TreeNetAI

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.

一款基于神经网络构建的TreeNet（TreeNet）数据时序分析工具箱。该集成了机器学习模型的软件以代码仓库形式托管于GitHub（https://github.com/treenet/treenetai），并采用GNU通用公共许可证第3版（GNU GENERAL PUBLIC LICENSE version 3）进行授权。
TreeNet（官网：treenet.info）是一个国际性监测与研究网络，其针对利用点状树木测径仪（point dendrometer）测得的树木茎干半径自动波动数据，开展森林生态系统对气候变化响应的相关分析。源源不断的微气候与树木生理数据，可实时提供树木水分关系及树木生长的相关信息。
TreeNet旨在将碳通量站点的研究成果与树木测径仪数据关联至完整的景观尺度。此外，该项目还为合作伙伴提供在线工具，可自动解析茎干半径波动对应的树木水分亏缺、木材生长以及森林生态系统碳汇与干旱胁迫的相关指标。
该项目于2009年由Roman Zweifel（供职于WSL）与Werner Eugster（供职于ETHZ）发起。