Jupyter Notebooks
Interactive Jupyter notebooks demonstrating Open Geodata API usage.
Available Notebooks
Quick Start
To run these notebooks:
Install Jupyter:
pip install jupyter
pip install open-geodata-api[complete]
Download notebooks from the examples repository
Start Jupyter:
jupyter notebook
Notebook Descriptions
- Sentinel-2 Analysis
Complete workflow for Sentinel-2 data analysis including NDVI calculation, cloud masking, and time series analysis.
- Landsat Time Series
Long-term analysis using Landsat archive data, demonstrating change detection and trend analysis techniques.
- Multi-Provider Comparison
Side-by-side comparison of data from Planetary Computer and EarthSearch, including data quality assessment and availability analysis.
Requirements
All notebooks require:
Python 3.8+
Jupyter notebook or JupyterLab
open-geodata-api[complete] (includes rioxarray, geopandas)
Additional packages: matplotlib, seaborn, plotly (for visualizations)
Optional for enhanced functionality:
stackstac (for efficient array stacking)
planetary-computer (for PC authentication)
folium (for interactive maps)
Installation command:
pip install open-geodata-api[complete] matplotlib seaborn plotly folium stackstac
Interactive Features
The notebooks include:
✅ Interactive widgets for parameter adjustment ✅ Progressive examples from basic to advanced ✅ Error handling and troubleshooting tips ✅ Visualization galleries with various plot types ✅ Performance comparisons between different approaches ✅ Best practices and optimization techniques
Contributing Notebooks
We welcome contributions of new notebooks! Please see the Contributing to Open Geodata API guide for details on:
Notebook structure and formatting
Required documentation
Testing procedures
Submission process
The notebooks repository accepts examples for:
Domain-specific applications
Integration with new libraries
Performance optimization techniques
Educational tutorials