Alps Data Explorer

The purpose of this repository is to be a data exploration playground for data related to the project "Decoding Rain-on-Snow Flooding using Statistics and Satellite Data". See more about this project at the project website, https://rainonsnow.vincenzocoia.com/.

Dependencies

I'm using python for obtaining the data and visualizing it. I've created a conda environment that you can reproduce from the environment.yml file by executing the command:

conda env create -f environment.yml

The environment is named alps-data-explorer, like this repository.

Workflow

The main idea behind the codebase:

• Access satellite data programmatically using Google Earth Engine and XEE.
• Wrangle the data using xarray.
• Display slices of data by deploying an interactive streamlit app, where users can specify what "slice" of the data they want (what pixel? what data aggregation -- max? What time range?)

Project Structure

The codebase follows a modular architecture for both interactive exploration and web deployment:

├── config.py          # Centralized configuration and defaults
├── core.py            # Core analysis functions (UI-agnostic)
├── app.py             # Clean Streamlit web application
├── explore.ipynb      # Jupyter notebook for interactive exploration
├── utils/             # Statistical utility functions
│   ├── __init__.py
│   └── stats.py       # Custom statistical functions (nscore, etc.)
└── environment.yml    # Conda environment specification

Usage

Interactive Exploration (Recommended)

# Launch Jupyter for data exploration
jupyter lab explore.ipynb

Web Application

# Launch Streamlit web app
streamlit run app.py

Contributing

This project is open source and welcomes contributions. Please see the contributing guide and the code of conduct.