Multimodality for rainfall measurement

Hagit Messer

نتاج البحث: فصل من :كتاب / تقرير / مؤتمرمنشور من مؤتمرمراجعة النظراء


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.

اللغة الأصليةالإنجليزيّة
عنوان منشور المضيفLatent Variable Analysis and Signal Separation - 13th International Conference, LVA/ICA 2017, Proceedings
المحررونPetr Tichavsky, Massoud Babaie-Zadeh, Olivier J.J. Michel, Nadege Thirion-Moreau
ناشرSpringer Verlag
عدد الصفحات11
رقم المعيار الدولي للكتب (المطبوع)9783319535463
المعرِّفات الرقمية للأشياء
حالة النشرنُشِر - 2017
منشور خارجيًانعم
الحدث13th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2017 - Grenoble, فرنسا
المدة: ٢١ فبراير ٢٠١٧٢٣ فبراير ٢٠١٧

سلسلة المنشورات

الاسمLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
مستوى الصوت10169 LNCS
رقم المعيار الدولي للدوريات (المطبوع)0302-9743
رقم المعيار الدولي للدوريات (الإلكتروني)1611-3349


!!Conference13th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2017

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Publisher Copyright:
© Springer International Publishing AG 2017.


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