SP Spatial List operation - error in R 2.9 not in R 2.8 (download example)

Rick Reeves
Scientific Programmer/Analyst and Data Manager
National Center for Ecological Analysis and Synthesis
UC Santa Barbara
www.nceas.ucsb.edu
805 892 2533

The script: 

#########################################################################
# SubsampleImageFiles.r
#  
# This function reads a raster image file, and creates an output
# file with coarser spatial resolution. Technique used: Subsampling.
# Create a sampling grid at a different (usually coarser) resolution
# than the input image, 'overlay' the sampling grid on the input
# image, extract a point from the image at each grid location,
# and then write the sampling grid to an output file in .img format.
# 
# This example demonstrates the R feaures that read, write and display
# raster datasets AND use of the R Spatial objects used to store
# and manipulate raster images.
# 
# Note: as of May 22, 2009, this routine does not work properly
# under R version 2.9: 
# Statement 'SamplingPoints <- as(SamplingGrid,"SpatialPoints")': In R version 2.9,
#            creates incorrect Spatial Points object, with only 2 rows/columns. 
# 
# Author: Rick Reeves
# Date created: 29-Apr-2009                 
# Date modified: 20-May-2009                                                            
# NCEAS
#
#########################################################################
#
SubsampleImageFilesQuest <- function()
{
   library(rgdal)
   library(maptools)  
   library(Hmisc)
#
   SampleFactor <- 2 # A factor of 2 creates a new image with 1/2 the number of pixels as the input image
#
# Step 1) Read input image into a SpatialGridDataFrame object, then display.
# 
   InputImage <- readGDAL("NevadaSiteDEMAlbersSub.tif")      
#
# Create a basic 256-level grey scale 'ramp' for the DEM image
#   
   greys <- grey(0:256 / 256)   
   dev.set(1) # plot in new window      
   grob <- spplot(InputImage, "band1", col.regions=greys,cuts=length(greys))
   plot(grob)    
#
# Create a sampling grid, using the input image's spatial parameters  
#   
   SamplingGridTopology <- GridTopology(InputImage at bbox[,1],
                                       InputImage at grid@cellsize * SampleFactor,
                                       InputImage at grid@cells.dim / SampleFactor)
#
# Create the necessary data structures
#                                       
   SamplingGrid <- SpatialGrid(SamplingGridTopology)  
   OutSpatialGridSGDF <- as(SamplingGrid,"SpatialGridDataFrame")
   SamplingPoints <- as(SamplingGrid,"SpatialPoints")   # In R ver 2.9, this line generates a
#                                                       # SamplingPoints object with 2 rows, 2 cols. 
#                                                       # R ver 2.81 produces a  SamplingPoints object
                                                        # with same number of rows/cols as SamplingGrid
#                                                        
# Subsample the input image, create 
# a SpatialGridDataFrame object.
# 
   SamplingResultsSPDF <- overlay(InputImage,SamplingPoints)    
   OutSpatialGridSGDF at data <- SamplingResultsSPDF at data 
   OutSpatialGridSGDF at proj4string <- CRS(proj4string(InputImage))   
   gridded(OutSpatialGridSGDF) <- TRUE 
#
# use Hmisc library describe() function to compare the incoming and resampled images
#
   message("Summary of incoming and outgoing images (hit key to continue):") 
   Incoming = describe(InputImage at data)
   print(Incoming)
   Outgoing = describe(SamplingResultsSPDF at data)  
   print(Outgoing)
   browser() 
#   
   dev.set(1) # plot in new window
   grob <- spplot(OutSpatialGridSGDF, "band1", col.regions=greys,cuts=length(greys))
   plot(grob)   
}