Geometry Validation: Ensures spatial data integrity
• CRS Conversion: Standardizes coordinate reference systems
• Smart Processing: AI-assisted data analysis and naming

Usage

1. Start the Flask development server:

python run.py

2. Open your web browser and navigate to http://localhost:5000

3. Upload spatial data through the interface:

   • Supports multiple file formats
   • Automatic processing and validation
   • AI-assisted naming and description
   • Quality analysis reporting

Future Enhancements

• Census data integration
• Advanced spatial analysis tools
• Custom styling interface
• Batch processing capabilities
• Enhanced AI features

Acknowledgments

• ESRI for real-time wildfire data
• OpenStreetMap contributors
• Leaflet.js community
• GDAL/OGR project

Additional Resources

• Leaflet Documentation
• PostGIS Documentation
• GDAL/OGR Documentation
• Leaflet Providers