This package replaces the strings package.
New features:
- Cleaner code
- More straightforward workflow
- don’t need to export intermediate “raw” and “trim” files
- few arguments to specify in templates
- Additional functions (e.g.,
ss_download_data()) - Variable names consistent with Climate Forecast conventions
- Formal tests
- More helpful
ErrorandWarningmessages
Compile, format, and visualize Water Quality (temperature, dissolved oxygen, salinity) data measured by different sensors.
Installation
You can install the development version of sensorstrings from GitHub with:
# install.packages("devtools")
devtools::install_github("dempsey-CMAR/sensorstrings")
Background
The Centre for Marine Applied Research (CMAR) coordinates an extensive Coastal Monitoring Program to measure Essential Ocean Variables from around the coast of Nova Scotia, Canada. There are three main branches of the program: Water Quality, Currents, and Waves. Processed data for each branch can be viewed and downloaded from several sources, as outlined in the CMAR Report & Data Access Cheat Sheet (download for clickable links).
The sensorstrings package is the backbone of the data pipeline for the Water Quality branch of the Coastal Monitoring Program. It is used to organize, compile, format, and visualize data Water Quality data.
Water Quality data (temperature, dissolved oxygen, and salinity) is collected using “sensor strings”. Each sensor string is attached to the seafloor by an anchor and suspended by a sub-surface buoy, with autonomous sensors attached at various depths (Figure 1). A string typically includes three sensor models: Hobo, aquaMeasure, and VR2AR (Table 1). Strings are deployed at a station for several months and data are measured every 1 minute to 1 hour, depending on the sensor.
Figure 1: Typical sensor string configuration (not to scale).
After retrieval, data from each sensor is exported to a separate csv file using manufacturer-specific software. Each type of sensor generates a data file with unique columns and header fields, which poses a significant challenge for compiling all data from a deployment into a single format for analysis.
The sensorstrings package offers functions to compile, format, convert units, and visualize sensor string data.
sensorstrings was developed specifically to streamline CMAR’s workflow, but is flexible enough that other users can apply it to process data from the accepted sensors (Table 1). Vignettes to come
| Sensor | Variable(s) Measured |
|---|---|
| HOBO Pro V2 | Temperature |
| HOBO DO | Temperature, Dissolved Oxygen |
| aquaMeasure DOT | Temperature, Dissolved Oxygen |
| aquaMeasure SAL | Temperature, Salinity |
| VR2AR | Temperature |
For more information on Water Quality data collection and processing, visit the CMAR Water Quality Data Collection & Processing Cheat Sheet (download for clickable links).
Example
Consider a string deployed from May 31, 2019 to October 19, 2019 with three sensors:
| Sensor | Serial # | Depth |
|---|---|---|
| HOBO Pro V2 | 10755220 | 2 |
| aquaMeasure DOT | 670364 | 5 |
| VR2AR | 547109 | 15 |
Raw data files
The data from each sensor is saved in separate csv file, each with manufacturer-specific columns.
Import raw data files:
path <- system.file("extdata", package = "sensorstrings")
aquameasure_raw <- ss_read_aquameasure_data(
path = paste0(path, "/aquameasure"),
file_name = "aquameasure-670364.csv"
)
hobo_raw <- ss_read_hobo_data(
path = paste0(path, "/hobo"),
file_name = "10755220.csv"
)
vemco_raw <- ss_read_vemco_data(
path = paste0(path, "/vemco"),
file_name = "vemco-547109.csv"
)Examine the first rows of each raw data file:
AquaMeasure data
head(aquameasure_raw)
#> Timestamp(UTC) Time Corrected(seconds) Sensor
#> 1 209s after startup (time not set) NA aquaMeasure-670364
#> 2 353s after startup (time not set) NA aquaMeasure-670364
#> 3 1226s after startup (time not set) NA aquaMeasure-670364
#> 4 2143s after startup (time not set) NA aquaMeasure-670364
#> 5 3006s after startup (time not set) NA aquaMeasure-670364
#> 6 3875s after startup (time not set) NA aquaMeasure-670364
#> Record Type Dissolved Oxygen Temperature Device Tilt Battery Voltage
#> 1 Device Tilt NA NA 90.4 NA
#> 2 Temperature NA 22.68 NA NA
#> 3 Dissolved Oxygen 100.5 NA NA NA
#> 4 Device Tilt NA NA 91.0 NA
#> 5 Device Tilt NA NA 91.1 NA
#> 6 Dissolved Oxygen 100.5 NA NA NA
#> TimeSet Time Text
#> 1 NA NA NA
#> 2 NA NA NA
#> 3 NA NA NA
#> 4 NA NA NA
#> 5 NA NA NA
#> 6 NA NA NAHobo data
head(hobo_raw)
#> # Date Time, GMT+00:00 Temp, °C (LGR S/N: 10755220, SEN S/N: 10755220) V4
#> 1 4 2019-05-30 21:00 6.661 NA
#> 2 8 2019-05-31 1:00 7.695 NA
#> 3 12 2019-05-31 5:00 7.569 NA
#> 4 16 2019-05-31 9:00 6.509 NA
#> 5 20 2019-05-31 13:00 6.788 NA
#> 6 24 2019-05-31 17:00 6.839 NA
#> Coupler Attached (LGR S/N: 10755220) Host Connected (LGR S/N: 10755220)
#> 1 NA NA
#> 2 NA NA
#> 3 NA NA
#> 4 NA NA
#> 5 NA NA
#> 6 NA NA
#> Stopped (LGR S/N: 10755220) End Of File (LGR S/N: 10755220)
#> 1
#> 2
#> 3
#> 4
#> 5
#> 6Vemco data
head(vemco_raw)
#> Date and Time (UTC) Receiver Description Data Units
#> 1 2019-05-30 18:06 VR2AR-547109 Noise 207.6 mV
#> 2 2019-05-30 18:10 VR2AR-547109 Tilt angle 89 °
#> 3 2019-05-30 18:13 VR2AR-547109 Temperature 13.6 °C
#> 4 2019-05-30 18:17 VR2AR-547109 Seawater depth 0 m
#> 5 2019-05-30 18:21 VR2AR-547109 Noise 178.3 mV
#> 6 2019-05-30 18:25 VR2AR-547109 Tilt angle 84 °Data from each sensor is exported in a slightly different layout, making it difficult to work with and analyze all of the data from a single deployment.
