L
Luis Alonso
Researcher at University of Valencia
Publications - 324
Citations - 10156
Luis Alonso is an academic researcher from University of Valencia. The author has contributed to research in topics: Wireless network & Energy consumption. The author has an hindex of 47, co-authored 320 publications receiving 8834 citations. Previous affiliations of Luis Alonso include University of Cologne & Polytechnic University of Catalonia.
Papers
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Journal ArticleDOI
Remote sensing of solar-induced chlorophyll fluorescence: Review of methods and applications
Michele Meroni,Micol Rossini,Luis Guanter,Luis Alonso,Uwe Rascher,Roberto Colombo,Jose Moreno +6 more
TL;DR: This paper reviews the main issues to be addressed for estimating F from RS observations and applications of the measured F signal at the three scales of observation are presented and discussed to provide the state of the art in F estimation.
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Is the Random Access Channel of LTE and LTE-A Suitable for M2M Communications? A Survey of Alternatives
TL;DR: A survey of the alternatives that have been proposed over the last years to improve the operation of the random access channel of LTE and LTE-A is provided, identifying strengths and weaknesses of each one of them, while drawing future trends to steer the efforts over the same shooting line.
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Evaluation of Sentinel-2 red-edge bands for empirical estimation of green LAI and chlorophyll content.
TL;DR: It is found that these new Sentinel-2 bands significantly improve the accuracy of Ch estimation, and the recently developed “Normalized Area Over reflectance Curve” (NAOC), an index that derives Ch from hyperspectral data, was studied on its compatibility with simulated Sentinel- 2 data.
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Machine learning regression algorithms for biophysical parameter retrieval: Opportunities for Sentinel-2 and -3
Jochem Verrelst,Jordi Muñoz,Luis Alonso,Jesús Delegido,Juan Pablo Rivera,Gustavo Camps-Valls,Jose Moreno +6 more
TL;DR: GPR proved to be a fast and accurate nonlinear retrieval algorithm that can be potentially implemented for operational monitoring applications and provided confidence intervals of the estimates and insight in relevant bands, which are key advantages over the other methods.
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Multioutput Support Vector Regression for Remote Sensing Biophysical Parameter Estimation
TL;DR: The achieved improvement with respect to the single-output regression approach suggests that M-SVR can be considered a convenient alternative for nonparametric biophysical parameter estimation and model inversion.