gf_nepa17

The dendrometer data from three Chir pine tree collected in hourly resolution for 2017.

datasets

There are various functions for managing and cleaning data before the application of different approaches. This includes identifying and erasing sudden jumps in dendrometer data not related to environmental change, identifying the time gaps of recordings, and changing the temporal resolution of data to different frequencies. Furthermore, the package calculates daily statistics of dendrometer data, including the daily amplitude of tree growth. Various approaches can be applied to separate radial growth from daily cyclic shrinkage and expansion due to uptake and loss of stem water. In addition, it identifies periods of consecutive days with user-defined climatic conditions in daily meteorological data, then check what trees are doing during that period.

Sugam Aryal

dendRoAnalyst

A Tool for Processing and Analyzing Dendrometer Data

Martin Häusser

Jussi Grießinger

Ze-Xin Fan

Achim Bräuning

gf_nepa17 function

A data frame with 8760 rows and 3 variables:<dl>
 <dt><code>Time</code></dt>
<dd>datetime time of data recording</dd> <dt><code>T2</code></dt>
<dd>double reading for first tree</dd> <dt><code>T3</code></dt>
<dd>double reading for second tree</dd>
</dl>

Format

Dendrometer data of Kathmandu for 2017 with gap filled — gf_nepa17

A data frame with 8760 rows and 3 variables:<dl>
 <dt><code>Time</code></dt>
<dd>datetime time of data recording</dd>

 <dt><code>T2</code></dt>
<dd>double reading for first tree</dd>

 <dt><code>T3</code></dt>
<dd>double reading for second tree</dd>


</dl>

gf_nepa17: Dendrometer data of Kathmandu for 2017 with gap filled

Description

Usage

Arguments

Format