Time series processing library
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Updated
Sep 29, 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.
Standalone HTML explorer for eddy covariance records: fluxes, meteorology, badges, trends, day by day
Detects and removes time lags in eddy covariance raw data, following the method described by Vitale et al. (2024).
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.
Import Eddy Covariance Streams from CSV to SQLite
Visualize Eddy-Covariance data Streams
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.
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