The paper describes an efficient workflow wherein UAV photogrammetry is combined with other 3D survey techniques (terrestrial photogrammetry, laser scanning and total station) to provide comprehensive documentation of a historical building. The output orthoimage of the tiled roof allowed high-lighting the covering damage state. The research aims to test and evaluate the feasibility of automatically mapping roof damage using an image classification procedure based on supervised machine learning. The methodology was validated on a historical building, now suffering from a serious state of neglect.
Aerial-photogrammetric survey for supervised classification and mapping of roof damages
FAUSTA FIORILLO;LUCA PERFETTI;GIULIANA CARDANI
2022-01-01
Abstract
The paper describes an efficient workflow wherein UAV photogrammetry is combined with other 3D survey techniques (terrestrial photogrammetry, laser scanning and total station) to provide comprehensive documentation of a historical building. The output orthoimage of the tiled roof allowed high-lighting the covering damage state. The research aims to test and evaluate the feasibility of automatically mapping roof damage using an image classification procedure based on supervised machine learning. The methodology was validated on a historical building, now suffering from a serious state of neglect.File in questo prodotto:
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