I am trying to plot a very large timeseries charts associated with RasterBrickTimeSeries-class in plotKML. The idea is to divide the RasterBrickTimeSeries into regions, and to use snowfall multicore as well.

A reproducible example is below:

#create a sample point for each cell
pnts <- LST[,47:48] # lon and lat columns
pnts <- cbind(1:nrow(pnts), pnts)
coordinates(pnts) <- ~lon + lat
proj4string(pnts) <- CRS("+proj=longlat +datum=WGS84")

gridded(LST) <- ~lon+lat
proj4string(LST) <- CRS("+proj=longlat +datum=WGS84")
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")
## get the dates from the file names:
LST_ll <- brick(LST[1:5])
LST_ll@title = "Land Surface Temperature images"
LST.ts <- new("RasterBrickTimeSeries", variable = "LST", sampled = pnts, 
              rasters = LST_ll, TimeSpan.begin = TimeSpan.begin[1:5], 
              TimeSpan.end = TimeSpan.end[1:5])
## plot images in Google Earth:
plotKML(LST.ts, colour_scale=SAGA_pal[[1]])

Till here the code is fine, a chart is plotted for each point

Trying the kml.tiles on pnts works:

tiles.LST.ts <- kml.tiles(pnts, block.x=0.05,

Tiles are produced and work fine, but of course it plots only the point locations not the actual charts.

I am not much interested in plotting the raster themselves, rather the timeseries charts only. Hence, plotKML.GDALobj might not be the best option

Is there a way to use kml.tiles on the LST.ts (i.e. RasterBrickTimeSeries) to plot the timeseries charts in parallels and regions?

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