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Spatial data quality checks

Source: R/spatial_qaqc.R
spatial_qaqc.Rd

This function performs spatial quality checks and outputs summary tables and plots. Checks include percent of observations on land, outside regulatory zone (spat), and on a zone boundary. If any observation occurs outside the regulatory zones then summary information on distance from nearest zone is provided. spatial_qaqc can filter out observations that are not within the distance specified in filter_dist.

Usage

spatial_qaqc(
  dat,
  project,
  spat,
  lon.dat,
  lat.dat,
  lon.spat = NULL,
  lat.spat = NULL,
  id.spat = NULL,
  epsg = NULL,
  date = NULL,
  group = NULL,
  filter_dist = NULL
)

Arguments

dat

Primary data containing information on hauls or trips. Table in FishSET database contains the string 'MainDataTable'.

project

Name of project.

spat

Spatial data containing information on fishery management or regulatory zones. sf objects are recommended, but sp objects can be used as well. If using a spatial table read from a csv file, then arguments lon.spat and lat.spat are required. To upload your spatial data to the FishSETFolder see load_spatial.

lon.dat

Longitude variable in dat.

lat.dat

Latitude variable in dat.

lon.spat

Variable or list from spat containing longitude data. Required for spatial tables read from csv files. Leave as NULL if spat is an sf or sp object.

lat.spat

Variable or list from spat containing latitude data. Required for spatial tables read from csv files. Leave as NULL if spat is an sf or sp object.

id.spat

Polygon ID column. Required for spatial tables read from csv files. Leave as NULL if spat is an sf or sp object.

epsg

EPSG number. Manually set the epsg code, which will be applied to spat and dat. If epsg is not specified but is defined for spat, then the spat epsg will be applied to dat. In addition, if epsg is not specified and epsg is not defined for spat, then a default epsg value will be applied to spat and dat (epsg = 4326). See http://spatialreference.org/ to help identify optimal epsg number.

date

String, name of date variable. Used to summarize over year. If NULL the first date column will be used. Returns an error if no date columns can be found.

group

String, optional. Name of variable to group spatial summary by.

filter_dist

(Optional) Numeric, distance value to filter primary data by (in meters). Rows containing distance values greater than or equal to filter_dist will be removed from the data. This action will be saved to the filter table.

Value

A list of plots and/or dataframes depending on whether spatial data quality issues are detected. The list includes:

dataset

Primary data. Up to five logical columns will be added if spatial issues are found: "ON_LAND" (if obs fall on land), "OUTSIDE_ZONE" (if obs occur at sea but outside zone), "ON_ZONE_BOUNDARY" (if obs occurs on zone boundary), "EXPECTED_LOC" (whether obs occurs at sea, within a zone, and not on zone boundary), and "NEAREST_ZONE_DIST_M" (distance in meters from nearest zone. Applies only to obs outside zone or on land).

spatial_summary

Dataframe containing the percentage of observations that occur at sea and within zones, on land, outside zones but at sea, or on zone boundary by year and/or group. The total number of observations by year/group are in the "N" column.

outside_plot

Plot of observations outside regulatory zones.

land_plot

Plot of observations that fall on land.

land_out_plot

Plot of observations that occur on land and are outside the regulatory zones (combines outside_plot and land_plot if both occur).

boundary_plot

Plot of observations that fall on zone boundary.

expected_plot

Plot of observations that occur at sea and within zones.

distance_plot

Histogram of distance form nearest zone (meters) by year for observations that are outside regulatory grid.

distance_freq

Binned frequency table of distance values.

distance_summary

Dataframe containing the minimum, 1st quartile, median, mean, 3rd quartile, and maximum distance values by year and/or group.

Examples

if (FALSE) {
# run spatial checks
spatial_qaqc("pollockMainDataTable", "pollock", spat = NMFS_AREAS, 
             lon.dat = "LonLat_START_LON", lat.dat = "LonLat_START_LAT")
             
# filter obs by distance
spat_out <- 
     spatial_qaqc(pollockMainDataTable, "pollock", spat = NMFS_AREAS,
                  lon.dat = "LonLat_START_LON", lat.dat = "LonLat_START_LAT",
                  filter_dist = 100)
mod.dat <- spat_out$dataset
}