mc_prep_TMSoffsoil {myClim}

Detection of out-of-soil measurements from TMS logger

Description

This function creates new virtual sensor labelling anomalies in TMS logger caused by displacement out of from soil.

Usage

mc_prep_TMSoffsoil(
  data,
  localities = NULL,
  soil_sensor = mc_const_SENSOR_TMS_T1,
  air_sensor = mc_const_SENSOR_TMS_T2,
  moist_sensor = mc_const_SENSOR_TMS_moist,
  output_sensor = "off_soil",
  smooth = FALSE,
  smooth_window = 10,
  smooth_threshold = 0.5,
  sd_threshold = 0.76085,
  minmoist_threshold = 721.5
)

Arguments

data

cleaned myClim object see myClim-package

localities

names of localities; if NULL then all (default NULL)

soil_sensor

character, soil temperature sensor (default mc_const_SENSOR_TMS_T1)

air_sensor

character, air temperature sensor (default mc_const_SENSOR_TMS_T2)

moist_sensor

character, soil moisture sensor (default mc_const_SENSOR_TMS_moist)

output_sensor

character, name of virtual sensor to store ouptup values (default "off_soil")

smooth

logical, smooth out isolated faulty/correct records using floating window (default FALSE)

smooth_window

integer, smooth floating window width (in days) (default 10)

smooth_threshold

numeric, floating window threshold for detection of faulty records. (default 0.5)

sd_threshold

numeric, threshold value for the criteria on the ratio of standard deviation of the soil sensor to the above-ground sensor temperatures (default 0.76085)

minmoist_threshold

numeric, threshold value for criteria on the minimum soil moisture (default 721.5)

Details

TMS loggers, when correctly installed in the soil, exhibit certain temperature and soil moisture signal characteristics. Temperature varies the most at the soil interface, and temperature fluctuations in the soil are minimized. The moisture signal from a sensor that has lost direct contact with the soil is reduced. The following criteria are used for detecting faulty measurements: the ratio of the standard deviations of the soil sensor to the above-ground sensor within 24h moving window is greater than the defined threshold (default 0.76085), and simultaneously, the soil moisture minimum within 24h mowing window is less than 721.5. Optionally, the prediction results can be smoothed using a floating window to average-out unlikely short periods detected by the algorithm. Selection and parametrization of criteria was done using a recursive partitioning (rpart::rpart) on the training set of 7.8M readings in 154 TMS timeseries from different environmental settings (temperate forests, tropical rainforest, cold desert, alpine and subnival zone, and invalid measurements from loggers stored in the office or displaced from the soil). Sensitivity of the method (true positive rate) on was 95.1% and specificity (true negative rate) was 99.4% using function default parameters. Smoothing with 10 day floating window increased sensitivity to 96.8% while retaining specifity at the same level of 99.4%. Decreasing 'smooth_threshold' below 0.5 will extend periods flagged as faulty measurement.

Value

numeric vector (0 = correct measurement, 1 = faulty measurement) stored as virtual sensor in myClim object

Examples

data <- mc_read_files(system.file("extdata", "data_93142760_201904.csv", package = "myClim"),
                      "TOMST")
data <- mc_prep_TMSoffsoil(data)
mc_plot_line(data, sensors = c("off_soil","TMS_T1", "TMS_T2","TMS_T3"))