| 1 |
77ed568c
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Jim Regetz
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library(raster)
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#Get list of tile names and add full pathname to beginning
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Tiles <- list.files("DEM/asterGdem/N59to81_W20toE19", pattern="^ASTGTM.*_dem.tif$")
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Tiles<- paste("DEM/asterGdem/N59to81_W20toE19/", Tiles, sep="")
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# datavalues: 0= water, -9999= nodata
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#Create new vectors for name of tile and accompanying % of cells= ocean and non-landmass
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# IF % OCEAN AND % NON-LAND ARE VERY DIFFERENT USE % NON-LAND FOR QC CHECK, IF THEY
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# ARE THE SAME, % OCEAN IS FASTER TO CALCULATE SO USE THIS
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l<- length (Tiles)
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Names<- c(1:l)*NA
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PctNotLand<- c(1:l) * NA
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PctOcean<- c(1:l)*NA
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#Fill vectors with % of each tiles where pixel value = 0 (water) OR 0 & -9999 (water or nodata)
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for (i in 1:l){
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Names[i]<-sapply(strsplit(Tiles[i], '[/]'), '[[', 4)
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PctOcean[i]<- count(raster(Tiles[i]),0)/ncell(raster(Tiles[i]))
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PctNotLand[i]<- (count(raster(Tiles[i]),0)+count(raster(Tiles[i]),-9999))/ncell(raster(Tiles[i]))
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}
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data.frame (Names, PctOcean,PctNotLand)
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#Use the above calculation to calculate % landmass for each tile and compare total over all tiles
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# in folder to % landmass of USGS coverage for same area.
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# Requires aggregating aster tiles to match pixel size of USGS coverage:
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LandAgg<- c(1:l) * NA
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Counts_Agg<- c(1:l)*NA
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for (i in 1:l){
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Counts_Agg[i]<- count(aggregate(raster(Tiles[i]),30),0)+count(aggregate(raster(Tiles[i]),30),-9999)
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LandAgg[i]<- ncell(aggregate(raster(Tiles[i]),30))-Counts_Agg[i]
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}
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a<-sum(LandAgg)
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#Calculate % landmass in USGS coverage and compare:
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AstRast<- raster("DEM/asterGdem/N59to81_W20toE19/w020n90/W020N90_clipped.dem")
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b<-ncell(AstRast)-cellStats(AstRast, "countNA") #Total # cells- cells with no value
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1-(b/a) #Difference= 4.49%
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#------------------------------------------------------------------
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#after first try, anytime PctNotLand was >= 99%, so too was PctOcean and visa versa
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# All subsequent runs will only calc. PctOcean to save time
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Tiles <- list.files("DEM/asterGdem/N59to81_E20to59", pattern="^ASTGTM.*_dem.tif$")
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Tiles<- paste("DEM/asterGdem/N59to81_E20to59/", Tiles, sep="")
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l<- length (Tiles)
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Names<- c(1:l)*NA
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PctNotLand<- c(1:l) * NA
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PctOcean<- c(1:l)*NA
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for (i in 1:l){
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Names[i]<-sapply(strsplit(Tiles[i], '[/]'), '[[', 4)
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PctOcean[i]<- count(raster(Tiles[i]),0)/ncell(raster(Tiles[i]))
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}
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data.frame (Names, PctOcean)
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LandAgg<- c(1:l) * NA
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Counts_Agg<- c(1:l)*NA
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for (i in 1:l){
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Counts_Agg[i]<- count(aggregate(raster(Tiles[i]),30),0)+count(aggregate(raster(Tiles[i]),30),-9999)
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LandAgg[i]<- ncell(aggregate(raster(Tiles[i]),30))-Counts_Agg[i]
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print( paste(round(100*i/l),"%",sep=""), quote=FALSE )
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}
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a<-sum(LandAgg)
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AstRast<- raster("DEM/asterGdem/N59to81_E20to59/e020n90/E020N90_clipped.dem")
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b<-ncell(AstRast)-cellStats(AstRast, "countNA") #Total # cells- cells with no value
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1-(b/a) #Difference= 2.21%
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#-----------------------------------------------------------------------
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Tiles <- list.files("DEM/asterGdem/N59to81_E60to99", pattern="^ASTGTM.*_dem.tif$")
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Tiles<- paste("DEM/asterGdem/N59to81_E60to99/", Tiles, sep="")
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l<- length (Tiles)
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Names<- c(1:l)*NA
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PctNotLand<- c(1:l) * NA
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PctOcean<- c(1:l)*NA
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for (i in 1:l){
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Names[i]<-sapply(strsplit(Tiles[i], '[/]'), '[[', 4)
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PctOcean[i]<- count(raster(Tiles[i]),0)/ncell(raster(Tiles[i]))
