Bathymetric Detection of Fluvial Environments through UASs and Machine Learning Systems
| Autor: | Grasso Nives, Pontoglio Emanuele, Lingua Andrea Maria, Camporeale Carlo, Cagninei Andrea, Dabove Paolo |
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| Rok vydání: | 2020 |
| Předmět: |
010504 meteorology & atmospheric sciences
0208 environmental biotechnology Geomatics bathymetry Point cloud Fluvial 02 engineering and technology photogrammetry Machine learning computer.software_genre 01 natural sciences Set (abstract data type) Bathymetry lcsh:Science 0105 earth and related environmental sciences UAS environment artificial intelligence business.industry Vegetation 020801 environmental engineering Identification (information) Photogrammetry General Earth and Planetary Sciences lcsh:Q Artificial intelligence business Environment computer Geology |
| Zdroj: | Remote Sensing, Vol 12, Iss 4148, p 4148 (2020) Remote Sensing; Volume 12; Issue 24; Pages: 4148 |
| ISSN: | 2072-4292 |
| Popis: | In recent decades, photogrammetric and machine learning technologies have become essential for a better understanding of environmental and anthropic issues. The present work aims to respond one of the most topical problems in environmental photogrammetry, i.e., the automatic classification of dense point clouds using the machine learning (ML) technology for the refraction correction on the fluvial water table. The applied methodology for the acquisition of multiple photogrammetric flights was made through UAV drones, also in RTK configuration, for various locations along the Orco River, sited in Piedmont (Italy) and georeferenced with GNSS—RTK topographic method. The authors considered five topographic fluvial cross-sections to set the correction methodology. The automatic classification in ML has found a valid identification of different patterns (Water, Gravel bars, Vegetation, and Ground classes), in specific hydraulic and geomatic conditions. The obtained results about the automatic classification and refraction reduction led us the definition of a new procedure, with precise conditions of validity. |
| Databáze: | OpenAIRE |
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