TY - GEN
T1 - Multimodality for rainfall measurement
AU - Messer, Hagit
N1 - Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - The need for accurate monitoring of rainfall, essential for many fields such as: hydrology, transportation and agriculture, calls for optimal use of all available resources. However, as the existing monitoring equipment is diverse, and different tools provide measurements of different nature, fusing these measurements is a challenging task. At one extreme, rain gauges provide local, direct measurements of the accumulated rainfall, and at the other end, satellite observations provide remote images of clouds, from which rainfall is estimated. In between, weather radar measures reflectivity which is non-linearly related to rainfall. In light of the new opportunities introduced by the use of physical measurements from cellular communication networks for rainfall monitoring, I first review the approaches for fusion of different rainfall direct and indirect measurements, distinguishing it from data assimilation, widely used in meteorology. I will then suggest a unified approach to the problem, combining parametric and non-parametric tools, and will present preliminary results.
AB - The need for accurate monitoring of rainfall, essential for many fields such as: hydrology, transportation and agriculture, calls for optimal use of all available resources. However, as the existing monitoring equipment is diverse, and different tools provide measurements of different nature, fusing these measurements is a challenging task. At one extreme, rain gauges provide local, direct measurements of the accumulated rainfall, and at the other end, satellite observations provide remote images of clouds, from which rainfall is estimated. In between, weather radar measures reflectivity which is non-linearly related to rainfall. In light of the new opportunities introduced by the use of physical measurements from cellular communication networks for rainfall monitoring, I first review the approaches for fusion of different rainfall direct and indirect measurements, distinguishing it from data assimilation, widely used in meteorology. I will then suggest a unified approach to the problem, combining parametric and non-parametric tools, and will present preliminary results.
KW - Data fusion
KW - Multimodality
KW - Rainfall monitoring
UR - http://www.scopus.com/inward/record.url?scp=85013377766&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-53547-0_32
DO - 10.1007/978-3-319-53547-0_32
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AN - SCOPUS:85013377766
SN - 9783319535463
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 333
EP - 343
BT - Latent Variable Analysis and Signal Separation - 13th International Conference, LVA/ICA 2017, Proceedings
A2 - Tichavsky, Petr
A2 - Babaie-Zadeh, Massoud
A2 - Michel, Olivier J.J.
A2 - Thirion-Moreau, Nadege
PB - Springer Verlag
T2 - 13th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2017
Y2 - 21 February 2017 through 23 February 2017
ER -