CRAU Review

This repository contains the CRAU Review project, which includes data analysis, results, and code for evaluating cloud mask and ET quicklook methods.

Repository Structure

Contains various datasets used for the analysis:

• data/
  • 2016_all_models_HUC8_WB.csv
  • et_2016.csv
  • usgs_water_watch_runoff_mm_WY.csv
  • 2018_final_combined_HUC8_WB.csv
  • 2009_final_combined_HUC8_WB.csv
  • 2013_final_combined_HUC8_WB.csv
  • et_2011.csv
  • et_2013.csv
  • et_2009.csv
  • 2011_final_combined_HUC8_WB.csv
  • et_2018.csv

Contains the results of the analysis:

• results/
  • crau/

Contains source code for data processing and analysis:

• src/
  • review_tools.py
  • review_tools_new.py

Contains Jupyter notebooks for testing and analysis:

• testing/
  • landsat_c2_sr_cloud_mask.ipynb
  • ETquicklook.ipynb

Getting Started

Prerequisites

Ensure you have the following software installed:

• Python 3.x
• Jupyter Notebook
• Necessary Python packages (listed in requirements.txt if available)

Installation

1. Clone the repository:

git clone https://github.com/Open-ET/CRAU-Review.git
cd CRAU-Review

2. Install the required Python packages:

pip install -r requirements.txt

Usage

To explore the datasets, navigate to the data/ directory and open the relevant CSV files.

To run the Jupyter notebooks for analysis:

jupyter notebook testing/landsat_c2_sr_cloud_mask.ipynb
jupyter notebook testing/ETquicklook.ipynb

Source code for data processing and analysis can be found in the src/ directory. You can run the Python scripts directly or import the functions in your own scripts.

Contributing

If you would like to contribute to this project, please follow these steps:

Fork the repository.

Create a new branch (git checkout -b feature-branch). Make your changes and commit them (git commit -am 'Add new feature'). Push to the branch (git push origin feature-branch). Create a new Pull Request.

Acknowledgements

AJ Purdy