Urban tree failure probability prediction based on dendrometric aspects and machine learning models

Danilo Samuel Jodas, Sergio Brazolin, Giuliana Del Nero Velasco, Reinaldo Araujo de Lima, Takashi Yojo, João Paulo Papa

Abstract: Highlights•To propose using machine learning models to predict the tree failure probability.•Instead of a simple classification approach, we propose a regression task for a broader assessment of the trees.•Evaluation of the internal aspects in the machine learning algorithms' effectiveness.•The dataset and an additional image set are made available for future research.