Processing Scripts of the ALPACA Dataset

This repository [1] includes various processing scripts of the ALPACA dataset [2] for hyperspectral and soil moisture data. The studies are published in [3].

We can not guarantee completeness or correctness of the code. If you find bugs or if you have suggestions on how to improve the code, we encourage you to post your ideas as GitHub issue.

License:	3-Clause BSD license
Author:	Felix M. Riese
Requirements:	Python 3 with these packages
Citation:	see Citation and in the bibtex file

Workflow

1. Process Soil Moisture Data
2. Process Full Dataset
3. Dataset Shift Detection
4. Estimation (Original Data)
5. Estimation (Monte Carlo)
6. Plots

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Citation

Code:

[1] F. M. Riese, "Processing Scripts for the ALPACA Dataset," Zenodo, 2020. DOI:10.5281/zenodo.3871459

@misc{riese2020processing,
    author = {Riese, Felix~M.},
    title = {{Processing Scripts for the ALPACA Dataset}},
    year = {2020},
    doi = {10.5281/zenodo.3871459},
    publisher = {Zenodo},
}

Dataset:

[2] F. M. Riese, S. Schroers, J. Wienhöfer, and S. Keller "Aerial Peruvian Andes Campaign (ALPACA) Dataset 2019," KITopen, 2020. DOI:10.5445/IR/1000118082

@misc{riese2020aerial,
    author = {Riese, Felix~M. and Schroers, Samuel and Wienh{\"o}fer, Jan and Keller, Sina},
    title = {Aerial Peruvian Andes Campaign (ALPACA) Dataset 2019},
    year = {2020},
    doi = {10.5445/IR/1000118082},
    organization = {KITopen},
}

Code is Supplementary Material to

[3] Felix M. Riese. "Development and Applications of Machine Learning Methods for Hyperspectral Data." PhD thesis. Karlsruhe, Germany: Karlsruhe Institute of Technology (KIT), 2020. DOI:10.5445/IR/1000120067

@phdthesis{riese2020development,
    author = {Riese, Felix~M.},
    title = {{Development and Applications of Machine Learning Methods for Hyperspectral Data}},
    school = {Karlsruhe Institute of Technology (KIT)},
    year = {2020},
    address = {Karlsruhe, Germany},
    doi = {10.5445/IR/1000120067},
}