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arXiv · 2403.13545

Next day fire prediction via semantic segmentation

Konstantinos Alexis·Stella Girtsou·Alexis Apostolakis·Giorgos Giannopoulos·Charalampos Kontoes
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Abstract

In this paper we present a deep learning pipeline for next day fire prediction. The next day fire prediction task consists in learning models that receive as input the available information for an area up until a certain day, in order to predict the occurrence of fire for the next day. Starting from our previous problem formulation as a binary classification task on instances (daily snapshots of each area) represented by tabular feature vectors, we reformulate the problem as a semantic segmentation task on images; there, each pixel corresponds to a daily snapshot of an area, while its channels represent the formerly tabular training features. We demonstrate that this problem formulation, built within a thorough pipeline achieves state of the art results.

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Konstantinos Alexis, Stella Girtsou, Alexis Apostolakis, Giorgos Giannopoulos, Charalampos Kontoes. 2024-03-20. Next day fire prediction via semantic segmentation. https://arxiv.org/abs/2403.13545

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