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Estimation and prediction of weather variables from surveillance data using spatio-temporal Kriging

Autor
Dalmau, R.; Perez-Batlle, M.; Prats, X.
Tipus d'activitat
Presentació treball a congrés
Nom de l'edició
36th Digital Avionics Systems Conference
Any de l'edició
2017
Data de presentació
2017-09-21
Llibre d'actes
DASC 2017: 36th Digital Avionics Systems Conference: St. Petersburg, Florida, USA: September 17-21, 2017: proceedings papers
Pàgina inicial
1
Pàgina final
8
DOI
https://doi.org/10.1109/DASC.2017.8102132 Obrir en finestra nova
Activitat premiada
Si
Repositori
http://hdl.handle.net/2117/112695 Obrir en finestra nova
URL
http://ieeexplore.ieee.org/document/8102132/ Obrir en finestra nova
Resum
Best paper award in Weather session at the 36th DASC - Digital Avionics Systems Conference State-of-the-art weather data obtained from numerical weather predictions are unlikely to satisfy the requirements of the future air traffic management system. A potential approach to improve the resolution and accuracy of the weather predictions could consist on using airborne aircraft as meteorological sensors, which would provide up-to-date weather observations to the sur- rounding aircraft and ground s...
Citació
Dalmau, R., Perez-Batlle, M., Prats, X. Estimation and prediction of weather variables from surveillance data using spatio-temporal Kriging. A: Digital Avionics Systems Conference. "DASC 2017: 36th Digital Avionics Systems Conference: St. Petersburg, Florida, USA: September 17-21, 2017: proceedings papers". St. Petersburg, Florida: 2017, p. 1-8.
Grup de recerca
ICARUS - Intelligent Communications and Avionics for Robust Unmanned Aerial Systems

Participants

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