Hotspot disambiguation dataset
This repository contains the dataset assembled as part of a work A Multimodal Supervised Machine Learning Approach for Satellite-based Wildfire Identification in Europe. Tha paper has been presented at the International Geoscience and Remote Sensing Symposium (IGARSS) 2023. The full paper is available at https://arxiv.org/abs/2308.02508 .
The data folder contains two files:
dataset.csv: this file contains the full cross-referenced dataset, obtained by conducing a temporal and spatial data intersection between the EFFIS burned areas and the MODIS/VIIRS hotspots.dataset_500.csv: this file contains a subset of the previous dataset (~500k data points), subsampled to obtain a dataset stratified with respect to the spatial distribution, and with a positive-negative proportion of 10%-90%. In addition to MODIS/VIIRS data points, additional columns have been added to improve the models' performances. This file is the one used to obtain the results showed in the paper.
Code
The code and models used in this work are available at https://github.com/links-ads/hotspot-disambiguation .
Contributions
- Angelica Urbanelli (angelica.urbanelli@linksfoundation.com)
- Luca Barco (luca.barco@linksfoundation.com)
- Edoardo Arnaudo (edoardo.arnaudo@polito.it | linksfoundation.com)
- Claudio Rossi (claudio.rossi@linksfoundation.com)
BibTex
@inproceedings{urbanelli2023hotspot,
title={A Multimodal Supervised Machine Learning Approach for Satellite-based Wildfire Identification in Europe},
author={Urbanelli, Angelica and Barco, Luca and Arnaudo, Edoardo and Rossi, Claudio},
booktitle={2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS},
year={2023}
}
Licence
cc-by-4.0
Acknowledgments
This work was carried out in the context of two H2020 projects: SAFERS (GA n.869353) and OVERWATCH (GA n.101082320), and presented at IGARSS 2023.