A Toolbox designed around neural networks for time series analysis of TreeNet data. The software containing the machine learning models is stored as a repository on GitHub (https://github.com/treenet/treenetai) and licensed under GNU GENERAL PUBLIC LICENSE version 3.

TreeNet (treenet.info) is an international monitoring and research network in which automated tree stem radius fluctuations measured with point dendrometers are analyzed in terms of forest ecosystem responses to climate change. A continuous stream of microclimate and tree physiology data provides realtime information on tree water relations and tree growth.

TreeNet aims to link research results from carbon flux sites with dendrometer data to entire landscapes. Further it provides online-tools to its partners to automatically interpret stem radius fluctuations in terms of tree water deficit, wood growth and related indicators for forest ecosystem carbon sink and drought stress.

The project was initiated by Roman Zweifel, WSL and Werner Eugster, ETHZ in 2009.