dt_noisy

Dataset consisting of the time series of a raw dT (the temperature
difference between thermal dissipation sap flow probes), meteorological
factors, and soil water content at Lambir Hills National Park, Malaysia.
Missing values are represented as -9999.

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_noisy 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>Raw 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

Raw dT time series with various artifacts — dt_noisy

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>Raw 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_noisy: Raw dT time series with various artifacts

Description

Usage

Arguments

Format