Dear Peter, The spatial taskview lists a number of interpolation methods [1]. Some of those support spatio-temporal interpolation. For example gstat supports spatio-temporal kriging [2,3,4].
regards, Paul [1] http://cran.r-project.org/web/views/Spatial.html [2] http://en.wikipedia.org/wiki/Kriging [3] http://www.google.nl/search?q=space+time+kriging [4] http://cran.r-project.org/web/packages/gstat/index.html On 07/30/2011 08:35 PM, Peter Maclean wrote: > Dear GIS people > What is the best way of implemeting spatial data interpolation (from large to > small grids)-especially for dummies. I searched the internet and could not > get concrete answer. Here is an example with simulated data. > > #Example of spatial data interpolation > require(utils) > #I need to interpolate the temp and rain data (from its surounding points) > #for the same period and accoubting for elevation > #New coordinates and elevation > lat <-seq(-1, -5, by=-0.1) > lon <-seq(28, 30, by=0.1) > year <- seq(2000, 2005, by=1) > period <- c("Mar", "Apr","May") > ndata <- list(year=year,period=period,lat=lat, lon=lon) > ndata <- expand.grid(ndata) > ndata$elev <-sample(1000: 8000,nrow(ndata),replace=T) > ndata <- ndata[order(ndata$year,ndata$period) , ] > fix(ndata) > > #Original data with elevation-same period > lat <- seq(-1, -5, by=-0.5) > lon <- seq(28, 30, by=0.5) > data <- list(year=year,period=period,lat=lat, lon=lon) > data <- expand.grid(data) > data$temp <- sample(15:100, nrow(data),replace=T) > data$rain <- sample(0: 1000,nrow(data),replace=T) > data <- data[order(data$year,data$period) , ] > data <- na.omit(merge(data,ndata, by=c("year", "period", "lat","lon"))) > fix(data) > ########## > #Spatial-Temporal Interpolation from original data (temp & rain) to new data > > > Peter Maclean > Department of Economics > UDSM > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. -- Paul Hiemstra, Ph.D. Global Climate Division Royal Netherlands Meteorological Institute (KNMI) Wilhelminalaan 10 | 3732 GK | De Bilt | Kamer B 3.39 P.O. Box 201 | 3730 AE | De Bilt tel: +31 30 2206 494 http://intamap.geo.uu.nl/~paul http://nl.linkedin.com/pub/paul-hiemstra/20/30b/770 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.