Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Maria Paola Clarizia"'
Publikováno v:
Remote Sensing, Vol 16, Iss 7, p 1125 (2024)
GNSS Reflectometry (GNSS-R) is an emerging technique for the remote sensing of the environment. Traditional GNSS-R bio-geophysical parameter retrieval algorithms and deep learning models utilize observables derived from only the peak power of the del
Externí odkaz:
https://doaj.org/article/f65d441c873141de807566a3c928eee1
Autor:
Hugo Carreno-Luengo, Adriano Camps, Chris Ruf, Nicolas Floury, Manuel Martin-Neira, Tianlin Wang, Siri Jodha Khalsa, Maria Paola Clarizia, Jennifer Reynolds, Joel Johnson, Andrew O'Brien, Carmela Galdi, Maurizio Di Bisceglie, Andreas Dielacher, Philip Jales, Martin Unwin, Lucinda King, Giuseppe Foti, Rashmi Shah, Daniel Pascual, Bill Schreiner, Milad Asgarimehr, Jens Wickert, Serni Ribo, Estel Cardellach
Publikováno v:
IEEE Access, Vol 9, Pp 89906-89933 (2021)
The Institute of Electrical and Electronics Engineers (IEEE) Geoscience and Remote Sensing Society (GRSS) created the GRSS “Standards for Earth Observation Technical Committee” to advance the usability of remote sensing products by experts from a
Externí odkaz:
https://doaj.org/article/e0357a81975149d1af8b504225be433e
Autor:
Emanuele Santi, Simonetta Paloscia, Simone Pettinato, Giacomo Fontanelli, Maria Paola Clarizia, Davide Comite, Laura Dente, Leila Guerriero, Nazzareno Pierdicca, Nicolas Floury
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 2351-2368 (2020)
In this study, the capability of Global Navigation Satellite System Reflectometry in evaluating forest biomass from space has been investigated by using data coming from the TechDemoSat-1 (TDS-1) mission of Surrey Satellite Technology Ltd. and from t
Externí odkaz:
https://doaj.org/article/cb289bfcb983474db34a5eb0be324b8b
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 708-716 (2020)
In this article, a retrieval algorithm based on the use of an artificial neural network (ANN) is proposed for wind speed estimations from cyclone global navigation satellite system (CYGNSS). The delay/Doppler map average and the leading edge slope ob
Externí odkaz:
https://doaj.org/article/5a4a64c9b0f04c94b438e4863467ace1
Publikováno v:
Remote Sensing, Vol 13, Iss 21, p 4313 (2021)
This article presents the methodology for an improved estimation of the sea surface wind speed measured by the cyclone global navigation satellite system (CYGNSS) constellation of satellites using significant wave height (SWH) information as external
Externí odkaz:
https://doaj.org/article/3a5f6043c18e4b4383e028373ad28a80
Autor:
Giuseppina De Felice Proia, Marco Restano, Davide Comite, Maria Paola Clarizia, Jerome Benveniste, Nazzareno Pierdicca, Leila Guerriero
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 60:1-11
Autor:
Giuseppina De Felice Proia, Marco Restano, Davide Comite, Maria Paola Clarizia, Jerome Benveniste, Nazzareno Pierdicca, Leila Guerriero
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 60:1-10
Publikováno v:
IEEE Geoscience and Remote Sensing Letters. 19:1-5
This letter investigates the sensitivity of the ocean surface bistatic scattering cross section measured by the Cyclone Global Navigation Satellite System (CYGNSS) to wind direction using the kurtosis of the delay-Doppler map (DDM) samples within a g
Autor:
Mehrez Zribi, Luca Cenci, Nicolas Floury, Maria Paola Clarizia, Hugo Carreno-Luengo, Adriano Camps, Emanuele Santi, Laura Dente, Leila Guerriero, Fabiano Costantini, Simonetta Paloscia, Antonio Mmollfulleda, Hyuk Park, Davide Comite, Nazzareno Pierdicca
Publikováno v:
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Universitat Politècnica de Catalunya (UPC)
This work presents an overview of the activity developed in the frame of a project funded by the European Space Agency (ESA). The research was focused on the study of the potential applications of GNSS Reflectometry (GNSS- R) over land, with an empha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a1f7b9e71141d5e5c2ab2b8cbc958e1f
https://hdl.handle.net/2117/359690
https://hdl.handle.net/2117/359690
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 58:3955-3964
In this article, a statistical methodology to estimate wind speed from CYGNSS observables is proposed and implemented. The approach uses the cumulative distribution function (cdf) of the observable and of the ground-truth reference winds. It depends