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}
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data.frame (Names, PctOcean)
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LandAgg<- c(1:l) * NA
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Counts_Agg<- c(1:l)*NA
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for (i in 1:l){
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Counts_Agg[i]<- count(aggregate(raster(Tiles[i]),30),0)+count(aggregate(raster(Tiles[i]),30),-9999)
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LandAgg[i]<- ncell(aggregate(raster(Tiles[i]),30))-Counts_Agg[i]
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}
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a<-sum(LandAgg)
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AstRast<- raster("DEM/asterGdem/N59to81_E60to99/USGS_ErosDEM_N59to81E60to99/E060N90_clipped.dem")
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b<-ncell(AstRast)-cellStats(AstRast, "countNA") #Total # cells- cells with no value
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1-(b/a) # Datasets differ by 2.27%
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cellStats(AstRast,max)
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cellStats(AstRast,min)
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count(AstRast, NA)
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#-----------------------------------------------------------------------
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Tiles <- list.files("DEM/asterGdem/N59to81_E100to139", pattern="^ASTGTM.*_dem.tif$")
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Tiles<- paste("DEM/asterGdem/N59to81_E100to139/", Tiles, sep="")
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l<- length (Tiles)
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Names<- c(1:l)*NA
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PctNotLand<- c(1:l) * NA
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PctOcean<- c(1:l)*NA
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for (i in 1:l){
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Names[i]<-sapply(strsplit(Tiles[i], '[/]'), '[[', 4)
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PctOcean[i]<- count(raster(Tiles[i]),0)/ncell(raster(Tiles[i]))
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}
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| 120 |
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| 121 |
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data.frame (Names, PctOcean)
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| 122 |
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| 123 |
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LandAgg<- c(1:l) * NA
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| 124 |
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Counts_Agg<- c(1:l)*NA
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| 125 |
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for (i in 1:l){
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Counts_Agg[i]<- count(aggregate(raster(Tiles[i]),30),0)+count(aggregate(raster(Tiles[i]),30),-9999)
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LandAgg[i]<- ncell(aggregate(raster(Tiles[i]),30))-Counts_Agg[i]
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print( paste(round(100*i/l),"%",sep=""), quote=FALSE )
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}
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a<-sum(LandAgg)
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AstRast<- raster("DEM/asterGdem/N59to81_E100to139/e100n90/E100N90_clipped.dem")
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b<-ncell(AstRast)-cellStats(AstRast, "countNA") #Total # cells- cells with no value
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1-(b/a) #Difference= 3.1%
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#-----------------------------------------------------------------------
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Tiles <- list.files("DEM/asterGdem/N59to81_E140to179", pattern="^ASTGTM.*_dem.tif$")
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Tiles<- paste("DEM/asterGdem/N59to81_E140to179/", Tiles, sep="")
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l<- length (Tiles)
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Names<- c(1:l)*NA
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PctNotLand<- c(1:l) * NA
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PctOcean<- c(1:l)*NA
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for (i in 1:l){
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Names[i]<-sapply(strsplit(Tiles[i], '[/]'), '[[', 4)
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PctOcean[i]<- count(raster(Tiles[i]),0)/ncell(raster(Tiles[i]))
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}
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data.frame (Names, PctOcean)
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LandAgg<- c(1:l) * NA
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Counts_Agg<- c(1:l)*NA
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for (i in 1:l){
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Counts_Agg[i]<- count(aggregate(raster(Tiles[i]),30),0)+count(aggregate(raster(Tiles[i]),30),-9999)
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LandAgg[i]<- ncell(aggregate(raster(Tiles[i]),30))-Counts_Agg[i]
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print( paste(round(100*i/l),"%",sep=""), quote=FALSE )
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}
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a<-sum(LandAgg)
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AstRast<- raster("DEM/asterGdem/N59to81_E140to179/e140n90/E140N90_clipped.dem")
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b<-ncell(AstRast)-cellStats(AstRast, "countNA") #Total # cells- cells with no value
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1-(b/a) #Difference= 3.4%
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#-----------------------------------------------------------------------
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Tiles <- list.files("DEM/asterGdem/N59to81_W60to21", pattern="^ASTGTM.*_dem.tif$")
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Tiles<- paste("DEM/asterGdem/N59to81_W60to21/", Tiles, sep="")
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l<- length (Tiles)
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Names<- c(1:l)*NA
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PctNotLand<- c(1:l) * NA
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PctOcean<- c(1:l)*NA
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for (i in 1:l){
