G
G. De Lannoy
Researcher at Katholieke Universiteit Leuven
Publications - 34
Citations - 2312
G. De Lannoy is an academic researcher from Katholieke Universiteit Leuven. The author has contributed to research in topics: Data assimilation & Water content. The author has an hindex of 19, co-authored 34 publications receiving 1800 citations. Previous affiliations of G. De Lannoy include Ghent University & Catholic University of Leuven.
Papers
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Journal ArticleDOI
Modelling the Passive Microwave Signature from Land Surfaces: A Review of Recent Results and Application to the L-Band SMOS SMAP Soil Moisture Retrieval Algorithms
Jean-Pierre Wigneron,Thomas J. Jackson,Peggy O'Neill,G. De Lannoy,P. de Rosnay,Jeffrey P. Walker,Paolo Ferrazzoli,Valery Mironov,Simone Bircher,Jennifer Grant,Mehmet Kurum,Mike Schwank,Joaquín Muñoz-Sabater,Narendra N. Das,Alain Royer,Amen Al-Yaari,Ahmad Al Bitar,Roberto Fernandez-Moran,Heather Lawrence,Arnaud Mialon,Marie Parrens,P. Richaume,Steven Delwart,Yann Kerr +23 more
TL;DR: In this paper, the authors present a review of the significant progress which has been made over the last decade in this field of research with a focus on L-band, and a discussion on possible applications to the SMOS and SMAP soil moisture retrieval approaches.
Journal ArticleDOI
Assimilation of passive and active microwave soil moisture retrievals
Clara S. Draper,Clara S. Draper,Rolf H. Reichle,G. De Lannoy,G. De Lannoy,G. De Lannoy,Qing Liu,Qing Liu +7 more
TL;DR: In this article, the authors compared the impact of assimilating ASCAT and AMSR-E soil moisture data, both separately and together, according to land cover type, by comparison to in situ soil moisture observations.
Journal ArticleDOI
SMOS soil moisture assimilation for improved hydrologic simulation in the Murray Darling Basin, Australia
Hans Lievens,Sat Kumar Tomer,Ahmad Al Bitar,G. De Lannoy,Matthias Drusch,Gift Dumedah,Harrie-Jan Hendricks Franssen,Yann Kerr,Brecht Martens,Ming Pan,Joshua K. Roundy,Harry Vereecken,Jeffrey P. Walker,Eric F. Wood,Niko E. C. Verhoest,Valentijn R. N. Pauwels +15 more
TL;DR: In this article, the authors explored the benefits of assimilating SMOS retrievals for hydrologic modeling, with a focus on soil moisture and streamflow simulations in the Murray Darling Basin, Australia.
Journal ArticleDOI
Feature selection for interpatient supervised heart beat classification
TL;DR: Feature selection techniques are considered to extract optimal feature subsets for state-of-the-art ECG classification models and indicate that a small number of individual features actually serve the classification and that better performances can be achieved by removing useless features.
Journal ArticleDOI
Weighted Conditional Random Fields for Supervised Interpatient Heartbeat Classification
TL;DR: Experiments show that the proposed method outperforms previously reported heartbeat classification methods, especially for the pathological heartbeats.