Compare Ground truth data sets and classes in feature spaces

• Agustin.Lobo@ictja.csic.es
• 20170224

knitr::opts_chunk$set(warning=FALSE, message=FALSE, fig.height=6, fig.width=8,
                      fig.path = "figure/grtruthComparison_")

require(raster)
require(rgdal)
require(plyr)
require(scales)

1. Data

#original digitized polygons
grtruthDN_mean <- readOGR(dsn="../sahara_datatest/grtruthDN_mean",
                          layer="grtruthDN_mean",
                          stringsAsFactors = FALSE)
grtruthDN_mean@data[1,]
grtruthDN_meanPCA <- readOGR(dsn="grtruthDN_meanPCA",
                             layer="grtruthDN_meanPCA",
                             stringsAsFactors = FALSE)
grtruthDN_meanPCA@data[1,]
# ground truth by segments (revised: v2)
grthsegMSv2 <- readOGR(dsn="grthsegMSv2",layer="grthsegMSv2",
                     stringsAsFactors = FALSE)
grthsegMSv2@data[1,]
grthsegMSPCAv2 <- readOGR(dsn="grthsegMSPCAv2",layer="grthsegMSPCAv2",
                        stringsAsFactors = FALSE)
grthsegMSPCAv2@data[1,]

2. Compare segments and original polygons

2.1 Compare segments and original polygons: NIR vs RED

plot(grtruthDN_mean@data[,c(7,10)],type="n",xlab="RED", ylab="NIR")
text(grtruthDN_mean@data[,c(7,10)],label=grtruthDN_mean@data$class,
     col="red",cex=0.75)
text(grthsegMSv2@data[,c(8,11)],label=grthsegMSv2@data$class,cex=0.75)
title(main="Ground Truth in NIR vs RED plane",
      sub="black:segments; red:digitized polygons")

Segmentes become “more grey” “shrubland” very close to “sand” errors in water: some “water” segments are actually “shadow”

2.2 Compare segments and original polygons: PC2 vs PC1

plot(grtruthDN_meanPCA@data[,4:5],type="n")
text(grtruthDN_meanPCA@data[,4:5],labels=grtruthDN_meanPCA@data$class,
     cex=0.75,col="red")
text(grthsegMSPCAv2@data[,5:6],label=grthsegMSPCAv2@data$class,
     cex=0.75)
title(main="Ground Truth in PC space",
      sub="black:segments; red:digitized polygons")

#labels
plot(grtruthDN_meanPCA@data[,4:5],type="n")
#text(grtruthDN_meanPCA@data[,4:5],labels=grtruthDN_meanPCA@data$class,
#     cex=0.75,col="red")
text(grthsegMSPCAv2@data[,5:6],label=grthsegMSPCAv2@data$label,
     cex=0.7)
title(main="Ground Truth (labels) in PC space",
      sub="black:segments; red:digitized polygons")

plot(grtruthDN_meanPCA@data[,c(5,6)],type="n")
text(grtruthDN_meanPCA@data[,c(5,6)],labels=grtruthDN_meanPCA@data$class,
     cex=0.75,col="red")
text(grthsegMSPCAv2@data[,c(6,7)],label=grthsegMSPCAv2@data$class,
     cex=0.75)
title(main="Ground Truth in PC space",
      sub="black:segments; red:digitized polygons")

#Classes are better separated with the revised version (v2)
# errors in water: some "water" segments are actually "shadow"
# revise shrubland and sand again: it might be possible to separate these 2 classes

3. Compare unsupervised clusters to ground truth

colorCodes <- c("red","green","blue","cyan","yellow","pink","orange",
                "black","darkred")

3.1 NIR vs RED

#TODO

3.2 PC2 vs PC1

colorines <- mapvalues(hclass9,from=unique(hclass9),to=colorCodes)
plot(grtruthDN_meanPCA@data[,4:5],type="n")
text(segMSPCArnd@data[,3:4],label=hclass9,cex=0.5,
     col=alpha(colorines,0.75))
# text(grtruthDN_meanPCA@data[,4:5],label=grtruthDN_meanPCA@data$class,
#      col="red", cex=0.75)
text(grthsegMSPCAv2@data[,5:6],label=grthsegMSPCAv2@data$class,cex=0.75)
title(main="Ground Truth in PC2 vs PC1 plane",
      sub="black:segments; red:digitized polygons")

4. Compare clusters (with repetition) to ground truth

colorCodes7 = c("red","green","blue","cyan","yellow","pink","orange")

4.1 NIR vs RED

#TODO

4.2 PC2 vs PC1

#colorines7 <- mapvalues(hclass7r,from=unique(hclass7r),to=colorCodes7)
colorCodes9 <- c("red","green","blue","cyan","yellow","pink","orange","black",
                 "darkred")
colorines9 <- mapvalues(hclass9r,from=unique(hclass9r),to=colorCodes9)
plot(grtruthDN_meanPCA@data[,4:5],type="n")
text(segMSPCArndr@data[,3:4],label=hclass9r,cex=0.7,
     col=alpha(colorines9,0.75))
#text(grtruthDN_meanPCA@data[,4:5],label=grtruthDN_meanPCA@data$grtruthclass,
#     col="red",cex=0.75)
text(grthsegMSPCAv2@data[,5:6],label=grthsegMSPCAv2@data$class, cex=0.75)
title(main="Ground Truth in PC2 vs PC1 plane",
      sub="black:segments; red:digitized polygons")

5. Compare km (with repetition) to ground truth

colorCodes = c("red","green","blue","cyan","yellow","pink","orange")

5.1 NIR vs RED

#TODO

5.2 PC2 vs PC1

# colorines7 <- mapvalues(segMSPCArndr@data$km7r,
#                        from=unique(segMSPCArndr@data$km7r),
#                        to=colorCodes7)
colorCodes9 <- c("red","green","blue","cyan","yellow","pink","orange","black",
                 "darkred")
colorineskm9r <- mapvalues(km9r$cluster,from=unique(km9r$cluster),to=colorCodes9)
plot(grtruthDN_meanPCA@data[,4:5],type="n")
text(segMSPCArndr@data[,3:4],label=segMSPCArndr@data$km9r,cex=0.7,
     col=alpha(colorineskm9r,0.75))
# text(grtruthDN_meanPCA@data[,4:5],label=grtruthDN_meanPCA@data$class,
#      col="red",cex=0.75)
text(grthsegMSPCAv2@data[,5:6],label=grthsegMSPCAv2@data$class, cex=0.75)
title(main="Ground Truth and km9r in PC2 vs PC1 plane",
      sub="black:segments; red:digitized polygons")

6. MCLUST

#TODO