Valeria Longhi
Bathymetry estimation of a shallow proglacial lake through UAV imagery and a geospatial regression method.
Rel. Stefania Tamea, Carlo Vincenzo Camporeale. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Per L'Ambiente E Il Territorio, 2023
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Abstract
Proglacial areas are one of the most rapidly changing ecosystems due to glacier and permafrost degradation. To better understand these environments and their dynamics, bathymetric mapping is a necessary step in hydraulic modelling. This is essential for assessing water quality, sediment and pollutant movement, and evaluating habitats. This thesis aims to evaluate the effectiveness of a geographically weighted regression (GWR) model, which can capture a spatially heterogeneous relationship between inputs and an output, to retrieve bathymetry of a shallow proglacial lake, of which water depth is less than about 1 m, from RGB and multispectral imagery. The case study is a system of proglacial channelized streams joining in a shallow lake originating from the melting of the Rutor alpine glacier, in Valle d’Aosta.
Field experiments were carried out during summer 2021 and 2023 for GNSS positioning along different sections of the streams and simultaneously for acquiring photogrammetric data with digital numbers (DN) using an uncrewed aerial vehicle (UAV)
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