rasterVis (version 0.21)

horizonplot-methods: Horizon plots of Raster objects.

Description

This method draws horizon graphs for each zone as calculated with zonal from the directions defined by xyLayer

Usage

## S3 method for class 'RasterStackBrick,missing':
horizonplot(x, data=NULL, dirXY=y, digits=0,
    xlab='Time', ylab='direction',
    colorkey=TRUE, colorkey.digits=1,
    scales=list(y=list(relation="same")),
    ...)

docType

methods

Details

(Extracted from the reference): The horizon graph allows to examine how a large number of items changed through time, to spot extraordinary behaviors and predominant patterns, view each of the items independently from the others when they wish, make comparisons between the items, and view changes that occurred with enough precision to determine if further examination is required.

References

http://www.perceptualedge.com/articles/visual_business_intelligence/time_on_the_horizon.pdf

See Also

horizonplot

Examples

##Solar irradiation data from CMSAF
##Data available from http://www.box.net/shared/rl51y1t9sldxk54ogd44

old <- getwd()
##change to your folder...
setwd('CMSAF')
listFich <- dir(pattern='2008')
stackSIS <- stack(listFich)
stackSIS <- stackSIS*24 ##from irradiance (W/m2) to irradiation Wh/m2
setwd(old)

idx <- seq(as.Date('2008-01-15'), as.Date('2008-12-15'), 'month')

SISmm <- setZ(stackSIS, idx)
names(SISmm) <- month.abb

horizonplot(SISmm)

library(zoo)

url <- "ftp://ftp.wiley.com/public/sci_tech_med/spatio_temporal_data/"
sst.dat = read.table(paste(url, "SST011970_032003.dat", sep=''), header = FALSE) 
sst.ll = read.table(paste(url, "SSTlonlat.dat", sep=''), header = FALSE)

spSST <- SpatialPointsDataFrame(sst.ll, sst.dat)
gridded(spSST) <- TRUE
proj4string(spSST) = "+proj=longlat +datum=WGS84"
SST <- brick(spSST)

idx <- seq(as.Date('1970-01-01'), as.Date('2003-03-01'), by='month')
idx <- as.yearmon(idx)
SST <- setZ(SST, idx)
names(SST) <- as.character(idx)
horizonplot(SST)