ISOFIT Tutorials

Welcome to the ISOFIT tutorials repository! This repository contains a collection of Jupyter notebooks that serve as tutorials, examples, and further documentation for the ISOFIT project. These notebooks are designed to work seamlessly with the official ISOFIT Docker image, ensuring a hassle-free setup process.

ISOFIT is a powerful tool for atmospheric correction of remote sensing data, particularly hyperspectral data. These notebooks provide step-by-step guides and demonstrations on using ISOFIT for atmospheric correction, making it easier for users to understand and utilize the capabilities of the ISOFIT software.

Getting Started

To get started with the ISOFIT Jupyter Notebooks, follow these simple steps:

1. Pull the Official ISOFIT Docker Image: The notebooks are designed to work with the official ISOFIT Docker image, which ensures a consistent environment. You can pull the image using the following command:

   docker pull jammont/isofit:latest

2. Clone This Repository: Clone this repository to your local machine using the following command:

   git clone https://github.com/isofit/isofit-tutorials.git

3. Run the Docker: Create a container from the image and attach the tutorials directory:

   docker run --rm --shm-size=9.58gb -p 8888:8888 -v isofit-tutorials:/home/ray/isofit isofit/v2

   This command will start a Jupyter Notebook server inside the Docker container and make it accessible on your host machine.

4. Launch Jupyter Notebooks: Run a Docker container using the pulled image, and forward the Jupyter Notebook port (usually 8888) to your local machine:

   docker run -it -p 8888:8888 -v $(pwd):/workspace isofit/isofit:latest jupyter notebook --ip 0.0.0.0

   This command will start a Jupyter Notebook server inside the Docker container and make it accessible on your host machine.

5. Access Notebooks: Open your web browser and navigate to http://localhost:8888. You should see the Jupyter Notebook interface. Navigate to the notebooks directory and start exploring the ISOFIT tutorials!

Contents

This repository contains the following tutorials:

• NEON: Step-by-step tutorial showcasing building a surface model, using apply_oe to generate defaults, then executing and improving ISOFIT results using NEON data

Feel free to explore, learn, and adapt the provided notebooks to your specific use cases.

Contributing

We welcome contributions from the community! If you find any issues, have suggestions for improvements, or want to add your own tutorials/examples, please feel free to open an issue or submit a pull request.

License

The ISOFIT Jupyter Notebooks project is licensed under the Apache v2.0 License.