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trip (version 1.10.0)

write_track_kml: Create a time-continuous KML file

Description

Export track data to a KML file, for use in Google Earth the continuous time slider.

Usage

write_track_kml(
  id,
  lon,
  lat,
  utc,
  z = NULL,
  kml_file = tempfile(fileext = ".kmz"),
  name = NULL,
  altitude_mode = c("absolute", "clampToGround", "clampToSeaFloor", "relativeToGround",
    "relativeToSeaFloor")
)

Value

character vector, file name location of file produced

Arguments

id

vector of grouping IDs (or a trip object)

lon

vector of longitude (ignored if id is a trip)

lat

vector of latitude (ignored if id is a trip)

utc

vector of POSIXct date-times (ignored if id is a trip)

z

vector of elevations, this cannot be set if 'id' is a trip

kml_file

filename for KML (KML or KMZ) (must end in .kml or .kmz)

name

internal name of dat (derived from kml_file if not specified)

altitude_mode

the altitude mode, 'absolute', 'clampToGround', 'clampToSeaFloor', 'relativeToGround', or 'relativeToSeaFloor', see Details

Author

Original implementation by Tomislav Hengl in the 'plotKML' package for 'SpatialLinesDataFrame', adapted by M. Sumner for use in continuous-time form.

Details

To include altitude set every argument explicitly, by input of separate 'id', 'lon', 'lat', 'utc' and 'z' arguments. If the first argument 'id' is a trip object there is no facility to include the 'z' altitude values.

If 'z' is included it is applied as a third coordinate, with 'altitude_mode' controlling the interpretation, see https://developers.google.com/kml/documentation/altitudemode. If the 'kml_file' ends with ".kmz" the file is compressed, otherwise it must end with ".kml" and the compression archive step is not applied.

Sadly the interactive time slider is only available with the desktop version of Google Earth, the data loads into the browser version but can't be interactive.

Examples

Run this code
kfile <- write_track_kml(walrus818[seq(1, 1000, by = 5), ])
print(kfile)
unlink(kfile)

Run the code above in your browser using DataLab