Description Usage Arguments Details Value See Also Examples
proc_treenet
processes L0
dendrometer data from the
TreeNet server directly to L1
(i.e. time-aligned data) or
L2
(i.e. cleaned L1
data).
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | proc_treenet(
site = NULL,
sensor_name = NULL,
from = NULL,
to = NULL,
last = NULL,
reso = 10,
frost_thr = 5,
lowtemp = 5,
tol_jump = 50,
tol_out = 10,
interpol = NULL,
frag_len = NULL,
proc_to = "L2",
plot = TRUE,
plot_period = "full",
plot_export = TRUE,
plot_name = "proc_L2_plot",
plot_show = "all",
plot_phase = FALSE,
path_cred = NULL,
year = "asis",
iter_clean = 1,
tz = "Etc/GMT-1",
use_intl = FALSE
)
|
site |
character, specify the site. String is not case sensitive. |
sensor_name |
character, specify the name of a single or
multiple sensors (e.g. |
from |
character, optional argument to select data after a specific
date ( |
to |
character, optional argument to select data up to a specific
date ( |
last |
numeric, optional argument to specify the number of latest
values. If |
reso |
numeric, desired output time resolution (in minutes). See
|
frost_thr |
numeric, increases the thresholds for outlier
and jump detection in periods of probable frost (i.e. temperature <
|
lowtemp |
numeric, specifies the temperature in °C below which frost
shrinkage or expansion is expected. Default value is set to
|
tol_jump |
numeric, defines the rigidity of the threshold above or below which a value is flagged for jump correction. Lower values increase the rigidity (see Details for further information). |
tol_out |
numeric, defines the rigidity of the threshold above or below which a value is classified as an outlier. Lower values increase the rigidity (see Details for further information). |
interpol |
numeric, length of gaps (in minutes) for which values are
linearly interpolated after data cleaning. Set |
frag_len |
numeric, specifies the length of data fragments occurring
in-between missing data that are automatically deleted during data
cleaning. This can be helpful to remove short fragments of erroneous data
within a period of missing data, i.e. after jumps. If
|
proc_to |
character, specify to which level the data should be
processed. Can be one of |
plot |
logical, specify whether the changes that occurred during data cleaning should be plotted. |
plot_period |
character, specify whether plots should be displayed for
the whole period ( |
plot_export |
logical, specifies whether the plots are exported as a
|
plot_name |
character, specify name of the PDF to which the plots are saved. |
plot_show |
character, specify whether all periods should be plotted
( |
plot_phase |
logical, specify whether identified phases should be plotted. |
path_cred |
optional argument to specify the full path to the
file |
year |
character, if |
iter_clean |
numeric, specifies the number of times the cleaning process is repeated. Can be used to check whether running the cleaning process multiple times has an effect on the results. In most cases, a single iteration is sufficient. |
tz |
specify the desired time zone. Default is |
use_intl |
logical, specify whether this function is used
internally on the server. Changes |
Time-aligned temperature data temp_L1
is used to define
periods in which frost shrinkage is probable, e.g. when the temperature
is below lowtemp
. Without temperature data, frost shrinkages may be
classified as outliers. For more details and an example see the following
vignette:
vignette("Introduction-to-treenetproc", package = "treenetproc")
.
Temperature data can also be provided along with dendrometer data. In this
case, the name of the temperature series has to contain the string
"temp"
. In case no temperature dataset is specified, a sample
temperature dataset will be used with a warning. The sample temperature
dataset assigns permanent frost to the three months December, January
and February.
Outliers and jumps are identified when exceeding a lower or upper
threshold. Thresholds are obtained on the basis of density distributions
of differences between neighbouring data points. The rigidity of the
thresholds can be controlled with the arguments tol_jump
and
tol_out
. For more information on the calculation of the thresholds
the user is referred to Knüsel et al. (2020, in prep).
The function returns a data.frame
with processed dendrometer
data containing the following columns:
series |
name of the dendrometer series. |
ts |
timestamp with format |
value |
dendrometer value ( |
max |
highest measured value up to this timestamp ( |
twd |
tree water deficit ( |
gro_yr |
growth since the beginning of the year ( |
frost |
indicates frost periods (i.e. periods in which the
temperature is below |
flags |
character vector specifying the changes that occurred
during the processing. For more details see the following vignette:
|
version |
package version number. |
proc_L1
to process dendrometer or climate data to
L1
.
proc_dendro_L2
to process dendrometer data from L1
to L2
.
corr_dendro_L1
to correct errors before processing.
corr_dendro_L2
to correct errors after processing.
1 2 3 4 5 6 7 8 9 | ## Not run:
proc_treenet(site = "sagno", year = "full", plot_period = "yearly")
proc_treenet(site = "lens", plot_period = "monthly")
proc_treenet(sensor_name = c("Alvaneu-2.dendrometer.ch0",
"Alvaneu-4.dendrometer.ch0"))
## End(Not run)
|
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