Spatio-Temporal Rainfall Estimation from Communication Satellite Data using Graph Neural Networks

Reference : Spatio-Temporal Rainfall Estimation from Communication Satellite Data using Graph Neu...


	Document type :	Scientific congresses, symposiums and conference proceedings : Unpublished conference
	Discipline(s) :	Physical, chemical, mathematical & earth Sciences : Earth sciences & physical geography Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/51068

Title :	Spatio-Temporal Rainfall Estimation from Communication Satellite Data using Graph Neural Networks
Language :	English
Author, co-author :	Krebs, Julian [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > > ; Databourg Systems S.A R.L-S, Luxembourg City L-1911 Luxembourg]
	Mishra, Kumar Vijay [United States CCDC Army Research Laboratory, Adelphi, MD 20783 USA]
	Gharanjik, Ahmad [Databourg Systems S.A R.L-S, Luxembourg City L-1911 Luxembourg]
	Mysore Rama Rao, Bhavani Shankar [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SPARC >]
Publication date :	May-2022
Peer reviewed :	No
Audience :	International
Event name :	EGU General Assembly 2022
Event date :	from 23-05-2022 to 27-05-2022
Event place (city) :	Vienna
Event country :	Austria
Keywords :	[en] Atmospheric Sciences ; Environmental Monitoring ; Machine Learning
Permalink :	http://hdl.handle.net/10993/51068
DOI :	10.5194/egusphere-egu22-1803
Other URL :	https://meetingorganizer.copernicus.org/EGU22/EGU22-1803.html
FnR project :	FnR ; FNR14787240 > Julian Krebs > MILAN > Machine Learning Applications For Environmental Monitoring Using Signalling Data From Satellite Network > 01/10/2020 > 30/09/2022 > 2020

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