airdas_process: Process aerial survey DAS data

In swfscAirDAS: Southwest Fisheries Science Center Aerial DAS Data Processing

Process aerial survey DAS data

Description

Process AirDAS data (the output of airdas_read), including extracting state and condition information for each AirDAS event

Usage

airdas_process(x, ...)

## S3 method for class 'character'
airdas_process(x, ...)

## S3 method for class 'data.frame'
airdas_process(x, ...)

## S3 method for class 'airdas_dfr'
airdas_process(
  x,
  days.gap.part = 0.5/24,
  days.gap.full = 12/24,
  gap.message = FALSE,
  reset.transect = TRUE,
  trans.upper = FALSE,
  ...
)

Arguments

x	an object of class airdas_dfr object, an object that can be coerced to class airdas_dfr, or a character (filepath) which is first passed to airdas_read
...	passed to airdas_read if x is a character. Otherwise ignored
days.gap.part	numeric of length 1; time gap (in days) used to identify when a 'partial reset' is performed, i.e. when propagated info (weather, observers, etc) is reset. Default is 30 minutes; must be less than or equal to days.gap.full
days.gap.full	numeric of length 1; time gap (in days) used to identify when a 'full reset; is performed, i.e. when all info (transect number and propagated info) is reset. Default is 12 hours; must be greater than days.gap.part
gap.message	logical; default is FALSE. Indicates if messages should be printed detailing which row(s) of the output data frame were partially or fully reset
reset.transect	logical; default is TRUE. Indicates if propagated info (weather, observers, etc) should be reset to NA when beginning a new transect. See Details section
trans.upper	logical; indicates if all transect codes should be capitalized using toupper. Default is FALSE

Details

If x is a character, it is assumed to be a filepath and first passed to airdas_read. This output is then processed.

This function cannot handle concatenated airdas_dfr objects of multiple file types. In other words, AirDAS data must be processed and then concatenated.

AirDAS data is event-based, meaning most events indicate when a state or weather condition changes. For instance, a 'W' event indicates when one or more weather conditions (such as Beaufort sea state) change, and the weather conditions are the same for subsequent events until the next 'W' event. For each state/condition: a new column is created, the state/condition information is extracted from relevant events, and extracted information is propagated to appropriate subsequent rows (events). Thus, each row in the output data frame contains all pertinent state/condition information for that row.

The following assumptions/decisions are made during processing:

• All '#' events (deleted events) are removed

• 'DateTime', 'Lat', and 'Lon' information are added to '1' events where applicable

• Effort is determined as follows: T/R events turns effort on, and O/E events turn effort off. T/R events themselves will be on effort, while O/E events will be off effort. The 'EffortDot' column is ignored

• 'HKR' values are converted to lower case. "Y" values are considered to be "H" values

• Observer ('ObsL', 'ObsB', 'ObsR', 'Rec') values are converted to lower case

• Viewing condition ('VLI', 'VLO', 'VB', 'VRI', 'VRO') values are converted to lower case

• Missing values are NA rather than -1

Normally, a T event (to indicate starting/resuming a transect) is immediately followed by a VPAW event series, creating a TVPAW event series. The reset.transect argument causes the conditions set in the VPAW event series (Beaufort, viewing conditions, altitude, etc.) to be reset to NA at each T event

Value

An airdas_df object, which is also a data frame. It consists of the input data frame, i.e. the output of airdas_read, with the following columns added:

State/condition	Column name	Notes
On/off effort	OnEffort
Transect code	Trans
Beaufort sea state	Bft
Percent overcast (cloud cover)	CCover
Jellyfish code	Jelly	not in PHOCOENA data
Horizontal sun (clock system)	HorizSun
Vertical sun (clock system)	VertSun	only in PHOCOENA data
Haze/Kelp/Red tide code	HKR
Haze (from HKR code)	Haze
Kelp (from HKR code)	Kelp
Red tide (from HKR code)	RedTide
Altitude (feet)	AltFt
Speed (knots)	SpKnot
Left observer	ObsL
Belly observer	ObsB
Right observer	ObsR
Data recorder	Rec
Viewing condition - left inside	VLI
Viewing condition - left outside	VLO
Viewing condition - belly	VB
Viewing condition - right inside	VRI
Viewing condition - right outside	VRO

See airdas_format_pdf for which data columns the condition information is extracted form for each file type. In addition, warnings are printed with line numbers of unexpected event codes

Examples

y <- system.file("airdas_sample.das", package = "swfscAirDAS")
airdas_process(y, trans.upper = FALSE)

y.read <- airdas_read(y)
airdas_process(y.read)

swfscAirDAS documentation built on Aug. 9, 2023, 1:06 a.m.