http://www.cnr.it/ontology/cnr/individuo/prodotto/ID41633
The effectiveness of airborne LiDAR data in the recognition of channel-bed morphology. (Articolo in rivista)
- Type
- Label
- The effectiveness of airborne LiDAR data in the recognition of channel-bed morphology. (Articolo in rivista) (literal)
- Anno
- 2008-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1016/j.catena.2007.11.001 (literal)
- Alternative label
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Cavalli M.; Tarolli P.; Marchi L.; Dalla Fontana G. (literal)
- Pagina inizio
- Pagina fine
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- http://www.sciencedirect.com/science/article/pii/S0341816207001841 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Rivista
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
- Note
- Scopus (literal)
- ISI Web of Science (WOS) (literal)
- Google Scholar (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- Marco Cavalli, Lorenzo Marchi: CNR-IRPI, Corso Stati Uniti 4, 35127 Padova, Italy; Paolo Tarolli, Giancarlo Dalla Fontana: Department of Land and Agroforest Environments University of Padova, Agripolis, viale dell'Università 16, 35020 Legnaro (PD), Italy (literal)
- Titolo
- The effectiveness of airborne LiDAR data in the recognition of channel-bed morphology. (literal)
- Abstract
- High-resolution topographic data have the potential to differentiate the main morphological features of a landscape. This paper analyses the capability of airborne LiDAR-derived data in the recognition of channel-bed morphology. For the purpose of this study, 0.5 m and 1 m resolution Digital Terrain Models (DTMs) were derived from the last pulse LiDAR data obtained by filtering the vegetation points. The analysis was carried out both at 1-D scale, i.e. along the longitudinal channel profile, and at 2-D scale, taking into account the whole extent of the channel bed. The 1-D approach analyzed the residuals of elevations orthogonal to the regression line drawn along the channel profile and the standard deviation of local slope. The 2-D analysis was based on two roughness indexes, consisting on the local variability of the elevation and slope of the channel bed. The study was conducted in a headwater catchment located in the Eastern Italian Alps. The results suggested a good capability of LiDAR data in the recognition of river morphology giving the potential to distinguish the riffle-pool and step-pool reaches. (literal)
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