plotKML (version 0.2-4)

RasterBrickTimeSeries-class: A class for a time series of regular grids

Description

A class containing list of rasters, begin, end times and sample points to allow exploration of the values. Objects of this class can be directly visualized in Google Earth by using the plotKML-method.

See Also

RasterBrickSimulations-class, plotKML-method

Examples

data(LST)
gridded(LST) <- ~x+y
proj4string(LST) <- CRS("+proj=utm +zone=33 +datum=WGS84 +units=m")
dates <- sapply(strsplit(names(LST), "LST"), function(x){x[[2]]})
datesf <- format(as.Date(dates, "%Y_%m_%d"), "%Y-%m-%dT%H:%M:%SZ")
# begin / end dates +/- 4 days:
TimeSpan.begin = as.POSIXct(unclass(as.POSIXct(datesf))-4*24*60*60, origin="1970-01-01") 
TimeSpan.end = as.POSIXct(unclass(as.POSIXct(datesf))+4*24*60*60, origin="1970-01-01")
LST_ll <- reproject(LST)
# pick few climatic stations:
data(HRtemp08)
pnts <- HRtemp08[which(HRtemp08$NAME=="Pazin")[1],]
pnts <- rbind(pnts, HRtemp08[which(HRtemp08$NAME=="Crni Lug - NP Risnjak")[1],])
pnts <- rbind(pnts, HRtemp08[which(HRtemp08$NAME=="Cres")[1],])
coordinates(pnts) <- ~Lon + Lat
proj4string(pnts) <- CRS("+proj=longlat +datum=WGS84")
# get the dates from the file names:
LST_ll <- brick(LST_ll)
LST_ll@title = "Time series of MODIS Land Surface Temperature (8-day mosaics) images"
LST.ts <- new("RasterBrickTimeSeries", variable = "LST", 
  sampled = pnts, rasters = LST_ll, TimeSpan.begin = TimeSpan.begin, TimeSpan.end = TimeSpan.end)
data(SAGA_pal)
# plot MODIS images in Google Earth:
plotKML(LST.ts, colour_scale=SAGA_pal[[1]])