Forest ecosystems have a crucial role for biodiversity conservation, providing a large set of ecosystem services. Understanding and assessing forest disturbance regimes on a large spatial and temporal scale is a prerequisite setting up sustainable forest management solutions. In this context, Remote Sensing is an efficient tool frequently used in land-use change detection. The present work is aimed at spatially estimating forest disturbing events occurred in Italy in the period 1985-2019. Using Landsat time series and the 3I3D forest disturbance detection algorithm, we analyzed “extreme” forest disturbance patterns and their evolution in the last 35 years. We found a total of 472 events, with the highest incidence (96) in the period 1990-1994. The accuracy of the 3I3D algorithm was estimated using a photo-interpreted dataset of nine random-sampled squared cells of 225 km2 each, distributed in the Italian region. Omission error for the 3I3D map ranged from a minimum of 37.43% to a maximum of 64.62% (mean value of 47.07%) while the commission error between 36.80% and 83.92%, with an average of 49.60%. Results suggest that occurrence of severe disturbance events do not seem to increase over time in the study period.

MONITORING THIRTY-FIVE YEARS OF ITALIAN FOREST DISTURBANCE USING LANDSAT TIME SERIES

Francini S.;Travaglini D.;Marchetti M.;Tonti D.;Ottaviano M.;Vangi E.;D'amico G.;Chirici G.
2021-01-01

Abstract

Forest ecosystems have a crucial role for biodiversity conservation, providing a large set of ecosystem services. Understanding and assessing forest disturbance regimes on a large spatial and temporal scale is a prerequisite setting up sustainable forest management solutions. In this context, Remote Sensing is an efficient tool frequently used in land-use change detection. The present work is aimed at spatially estimating forest disturbing events occurred in Italy in the period 1985-2019. Using Landsat time series and the 3I3D forest disturbance detection algorithm, we analyzed “extreme” forest disturbance patterns and their evolution in the last 35 years. We found a total of 472 events, with the highest incidence (96) in the period 1990-1994. The accuracy of the 3I3D algorithm was estimated using a photo-interpreted dataset of nine random-sampled squared cells of 225 km2 each, distributed in the Italian region. Omission error for the 3I3D map ranged from a minimum of 37.43% to a maximum of 64.62% (mean value of 47.07%) while the commission error between 36.80% and 83.92%, with an average of 49.60%. Results suggest that occurrence of severe disturbance events do not seem to increase over time in the study period.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11695/130832
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