Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 546696
Title Modelling Landsurface Time-Series with Recurrent Neural Nets
Author(s) Reichstein, Markus; Besnard, Simon; Carvalhais, Nuno; Gans, Fabian; Jung, Martin; Kraft, Basil; Mahecha, Miguel
Event IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018-07-22/2018-07-27
DOI https://doi.org/10.1109/IGARSS.2018.8518007
Department(s) Laboratory of Geo-information Science and Remote Sensing
PE&RC
Publication type Contribution in proceedings
Publication year 2018
Abstract Machine learning tools and semi-empirical models have been very successful in describing and predicting instantaneous climatic influences on the spatial and seasonal variability of biosphere state and function. Yet, little work has been carried to explicitly model dynamic features accounting for memory effects, where in some cases hand-designed features (e.g. temperature sum, lagged precipitation) have been employed. Here, we explore the ability of recurrent neural network variants (RNN, LSTM) to model time series of dynamic variables 1) fPAR and NDVI, and 2) Carbon dioxide uptake and evapotranspiration, with meteorological variables as the only dynamic predictors. We show that the recurrent neural net approach excellently deals with this dynamic modelling challenge and outcompetes approaches where hand-designed features are complicated to conceive.
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