PORTO @ 
Archivio Istituzionale della Ricerca
IRIS è la soluzione IT che facilita la raccolta e la gestione dei dati relativi alle attività e ai prodotti della ricerca. Fornisce a ricercatori, amministratori e valutatori gli strumenti per monitorare i risultati della ricerca, aumentarne la visibilità e allocare in modo efficace le risorse disponibili.
EnglishGNSS Reflectometry (GNSS-R) is a consolidated remote sensing technique that exploits the back-scattered GNSS signals to retrieve information about the Earth surface. By the use of GNSS-R sensors onboard UAVs, this tool can bring significant advantages in agriculture, especially for the detection of the presence of water/moisure in specific rural areas. However, to perform this detection, GNSS-R needs a priori calibration of a threshold on the received reflected power in order to distinguish the presence/no prence of water. This is a limitation for the adoption of this approach at large scale. The work presented in this paper aims at overcoming such a limitation, proposing a novel approach based on artificial intelligence for the automatic water detection on the Earth surface, avoiding a priori, empirical, thresholding.
Scheda prodotto non validato
Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo
| Titolo: | Detecting water using UAV-based GNSS-Reflectometry data and Artificial Intelligence |
| Autori: | |
| Data di pubblicazione: | 2019 |
| Abstract: | GNSS Reflectometry (GNSS-R) is a consolidated remote sensing technique that exploits the back-sca...ttered GNSS signals to retrieve information about the Earth surface. By the use of GNSS-R sensors onboard UAVs, this tool can bring significant advantages in agriculture, especially for the detection of the presence of water/moisure in specific rural areas. However, to perform this detection, GNSS-R needs a priori calibration of a threshold on the received reflected power in order to distinguish the presence/no prence of water. This is a limitation for the adoption of this approach at large scale. The work presented in this paper aims at overcoming such a limitation, proposing a novel approach based on artificial intelligence for the automatic water detection on the Earth surface, avoiding a priori, empirical, thresholding. |
| ISBN: | 978-1-7281-3611-0 |
| Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
File in questo prodotto:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| Favenza2019detecting_MetroAgriFor_NoCopyrightSign.pdf | Final Submitted version of the article. | 2. Post-print | PUBBLICO - Tutti i diritti riservati | Visibile a tuttiVisualizza/Apri |
| Favenza2019detecting_MetroAgriFor_IEEEcopyright.pdf | Article as Published on ieeeXplore website | 2a. Post-print Versione editoriale | Non Pubblico - Accesso privato/ristretto | Administrator Richiedi una copia |
http://hdl.handle.net/11583/2799414
Copyright © 2020