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The earthmapps.io team under supervision of Stef Lhermitte, focuses on the use of multi-source satellite imagery to assess land-atmosphere interactions. Our research aims at developing innovative remote sensing methods for quantifying the effect of climate (change) on snow/ice, vegetation dynamics, etc. and determine their (climate) feedbacks. We work on big data solutions and machine learning techniques to bridge the gap between remote sensing technology and its (scientific) applications.
Technologically we work on the interface between multi-source satellite imagery, radiative transfer models, land-surface models (e.g. snowmodels) and climate models. Within this framework we aim at developing and integrating innovative methodologies to assess the Earth's surface properties, mainly snow/ice and vegetation related, and understand their complex spatio-temporal response to climate. These methodologies range from improved data processing and data machine learning, to big data solutions and time series analysis (e.g. tipping points)
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论文共 149 篇作者统计合作学者相似作者
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CRYOSPHEREno. 7 (2023): 3041-3062
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Journal of Advances in Modeling Earth Systemsno. 6 (2023)
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. (2023): 2462-2480
Lena G. Buth,Bert Wouters,Sanne B. M. Veldhuijsen,Stef Lhermitte,Peter Kuipers Munneke, Michiel R. van den Broeke
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