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Names[i]<-sapply(strsplit(Tiles[i], '[/]'), '[[', 4)
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PctOcean[i]<- count(raster(Tiles[i]),0)/ncell(raster(Tiles[i]))
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}
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data.frame (Names, PctOcean)
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| 176 |
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| 177 |
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LandAgg<- c(1:l) * NA
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| 178 |
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Counts_Agg<- c(1:l)*NA
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| 179 |
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for (i in 1:l){
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| 180 |
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Counts_Agg[i]<- count(aggregate(raster(Tiles[i]),30),0)+count(aggregate(raster(Tiles[i]),30),-9999)
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LandAgg[i]<- ncell(aggregate(raster(Tiles[i]),30))-Counts_Agg[i]
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print( paste(round(100*i/l),"%",sep=""), quote=FALSE )
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}
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a<-sum(LandAgg)
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AstRast<- raster("DEM/asterGdem/N59to81_W60to21/w060n90/W060N90_clipped.dem")
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b<-ncell(AstRast)-cellStats(AstRast, "countNA") #Total # cells- cells with no value
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1-(b/a) #Difference= 3.03%
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#-----------------------------------------------------------------------
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Tiles <- list.files("DEM/asterGdem/N59to81_W180to141", pattern="^ASTGTM.*_dem.tif$")
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Tiles<- paste("DEM/asterGdem/N59to81_W180to141/", Tiles, sep="")
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| 192 |
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| 193 |
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l<- length (Tiles)
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| 194 |
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Names<- c(1:l)*NA
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| 195 |
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PctNotLand<- c(1:l) * NA
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| 196 |
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PctOcean<- c(1:l)*NA
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| 197 |
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for (i in 1:l){
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| 198 |
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Names[i]<-sapply(strsplit(Tiles[i], '[/]'), '[[', 4)
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| 199 |
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PctOcean[i]<- count(raster(Tiles[i]),0)/ncell(raster(Tiles[i]))
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| 200 |
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}
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| 201 |
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| 202 |
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data.frame (Names, PctOcean)
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| 203 |
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| 204 |
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LandAgg<- c(1:l) * NA
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| 205 |
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Counts_Agg<- c(1:l)*NA
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| 206 |
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for (i in 1:l){
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| 207 |
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Counts_Agg[i]<- count(aggregate(raster(Tiles[i]),30),0)+count(aggregate(raster(Tiles[i]),30),-9999)
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| 208 |
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LandAgg[i]<- ncell(aggregate(raster(Tiles[i]),30))-Counts_Agg[i]
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| 209 |
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print( paste(round(100*i/l),"%",sep=""), quote=FALSE )
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}
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| 211 |
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| 212 |
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a<-sum(LandAgg)
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| 213 |
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AstRast<- raster("DEM/asterGdem/N59to81_W180to141/w180n90/W180N90_clipped.dem")
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| 214 |
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b<-ncell(AstRast)-cellStats(AstRast, "countNA") #Total # cells- cells with no value
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| 215 |
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1-(b/a) #Difference= 2.87%
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| 216 |
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#-----------------------------------------------------------------------
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| 217 |
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Tiles <- list.files("DEM/asterGdem/N59to81_W140to101", pattern="^ASTGTM.*_dem.tif$")
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| 218 |
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Tiles<- paste("DEM/asterGdem/N59to81_W140to101/", Tiles, sep="")
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| 219 |
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| 220 |
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l<- length (Tiles)
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| 221 |
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Names<- c(1:l)*NA
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| 222 |
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PctNotLand<- c(1:l) * NA
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| 223 |
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PctOcean<- c(1:l)*NA
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| 224 |
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for (i in 1:l){
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| 225 |
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Names[i]<-sapply(strsplit(Tiles[i], '[/]'), '[[', 4)
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| 226 |
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PctOcean[i]<- count(raster(Tiles[i]),0)/ncell(raster(Tiles[i]))
