plotKML (version 0.2-4)

kml_layer.STTDF: Write a space-time trajectory to KML

Description

Writes an object of class "STTDF" to a KML file with a possibility to parse attribute variables using several aesthetics arguments.

Usage

kml_layer.STTDF(obj, id.name = names(obj@data)[which(names(obj@data)== "burst")],
       dtime = "", extrude = FALSE, 
       start.icon = paste(get("home_url", envir = plotKML.opts), "3Dballyellow.png", sep = ""), 
       end.icon = paste(get("home_url", envir = plotKML.opts), "golfhole.png", sep = ""), 
       LabelScale = 0.8 * get("LabelScale", envir = plotKML.opts), z.scale = 1,
       metadata = NULL, html.table = NULL, ...)

Arguments

obj

space-time object of class "STTDF" (spatio-temporal irregular data.frames trajectory)

id.name

trajectory ID column name

dtime

temporal support size (in seconds)

extrude

logical; extrude GPS vertices?

start.icon

start icon name (3Dballyellow.png)

end.icon

destination icon name (golfhole.png)

LabelScale

the default size of icons

z.scale

vertical exaggeration

metadata

(optional) specify the metadata object

html.table

optional description block (html) for each GPS point (vertices)

...

other optional arguments

encoding

latin1

Details

The dateTime is defined as yyyy-mm-ddThh:mm:sszzzzzz, where T is the separator between the date and the time, and the time zone is either Z (for UTC) or zzzzzz, which represents �{+-}hh:mm in relation to UTC. For more info on how Time Stamps work see http://kml-samples.googlecode.com. If the time is measured at block support, then: tags will be inserted. Temporal support ($\Delta t$) is estimated using the xts::periodicity function (median time between observations). The begin time is then derived as $t_1 = t - .5\cdot \Delta t$.

References

• Pebesma, E. (2011) Classes and Methods for Spatio-Temporal Data in R. Journal of Statistical Software.
• spacetime package (http://CRAN.R-project.org/package=spacetime)

See Also

readGPX

Examples

data(gpxbtour)
# format the time column:
gpxbtour$ctime <- as.POSIXct(gpxbtour$time, format="%Y-%m-%dT%H:%M:%SZ")
coordinates(gpxbtour) <- ~lon+lat
proj4string(gpxbtour) <- CRS("+proj=longlat +datum=WGS84")
# derive distance from origin:
library(fossil)
xy <- as.list(data.frame(t(coordinates(gpxbtour))))
gpxbtour$dist.km <- sapply(xy, function(x) 
  deg.dist(long1=x[1], lat1=x[2], long2=xy[[1]][1], lat2=xy[[1]][2]))
plot(gpxbtour$dist.km, gpxbtour$speed, type="l", 
  xlab="Distance from origin in km", ylab="speed in km per hour")
# convert to a STTDF class:
library(spacetime)
library(adehabitat)
gpx.ltraj <- as.ltraj(coordinates(gpxbtour), gpxbtour$ctime, id = "th")
gpx.st <- as(gpx.ltraj, "STTDF")
gpx.st$speed <- gpxbtour$speed
gpx.st@sp@proj4string <- CRS("+proj=longlat +datum=WGS84")
# open KML file:
kml_open("gpxbtour_speed.kml")
# plot trajectory with speed as colour attribute:
kml_layer(obj = gpx.st, colour = speed, z.lim = c(18,32))
# close KML:
kml_close("gpxbtour_speed.kml")
kml_compress("gpxbtour_speed.kml")