Upper forestline dynamics in the Italian Alps and Apennines revealed by Landsat time-series

Abstract ID: 3.12598 | Accepted as Talk | Talk | TBA | TBA

Lorena Baglioni (0)
Morresi, Donato (1), Garbarino, Matteo (2), Urbinati, Carlo, Lingua, Emanuele (3), Marzano, Raffaella (2), Vitali, Alessandro
Lorena Baglioni ((0) Marche Polythecnic University, Via Brecce Bianche, 10, 60131, Ancona, Italy, IT)
Morresi, Donato (1), Garbarino, Matteo (2), Urbinati, Carlo, Lingua, Emanuele (3), Marzano, Raffaella (2), Vitali, Alessandro

(0) Marche Polythecnic University, Via Brecce Bianche, 10, 60131, Ancona, Italy, IT
(1) Swedish University of Agricultural Sciences, Skogsmarksgränd, SE-901 83 Umeå, Sweden
(2) University of Turin, Largo Paolo Braccini 2, 10095, Grugliasco (TO), Italy
(3) University of Padova, Viale dell'Università 16, 35020, Legnaro (PD), Italy

(1) Swedish University of Agricultural Sciences, Skogsmarksgränd, SE-901 83 Umeå, Sweden
(2) University of Turin, Largo Paolo Braccini 2, 10095, Grugliasco (TO), Italy
(3) University of Padova, Viale dell'Università 16, 35020, Legnaro (PD), Italy

Categories: Biodiversity, Ecosystems, ES-Forests, Remote Sensing
Keywords: remote sensing, Contextual Mann Kendall, treeline ecotones, Alps, Apennines

Categories: Biodiversity, Ecosystems, ES-Forests, Remote Sensing
Keywords: remote sensing, Contextual Mann Kendall, treeline ecotones, Alps, Apennines

The interest on the ecological effects of global warming and land use changes on vegetation, combined with the increasing development of remote sensing techniques, have fostered the research about the successional dynamics at the upper forest ecotones . In this context, the aims of this study are: i) to define an automatic approach for mapping the current position of the most representative upper forestlines in the Alps and Apennines (Italy); ii) to detect and assess the long-term spectral changes at their ecotones using Landsat-based trend analysis; iii) to appraise the performance of greenness and wetness indices along a forestline buffer which includes the closed forest below and the ecotone above it. We used a regional scale approach to make the method replicable in different geographic areas. We calculated spectral greenness and wetness vegetation indices from Landsat timeseries for the period 1984 – 2023 and tested the significance of their long-term spectral trends with the Contextual Mann-Kendall test for monotonicity. Our results show an overall increasing trend, mainly close to the forestline ecotone and at lower elevations inside the buffer. Comparing the relative trends with the current canopy cover, we found in the Alps the highest values of greenness and wetness trends in the sparse and dense cover class respectively, as a result of encroachment and gap filling dynamics. We plan to analyse the detected trends integrating the Landsat data with others at higher-resolution to better assess the effect of structure and site-specific drivers.

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