琴叶栎树干液流预测数据

可以用于预测琴叶栎液流值,输入温度、大气压亏缺、风速、相对湿度，输出为液流值。该模型帮助解决了琴叶栎液流和相关环境指标的关系建模的问题。将采集的数据使用传统算法，多元线性回归算法等方式以预测用于琴叶栎液流值预测。该模型通过输温度、大气压亏缺、风速、相对湿度等，来输出预测的琴叶栎液流。
温度ta，相对湿度rh，大气压亏缺vpd，短波sw_in，光合光通量密度ppfd_in，辐射ext_rad，液流值USA_NWH_Qly_Jt_1。

This dataset is developed for predicting the sap flow value of *Quercus lyrata*. It takes temperature, atmospheric vapor pressure deficit (VPD), wind speed and relative humidity as input features, and outputs the sap flow value as the prediction target. This model resolves the challenge of modeling the correlation between the sap flow of *Quercus lyrata* and associated environmental metrics. Collected observational data were processed with traditional algorithms including multiple linear regression to achieve sap flow prediction for *Quercus lyrata*. The model generates predicted sap flow values of *Quercus lyrata* by taking inputs including temperature, atmospheric vapor pressure deficit (VPD), wind speed, relative humidity and other relevant environmental factors.
The included variables are: air temperature (ta), relative humidity (rh), atmospheric vapor pressure deficit (vpd), shortwave radiation (sw_in), photosynthetic photon flux density (ppfd_in), external radiation (ext_rad), and the target sap flow value USA_NWH_Qly_Jt_1.