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8fd072d3
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Rick Reeves
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##############################################################################################
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#
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# CreateImageDiffPlots
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#
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# R script generates collection of nine plots that display the distributions of populations of
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# three elevation pixel pairs in proximity to the border between ASTER and STRM data in mosaic
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# images# under development for the Environment and Organisms project.
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#
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#
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# Inputs:
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# 1) Comma Separated Value (CSV) table containing randomly-sampled elevation value pairs,
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# extracted from ASTER/CGIAR mosaic and CDEM images, created by the R script: makeImagePairTable.r
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# Note: At present, be sure that this file has been sorted by column 1 (ColumnID) in Excel
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# before using in this program.
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#
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# 2) sampling factor: integer (range=1 to number of recors in input table. Determines
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# the size of randomly-selected sampe of total table record 'triplets' (north, border,
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# and south) rows of each column sample) to be displayed in the plots:
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# sampling factor = 1 : plot every table record
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# 10 : plot a random sample containing 1/10th of records
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# 100 : plot random sample containing 1/100th of records.
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#
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# To run:
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#
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# 1) place this file and the input file "tableForMark4000_5_8_SortColID.csv" in folder
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# 2) start R
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# 3) > source("CreateImageDiffPlotsOverlay.r")
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# 4) > CreateImageDiffPlots(sampling factor)
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# < press <cr> key to view plots sequentially
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#
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# TODO: add symbol legend to each plot.
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# Author: Rick Reeves, NCEAS
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# May 14, 2011
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##############################################################################################
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CreateImageDiffPlotsNew <- function(plotSampFact = 100)
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{
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# Check plotSampleFact range
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if (plotSampFact < 1)
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plotSampFact = 1
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if (plotSampFact > 100)
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plotSampFact = 100
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# Read input table that was sorted OFFLINE in Excel on the first column (ColumnID)
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pointTable <-read.csv("tableForMark4000_5_8_SortColID.csv")
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# Table created by randomly sampling from two superimposed
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# image:
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# 1) DOM mosaic image comprised of ASTER and SRTM components.
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# 2) 'Baseline' Canadian DEM (CDEM) image.
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#
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# The input table contains three rows for each randomly-selected
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# pixel pair from both images. Each row contains two pixel pairs,
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# the first pair drawn from the image mosaic, the second pair
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# drawn from the CDEM image:
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# First pair: North pixel, South pixel (ASTER/SRTM mosaic)
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# Second pair: North pixel, South pixel (CDEM)
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#
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# The first row of each 'triplet' contains pixel pairs North of border,
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# The second row contains pixel pairs spanning border,
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# The third row contains pixel pairs South of border,
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#
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# This script generates a series of plots that display
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# differences between:
