LXG

This repository provides the R code to reproduce the computational analysis of the paper: "Logistic regression versus machine learning for detecting burned areas using satellite images" (Militino et al., 2023).

Table of contents

• R code
• Additional data

R code

The script LXG_terra.R contains the implementation of the models described in the paper.

Additional data

The Data/ folder contains the following:

• MODIS_DataSet.tif: This file contains the raster data set used to compare the described models.

• acc_metrics.RData: This file comprises R objects that store the accuracy metrics for every simulation conducted.

Acknowledgements

This work has been funded by the project PID 2020-113125RB-I00 of the Spanish Research Agency (MCIN/ AEI/ 10.13039/501100011033) and Ayudas predoctorales UPNA 2022-2023.

References

Militino, A. F., Goyena, H., Pérez-Goya, U. and Ugarte, M.D (2024). Logistic regression versus machine learning for detecting burned areas using satellite images Environmental and Ecological Statistics, https://doi.org/10.1007/s10651-023-00590-7.