This repository contains the code developed within the framework of the paper A Multimodal Supervised Machine Learning Approach for Satellite-based Wildfire Identification in Europe presented at the International Geoscience and Remote Sensing Symposium (IGARSS) 2023. The full paper is available at https://arxiv.org/abs/2308.02508 .
The dataset was assembled as part of a work project, by cross-referencing multiple data sorces. The data are availabe through the Huggingface platform at https://huggingface.co/datasets/links-ads/hotspot-dataset .
- 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)
@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}
}
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.