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# 1) The mosaic and CDEM images
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# 2) Image pixels on and away from the ASTER / SRTM boundary.
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#
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northRowIndexes = seq(from=1, to=(nrow(pointTable) - 3),by=3)
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borderRowIndexes = seq(from=2, to=(nrow(pointTable) - 1),by=3)
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southRowIndexes = seq(from=3, to=(nrow(pointTable)),by=3)
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#
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# calculate and append the difference between elevations
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# and CDEM
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# these lines create the inputs for differnce image plots for each of three
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# pixel pair subsets: North of border (All Aster), border (combo Aster/Srtm),
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# South of border (all Srtm)
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#
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# First, add the 'difference columns' to the entire table
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#
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pointTable <-cbind(pointTable,(pointTable$elevNorth - pointTable$elevSouth))
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pointTable <-cbind(pointTable,(pointTable$cdemNorth - pointTable$cdemSouth))
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pointTable <-cbind(pointTable,(pointTable$elevNorth - pointTable$cdemNorth))
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pointTable <-cbind(pointTable,(pointTable$elevSouth - pointTable$cdemSouth))
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#
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colnames(pointTable)[6] <- "diffMosaicNorthSouth"
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colnames(pointTable)[7] <- "diffCDEMNorthSouth"
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colnames(pointTable)[8] <- "diffNorthMosaicCDEM"
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colnames(pointTable)[9] <- "diffSouthMosaicCDEM"
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# add a placeholder for the 'boundary' value, across each table
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# pointTable <-cbind(pointTable,(-1))
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# colnames(pointTable)[10] <- "deltaAcrossBorder"
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# Difference between Mosaic (ASTER or CGIAR or border)
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# and CDEM elevation as pertentage of the mosaic elevation
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pointTable <-cbind(pointTable,(pointTable$diffNorthMosaicCDEM/pointTable$elevNorth * 100))
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pointTable <-cbind(pointTable,(pointTable$diffSouthMosaicCDEM/pointTable$elevSouth * 100))
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colnames(pointTable)[10] <- "magDiffMosaicCDEMNorthPct"
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colnames(pointTable)[11] <- "magDiffMosaicCDEMSouthPct"
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# For the plots, subdivide the table into three segments:
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# rows north of border
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# rows crossing border
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# rows south of border
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northRowTblAll = pointTable[northRowIndexes,]
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borderRowTblAll = pointTable[borderRowIndexes,]
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southRowTblAll = pointTable[southRowIndexes,]
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subset <- 1:nrow(northRowTblAll)
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randSub <- sample(subset,as.integer(length(subset) / plotSampFact))
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northRowTbl <- northRowTblAll[randSub,]
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borderRowTbl <- borderRowTblAll[randSub,]
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southRowTbl <- southRowTblAll[randSub,]
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message("hit key to create each plot...")
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browser()
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# Three plotting characters used
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plotCh1 <- 17 # 'north' (aster) points
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plotCh2 <- 18 # 'border' (aster+srtm) points
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plotCh3 <- 20 # 'south' (srtm) points
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# NEW: Three plots: The difference between Mosaic and CDEM for pixels along
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# each of three border edges: North (ASTER), Border, South (SRTM)
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# for now, north, border, south have separate plots
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# We need to tailor the plot 'triplet' X and Y axes to the dynamic ranges of all three data sets.
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par(mfrow=c(1,3)) # Create a three column multi-plot
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# Create values for the 'delta across pixel boundaries' plot
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deltaBoundaryASTER <- northRowTbl$diffNorthMosaicCDEM - northRowTbl$diffSouthMosaicCDEM
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deltaBoundaryBorder <- borderRowTbl$diffNorthMosaicCDEM - borderRowTbl$diffSouthMosaicCDEM
