EXERCISE for Remote Sensing Course

This repository contains the exercices for the EPFL Remote Sensing Course.

The exercises can be executed directly on the EPFL VMware Horizon platform. Please select the ENAC-SSIE-Ubuntu-20-04 Virtual Desktop Infrastructure (VDI) and then follow these steps:

1. Download the RS2025 GitHub repository

2. Unzip the RS2025-main.zip file and move the RS2025 directory within the /home/<your_username>/Desktop/myfiles/ directory. If your data are saved within the /myfiles directory, they will be available the next time you reconnect to the VDI.

3. Open a terminal and activate the lte environment with:

micromamba activate lte

4. Then create the lte ipykernel for Jupyter with:

python -m ipykernel install --user --name=lte

5. Launch the Jupyter Notebook interface with jupyter notebook, navigate to the RS2025 directory, and open the file Exercise_6.ipynb or Exercise_7.ipynb.

6. To execute correctly the Jupyter Notebook, in the top menu bar select Kernel > Change Kernel... and switch the kernel from Python 3 (ipykernel) to lte.
   Now you are ready to start the exercice !

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Alternatively, you can clone the RS2025 repository on your laptop and install the required environment using conda, mamba or micromamba:

1. Go to the directory where you want to clone the repository. As an example:

cd /home/ghiggi/courses

2. Clone this repository:

git clone [email protected]:ltelab/RS2025.git
cd RS2025

3. Install the dependencies using conda, mamba or micromamba:

micromamba env create -f environment.yml

4. Activate the lte conda environment:

micromamba activate lte

5. Create the lte ipykernel for Jupyter with:

python -m ipykernel install --user --name=lte

6. Launch the Jupyter Notebook interface with jupyter notebook, navigate to the RS2025 directory, and open the file Exercise_6.ipynb or Exercise_7.ipynb.

7. To execute correctly the Jupyter Notebook, in the top menu bar select Kernel > Change Kernel... and switch the kernel from Python 3 (ipykernel) to lte.
   Now you are ready to start the exercice !

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Note that the installation of the dependencies on your laptop might cause conflicts; in case you encounter such issues and cannot fix them, please contact the TA team.

The latest version of the required packages can be installed using the following command:

conda install numpy pandas xarray dask rasterio rioxarray scikit-learn matplotlib-base seaborn colorcet pywavelets pillow jupyter