Luca Maffeo Albertelli

Dr. Luca Maffeo Albertelli

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Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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27 December 2024 in Journal of Mountain Science
Verified
Journal Article
Closed access
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BTBattista Taboni
Battista Taboni
Gessica UmiliGessica Umili
Gessica Umili
Luca Maffeo AlbertelliLuca Maffeo Albertelli
Luca Maffeo Albertelli
ITIuri D. Tagliaferri
Iuri D. Tagliaferri

7 November 2025 in Remote Sensing
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Journal Article
Open access
PDF file
Bianca VoglinoBianca Voglino
Bianca Voglino
Danilo GodoneDanilo Godone
Danilo Godone
MBMarco Baldo
Marco Baldo
BBBarbara Bono
Barbara Bono
Fabio LuinoFabio Luino
Fabio Luino
LAURA TURCONILAURA TURCONI
LAURA TURCONI
Detecting topographic change in mountainous areas using historical aerial imagery is challenging due to complex terrain and variable data quality. This study evaluates the potential of Structure from Motion (SfM) for deriving 3D information from archival photograms in the Rabbia basin (Central Italian Alps), a catchment with a well-documented history of debris flow activity. The aim is to assess the impact of input configurations and photogrammetric processing strategies on the quality and interpretability of 3D reconstructions from historical aerial imagery, as a basis for further geomorphological analyses. A 1999 aerial dataset was processed via SfM workflow to generate a point cloud and orthomosaic, and then co-registered with a 2021 LiDAR-derived dataset. Multi-temporal analysis was conducted using point cloud distance computations and visual interpretation of orthomosaics. Additional aerial images spanning nearly 80 years expanded the temporal scale of the analysis, providing valuable retrospective insight into long-term terrain evolution. The results, although considered semi-quantitative due to data quality limitations, are consistent with geomorphological trends in the area. The study confirms that historical SfM-derived products, when supported by robust co-registration and quality checks, can contribute to sediment dynamics and hazard evaluation in alpine environments, though result interpretation should remain cautious due to dataset-specific uncertainties.