dt_gf

Dataset consisting of the time series of the quality-controlled and
gap-filled dT (the temperature difference between thermal dissipation sap
flow probes), meteorological factors, and soil water content at Lambir Hills
National Park, Malaysia.

datasets

Provides a flexible framework for post-processing thermal
dissipation sap flow data using statistical methods and machine learning.
This framework includes anomaly correction, outlier removal, gap-filling,
trend removal, signal damping correction, and sap flux density calculation.
The functions in this package can also apply to other time series with
various artifacts.

Yoshiaki Hata

fluxfixer

Advanced Framework for Sap Flow Data Post-Process

dt_gf function

A data frame with 17520 rows and 8 variables:<dl>
 <dt>time</dt>
<dd>Timestamp of the measurement end timing</dd> <dt>dt</dt>
<dd>Quality-controlled and gap-filled dT (degrees Celsius)</dd> <dt>p</dt>
<dd>Precipitation (mm)</dd> <dt>sw_in</dt>
<dd>Global solar radiation (W m-2)</dd> <dt>ta</dt>
<dd>Air temperature (degrees Celsius)</dd> <dt>vpd</dt>
<dd>Vapor pressure deficit (hPa)</dd> <dt>ws</dt>
<dd>Horizontal wind speed (m s-1)</dd> <dt>swc</dt>
<dd>Soil water content (m3 m-3)</dd>
</dl>

Format

Quality-controlled and gap-filled dT time series — dt_gf

A data frame with 17520 rows and 8 variables:<dl>
 <dt>time</dt>
<dd>Timestamp of the measurement end timing</dd>

 <dt>dt</dt>
<dd>Quality-controlled and gap-filled dT (degrees Celsius)</dd>

 <dt>p</dt>
<dd>Precipitation (mm)</dd>

 <dt>sw_in</dt>
<dd>Global solar radiation (W m-2)</dd>

 <dt>ta</dt>
<dd>Air temperature (degrees Celsius)</dd>

 <dt>vpd</dt>
<dd>Vapor pressure deficit (hPa)</dd>

 <dt>ws</dt>
<dd>Horizontal wind speed (m s-1)</dd>

 <dt>swc</dt>
<dd>Soil water content (m3 m-3)</dd>


</dl>

dt_gf: Quality-controlled and gap-filled dT time series

Description

Usage

Arguments

Format