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| 227 |
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}
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| 228 |
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| 229 |
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data.frame (Names, PctOcean)
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| 230 |
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| 231 |
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LandAgg<- c(1:l) * NA
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| 232 |
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Counts_Agg<- c(1:l)*NA
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| 233 |
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for (i in 1:l){
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| 234 |
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Counts_Agg[i]<- count(aggregate(raster(Tiles[i]),30),0)+count(aggregate(raster(Tiles[i]),30),-9999)
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| 235 |
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LandAgg[i]<- ncell(aggregate(raster(Tiles[i]),30))-Counts_Agg[i]
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| 236 |
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print( paste(round(100*i/l),"%",sep=""), quote=FALSE )
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| 237 |
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}
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| 238 |
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| 239 |
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a<-sum(LandAgg)
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| 240 |
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AstRast<- raster("DEM/asterGdem/N59to81_W140to101/w140n90/W140N90_clipped.dem")
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| 241 |
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b<-ncell(AstRast)-cellStats(AstRast, "countNA") #Total # cells- cells with no value
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| 242 |
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1-(b/a) #Difference= 3.84%
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| 243 |
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#-----------------------------------------------------------------------
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| 244 |
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Tiles <- list.files("DEM/asterGdem/N59to81_W100to61", pattern="^ASTGTM.*_dem.tif$")
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| 245 |
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Tiles<- paste("DEM/asterGdem/N59to81_W100to61/", Tiles, sep="")
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| 246 |
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| 247 |
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l<- length (Tiles)
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| 248 |
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Names<- c(1:l)*NA
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| 249 |
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PctNotLand<- c(1:l) * NA
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| 250 |
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PctOcean<- c(1:l)*NA
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| 251 |
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for (i in 1:l){
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| 252 |
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Names[i]<-sapply(strsplit(Tiles[i], '[/]'), '[[', 4)
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| 253 |
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PctOcean[i]<- count(raster(Tiles[i]),0)/ncell(raster(Tiles[i]))
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| 254 |
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}
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| 255 |
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| 256 |
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data.frame (Names, PctOcean)
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| 257 |
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| 258 |
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LandAgg<- c(1:l) * NA
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| 259 |
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Counts_Agg<- c(1:l)*NA
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| 260 |
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for (i in 1:l){
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| 261 |
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Counts_Agg[i]<- count(aggregate(raster(Tiles[i]),30),0)+count(aggregate(raster(Tiles[i]),30),-9999)
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| 262 |
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LandAgg[i]<- ncell(aggregate(raster(Tiles[i]),30))-Counts_Agg[i]
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| 263 |
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print( paste(round(100*i/l),"%",sep=""), quote=FALSE )
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| 264 |
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}
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| 265 |
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| 266 |
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a<-sum(LandAgg)
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| 267 |
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AstRast<- raster("DEM/asterGdem/N59to81_W100to61/w100n90/W100N90_clipped.dem")
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| 268 |
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b<-ncell(AstRast)-cellStats(AstRast, "countNA") #Total # cells- cells with no value
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| 269 |
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1-(b/a) #Difference= 7.21% (lot's of coastline in this set of tiles!)
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| 270 |
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#-------------------------------------------------------------------
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| 271 |
|
|
c<- raster("DEM/asterGdem/N59to81_E60to99/USGS_ErosDEM_N59to81E60to99/E060N90.DEM")
|
| 272 |
|
|
a<- raster("DEM/asterGdem/N59to81_E60to99/USGS_ErosDEM_N59to81E60to99/E060N90_clipped.dem")
|
| 273 |
|
|
b<- raster(nrow=82800, ncol=144000)
|
| 274 |
|
|
d<- raster("DEM/asterGdem/N59to81_E60to99/ASTGTM_N59E060_dem.tif")
|
| 275 |
|
|
s<- resample(a,b,method='ngb')
|
| 276 |
|
|
disaggregate(a,30)
|
| 277 |
|
|
e<-aggregate(d,30)
|
| 278 |
|
|
|
| 279 |
|
|
count(e, -9999)
|
| 280 |
|
|
count (e,0)
|
