Time series processing library
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Updated
Aug 20, 2026 - Python
Time series processing library
Using atmospheric humidity deficits to discern soil moisture deficits. Python code repository for Baldocchi et al. (2021)
R code for Zohner et al. (2023)
Relating (soil) droughts to spectral indices
APES (Atmosphere - Plant - Exchange Simulator) codes in Matlab
A collection of deep learning/machine learning models for the modeling of ecological fluxes with ecosystem memory and lagged drivers.
Detects and removes time lags in eddy covariance raw data, following the method described by Vitale et al. (2024).
Visualize Eddy-Covariance data Streams
Import Eddy Covariance Streams from CSV to SQLite
A research programme on a biophysical contribution to Earth's radiative budget. Twelve single-author preprints testing and bounding ecosystem-mediated cooling. Per-paper concept files, reproducibility matrix, machine-readable citation.
A toolbox for processing, quality controlling and gap-filling FLUXNET2015 dataset for use in land surface modelling
dimensionality reduction on fluxnet series and how does it separate timescales?
Retrieve and extract Google Earth Engine satellite data over eddy-covariance flux tower sites, with batch export to local or remote storage.
Standalone HTML explorer for eddy covariance records: fluxes, meteorology, badges, trends, day by day
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