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deltaBoundarySRTM <- southRowTbl$diffNorthMosaicCDEM - southRowTbl$diffSouthMosaicCDEM
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commonXAxis <- c(0,max(pointTable$ColumnID))
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commonYAxis <- range(c(deltaBoundarySRTM,deltaBoundaryBorder,deltaBoundaryASTER),na.rm=TRUE)
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xAxisLbl <- sprintf("M/SD: ASTER: %.2f / %.2f",mean(deltaBoundaryASTER,na.rm=TRUE),sd(deltaBoundaryASTER,na.rm=TRUE))
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plot(northRowTbl$ColumnID,deltaBoundaryASTER,xlim=commonXAxis, ylim=commonYAxis,main="Difference along Row Boundary: ASTER",xlab=xAxisLbl,col="red",pch=plotCh1)
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xAxisLbl <- sprintf("M/SD: BORDER: %.2f / %.2f",mean(deltaBoundaryBorder,na.rm=TRUE),sd(deltaBoundaryBorder,na.rm=TRUE))
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plot(northRowTbl$ColumnID,deltaBoundaryBorder,xlim=commonXAxis, ylim=commonYAxis,main="Difference along Row Boundary: Border",xlab=xAxisLbl,col="darkgreen",pch=plotCh2)
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xAxisLbl <- sprintf("M/SD: SRTM: %.2f / %.2f",mean(deltaBoundarySRTM,na.rm=TRUE),sd(deltaBoundarySRTM,na.rm=TRUE))
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plot(northRowTbl$ColumnID,deltaBoundarySRTM,main="Difference along Row Boundary: SRTM",xlim=commonXAxis, ylim=commonYAxis,xlab=xAxisLbl,col="blue",pch=plotCh3)
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message("Three-Plot done")
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browser()
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dev.new()
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deltaBoundary <- southRowTbl$diffNorthMosaicCDEM - southRowTbl$diffSouthMosaicCDEM
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xAxisLbl <- sprintf("M/SD: SRTM: %.2f / %.2f",mean(deltaBoundary,na.rm=TRUE),sd(deltaBoundary,na.rm=TRUE))
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plot(northRowTbl$ColumnID,deltaBoundary,main="Difference along Row Boundary: Border",xlab=xAxisLbl,col="red",pch=plotCh1)
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browser()
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xAxisLbl <- sprintf("M/SD: AST: %.2f / %.2f BRD: %.2f / %.2f STM: %.2f / %.2f",mean(northRowTbl$elevSouth,na.rm=TRUE),sd(northRowTbl$elevSouth,na.rm=TRUE),
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mean(borderRowTbl$elevSouth,na.rm=TRUE),sd(borderRowTbl$elevSouth,na.rm=TRUE),
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mean(southRowTbl$elevSouth,na.rm=TRUE),sd(southRowTbl$elevSouth,na.rm=TRUE))
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plot(northRowTbl$ColumnID,northRowTbl$elevSouth,main="South Mosaic Pixel Elev: ASTER (red) Border (green) SRTM (blue)",xlab=xAxisLbl,col="red",pch=plotCh1)
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points(borderRowTbl$ColumnID,borderRowTbl$elevSouth,col="darkgreen",pch=plotCh2)
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points(southRowTbl$ColumnID,southRowTbl$elevSouth,col="blue",pch=plotCh3)
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browser()
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dev.new()
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# Second plot pair: North/South CDEM pixel elevation for North/South subsets 'distance East from Western edge'.
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xAxisLbl <- sprintf("M/SD: AST: %.2f / %.2f BRD: %.2f / %.2f STM: %.2f / %.2f",mean(northRowTbl$cdemNorth,na.rm=TRUE),sd(northRowTbl$cdemNorth,na.rm=TRUE),
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mean(borderRowTbl$cdemNorth,na.rm=TRUE),sd(borderRowTbl$cdemNorth,na.rm=TRUE),
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mean(southRowTbl$cdemNorth,na.rm=TRUE),sd(southRowTbl$cdemNorth,na.rm=TRUE))
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plot(northRowTbl$ColumnID,northRowTbl$cdemNorth,main="North CDEM Pixel Elev ASTER (r) Border (g) SRTM (b)",xlab=xAxisLbl,col="red",pch=plotCh1)
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points(borderRowTbl$ColumnID,borderRowTbl$cdemNorth,col="darkgreen",pch=plotCh2)
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points(southRowTbl$ColumnID,southRowTbl$cdemNorth,col="blue",pch=plotCh3)
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browser()
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dev.new()
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xAxisLbl <- sprintf("M/SD: AST: %.2f / %.2f BRD: %.2f / %.2f STM: %.2f / %.2f",mean(northRowTbl$cdemSouth,na.rm=TRUE),sd(northRowTbl$cdemSouth,na.rm=TRUE),
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mean(borderRowTbl$cdemSouth,na.rm=TRUE),sd(borderRowTbl$cdemSouth,na.rm=TRUE),
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mean(southRowTbl$cdemSouth,na.rm=TRUE),sd(southRowTbl$cdemSouth,na.rm=TRUE))
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plot(northRowTbl$ColumnID,northRowTbl$cdemSouth,main="South CDEM Pixel Elev ASTER (r) Border (g) SRTM (b)",xlab=xAxisLbl,col="red",pch=plotCh1)
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points(borderRowTbl$ColumnID,borderRowTbl$cdemSouth,col="darkgreen",pch=plotCh2)
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points(southRowTbl$ColumnID,southRowTbl$cdemSouth,col="blue",pch=plotCh3)
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browser()
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dev.new()
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message("All plots created - hit key to delete them...")
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browser()
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graphics.off()
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}
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