geeadvance 0.1.0

Advanced landscape metrics analysis using Google Earth Engine

🌍 GeeAdvance

GeeAdvance is a Python package for advanced landscape metrics analysis using Google Earth Engine (GEE). It implements landscape ecology metrics similar to the R landscapemetrics package, enabling comprehensive spatial pattern analysis of GEE-derived imagery and datasets.

🚀 Features

• 🔐 Standard GEE Authentication - Seamless integration with Google Earth Engine
• 📊 Comprehensive Landscape Metrics - Implementation of metrics from landscapemetrics
  • Area & Edge Metrics
  • Shape Metrics
  • Core Area Metrics
  • Aggregation Metrics
  • Diversity Metrics
• 🗺️ GEE Integration - Direct analysis of GEE imagery and datasets
• 📥 Export Capabilities - Download results as GeoTIFF and other formats
• 📚 Beginner-Friendly - Extensive tutorials and documentation

📦 Installation

pip install geeadvance

Or install from source:

git clone https://github.com/pulakeshpradhan/geeadvance.git
cd geeadvance
pip install -e .

🔑 Quick Start

1. Authenticate with Google Earth Engine

import ee
import geeadvance

# Standard GEE authentication
ee.Authenticate()
ee.Initialize(project='your-project-id')

2. Calculate Landscape Metrics

# Load a land cover dataset
dataset = geeadvance.load_dataset('MODIS/006/MCD12Q1', 
                                  start_date='2020-01-01',
                                  end_date='2020-12-31')

# Define region of interest
roi = ee.Geometry.Rectangle([77.0, 20.0, 78.0, 21.0])

# Calculate landscape metrics
metrics = geeadvance.calculate_metrics(dataset, roi, scale=500)

# Get specific metrics
area_metrics = geeadvance.area_metrics(dataset, roi)
shape_metrics = geeadvance.shape_metrics(dataset, roi)
diversity_metrics = geeadvance.diversity_metrics(dataset, roi)

print(metrics)

3. Export Results

# Export as GeoTIFF
geeadvance.export_tif(dataset, roi, 'output_landcover.tif')

# Export metrics as CSV
metrics.to_csv('landscape_metrics.csv')

📖 Documentation

Full documentation is available at: https://pulakeshpradhan.github.io/geeadvance/

🎓 Tutorials

Check out our beginner-friendly tutorials:

1. Getting Started with GEE Authentication
2. Loading and Visualizing GEE Datasets
3. Calculating Area and Edge Metrics
4. Shape and Core Metrics
5. Aggregation and Diversity Metrics
6. Exporting Data and Results
7. Complete Workflow Example

🌟 Implemented Metrics

Area & Edge Metrics

• CA - Class Area
• PLAND - Percentage of Landscape
• TE - Total Edge
• ED - Edge Density

Shape Metrics

• SHAPE - Shape Index
• FRAC - Fractal Dimension
• PARA - Perimeter-Area Ratio
• CIRCLE - Related Circumscribing Circle

Core Area Metrics

• TCA - Total Core Area
• CPLAND - Core Area Percentage of Landscape
• CAI - Core Area Index

Aggregation Metrics

• AI - Aggregation Index
• CLUMPY - Clumpiness Index
• COHESION - Patch Cohesion Index
• DIVISION - Landscape Division Index

Diversity Metrics

• SHDI - Shannon's Diversity Index
• SHEI - Shannon's Evenness Index
• SIDI - Simpson's Diversity Index

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

👤 Author

Pulakesh Pradhan

• Email: [e-mail]
• GitHub: @pulakeshpradhan

🙏 Acknowledgments

• Inspired by the R landscapemetrics package
• Built on Google Earth Engine

📚 Citation

If you use this package in your research, please cite:

@software{geeadvance2026,
  author = {Pradhan, Pulakesh},
  title = {GeeAdvance: Landscape Metrics for Google Earth Engine},
  year = {2026},
  url = {https://github.com/pulakeshpradhan/geeadvance}
}