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Machine learning models of forest vulnerability to fires, windthrows and insect outbreaks

posted on 14.01.2021, 22:10 authored by Giovanni ForzieriGiovanni Forzieri, Guido CeccheriniGuido Ceccherini, Marco GirardelloMarco Girardello, Jonathan Spinoni, Luc Feyen, Henrik Hartmann, Pieter S.A. Beck, Gustau Camps-Valls, Gherardo ChiriciGherardo Chirici, ACHILLE MAURIACHILLE MAURI, Alessandro Cescatti

Forest disturbance regimes are expected to intensify as Earth’s climate changes. We investigated the vulnerability of European forests to fires, windthrows and insect outbreaks during the period 1979-2018 by integrating machine learning with disturbance data and satellite products. The proposed methodology is purely data-driven and therefore reproducible, applicable at large scales, and in line with the measurement/reporting/verification process of UNFCCC. Results of this study have been published in Forzieri et al. (2021).

Pre-processed data, codes and final vulnerability models developed in the afore-mentioned work are made publicly available here and briefly described to facilitate reproducibility and applicability.


The study was funded by the Exploratory Project FOREST@RISK of the European Commission, Joint Research Centre.