The growing interest on the ecological effects of global warming and land use changes on vegetation, along with the development of remote sensing techniques, fostered applied research on the successional dynamics at the upper limits of forests. The aims of this study are (i) to develop an automated methodology for mapping the current position of the uppermost Italian forestlines and (ii) to identify hotspots of change by the analysis of long-term greenness and wetness spectral dynamics. We carried out a Landsat-based trend analysis in buffer zones along the forestlines, testing differences between sparse and dense canopy cover classes and at different elevations and distances to the forestline. We used regional-scale datasets and avoided to fix a minimum elevation threshold for the detection in order to make the method replicable in different mountain ranges. For the spectral dynamics analyses, we used Landsat time series of common vegetation indices for the period 1984-2023 and tested the significance of their long-term spectral trends with the contextual Mann-Kendall test for monotonicity. We determined that the highest forestlines are located in the western Alps for the Alps mountain range and in the central sector for the Apennines. We observed a general expansion of the forest cover mainly close to the forestline and at lower elevations. The highest values of greenness and wetness indices were, respectively, in the sparse tree cover class and in the dense one, particularly in the Alps.

Forestlines in Italian mountains are shifting upward: detection and monitoring using satellite time series

Lingua E.;
2025

Abstract

The growing interest on the ecological effects of global warming and land use changes on vegetation, along with the development of remote sensing techniques, fostered applied research on the successional dynamics at the upper limits of forests. The aims of this study are (i) to develop an automated methodology for mapping the current position of the uppermost Italian forestlines and (ii) to identify hotspots of change by the analysis of long-term greenness and wetness spectral dynamics. We carried out a Landsat-based trend analysis in buffer zones along the forestlines, testing differences between sparse and dense canopy cover classes and at different elevations and distances to the forestline. We used regional-scale datasets and avoided to fix a minimum elevation threshold for the detection in order to make the method replicable in different mountain ranges. For the spectral dynamics analyses, we used Landsat time series of common vegetation indices for the period 1984-2023 and tested the significance of their long-term spectral trends with the contextual Mann-Kendall test for monotonicity. We determined that the highest forestlines are located in the western Alps for the Alps mountain range and in the central sector for the Apennines. We observed a general expansion of the forest cover mainly close to the forestline and at lower elevations. The highest values of greenness and wetness indices were, respectively, in the sparse tree cover class and in the dense one, particularly in the Alps.
2025
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3588678
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