Compile and format with sensorstrings
The ss_compile_deployment_data() function makes it easy to compile these files into a single data frame, with additional information added from the deployment log.
Deployment Log
The deployment log includes the deployment and retrieval dates, information on where the string was deployed, and the depth of each sensor.
log <- ss_read_log(path)
#> ✔ Reading from "STRING TRACKING".
#> ✔ Range ''Area Info''.
log$deployment_dates
#> start_date end_date
#> 1 2019-05-30 2019-10-19
log$area_info
#> county waterbody latitude longitude station lease
#> 1 Halifax Shoal Bay 44.77241 -62.72608 Borgles Island NA
log$sn_table
#> # A tibble: 3 × 3
#> log_sensor sensor_serial_number depth
#> <chr> <dbl> <dbl>
#> 1 HOBO Pro V2 10755220 2
#> 2 aquaMeasure DOT 670364 5
#> 3 VR2AR 547109 15Compile Data
ss_compile_deployment_data() reads in the log and the data for each sensor and exports a single data frame.
dat <- ss_compile_deployment_data(path)
#> ✔ Reading from "STRING TRACKING".
#> ✔ Range ''Area Info''.
#> aquameasure data compiled
#> hobo data compiled
#> vemco data compiled: Temperature & Seawater depth
kable(dat[1:10, ])| county | waterbody | station | lease | latitude | longitude | deployment_range | string_configuration | sensor_type | sensor_serial_number | timestamp_utc | sensor_depth_at_low_tide_m | dissolved_oxygen_percent_saturation | sensor_depth_measured_m | temperature_degree_c |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Halifax | Shoal Bay | Borgles Island | NA | 44.77241 | -62.72608 | 2019-May-30 to 2019-Oct-19 | sub-surface buoy | hobo | 10755220 | 2019-05-30 21:00:00 | 2 | NA | NA | 6.661 |
| Halifax | Shoal Bay | Borgles Island | NA | 44.77241 | -62.72608 | 2019-May-30 to 2019-Oct-19 | sub-surface buoy | hobo | 10755220 | 2019-05-31 01:00:00 | 2 | NA | NA | 7.695 |
| Halifax | Shoal Bay | Borgles Island | NA | 44.77241 | -62.72608 | 2019-May-30 to 2019-Oct-19 | sub-surface buoy | hobo | 10755220 | 2019-05-31 05:00:00 | 2 | NA | NA | 7.569 |
| Halifax | Shoal Bay | Borgles Island | NA | 44.77241 | -62.72608 | 2019-May-30 to 2019-Oct-19 | sub-surface buoy | hobo | 10755220 | 2019-05-31 09:00:00 | 2 | NA | NA | 6.509 |
| Halifax | Shoal Bay | Borgles Island | NA | 44.77241 | -62.72608 | 2019-May-30 to 2019-Oct-19 | sub-surface buoy | hobo | 10755220 | 2019-05-31 13:00:00 | 2 | NA | NA | 6.788 |
| Halifax | Shoal Bay | Borgles Island | NA | 44.77241 | -62.72608 | 2019-May-30 to 2019-Oct-19 | sub-surface buoy | hobo | 10755220 | 2019-05-31 17:00:00 | 2 | NA | NA | 6.839 |
| Halifax | Shoal Bay | Borgles Island | NA | 44.77241 | -62.72608 | 2019-May-30 to 2019-Oct-19 | sub-surface buoy | hobo | 10755220 | 2019-05-31 21:00:00 | 2 | NA | NA | 7.192 |
| Halifax | Shoal Bay | Borgles Island | NA | 44.77241 | -62.72608 | 2019-May-30 to 2019-Oct-19 | sub-surface buoy | hobo | 10755220 | 2019-06-01 01:00:00 | 2 | NA | NA | 7.594 |
| Halifax | Shoal Bay | Borgles Island | NA | 44.77241 | -62.72608 | 2019-May-30 to 2019-Oct-19 | sub-surface buoy | hobo | 10755220 | 2019-06-01 05:00:00 | 2 | NA | NA | 7.544 |
| Halifax | Shoal Bay | Borgles Island | NA | 44.77241 | -62.72608 | 2019-May-30 to 2019-Oct-19 | sub-surface buoy | hobo | 10755220 | 2019-06-01 09:00:00 | 2 | NA | NA | 6.661 |
