Vol. 77 No. 1 (2022)
Articles

Automatic mapping of Italian forest disturbances between 1985 and 2019 using Landsat imagery and Google Earth Engine

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  • Saverio Francini,
  • Costanza Borghi,
  • Giovanni D'Amico,
  • Stefano Santi,
  • Davide Travaglini
Saverio Francini
Dipartimento di Scienze e Tecnologie Agrarie, Alimentari, Ambientali e Forestali, Università degli Studi di Firenze, Via San Bonaventura, 13 - 50145 Firenze, Italy.
Costanza Borghi
Dipartimento di Scienze e Tecnologie Agrarie, Alimentari, Ambientali e Forestali, Università degli Studi di Firenze, Via San Bonaventura, 13 - 50145 Firenze, Italy.
Giovanni D'Amico
Dipartimento di Scienze e Tecnologie Agrarie, Alimentari, Ambientali e Forestali, Università degli Studi di Firenze, Via San Bonaventura, 13 - 50145 Firenze, Italy.
Stefano Santi
Dipartimento di Scienze e Tecnologie Agrarie, Alimentari, Ambientali e Forestali, Università degli Studi di Firenze, Via San Bonaventura, 13 - 50145 Firenze, Italy.
Davide Travaglini
Dipartimento di Scienze e Tecnologie Agrarie, Alimentari, Ambientali e Forestali, Università degli Studi di Firenze, Via San Bonaventura, 13 - 50145 Firenze, Italy.
DOI: https://doi.org/10.36253/ifm-1616

Published 2022-03-30

Keywords

  • remote sensing,
  • algorithms,
  • forest disturbance
Copyright Notice

Abstract

Forests play a key role in the carbon cycle and the fight against climate change. Long-term monitoring of forest dynamics represents a key element for understanding forests transformations due to forest harvestings and disturbances including fires, wind storms, frost or drought events, and pathogen attacks. This work aims at mapping and evaluating the forest disturbances that have occurred in Italy since 1985, using Landsat satellite imagery and apposite algorithms. We predicted about 1.8 million forest disturbances occurring during the observation period. Disturbances ranged between 27.923 ha in 2014 and 261.733 ha in 1985. Most of the forest disturbances have been identified in Sicilia and Calabria. Commission errors fluctuated between 29% in 2012 and 65% in 2001 while omission errors were between 8% in 2014 and 88% in 2003. The results that we present in this work can increase our understanding of Italian forests, and serve as basis for future research, while the methodology we applied can support the production of official statistics on forest disturbances.

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