Untitled

df<-read.csv("https://raw.githubusercontent.com/tuyenhavan/Statistics/master/Area_Sentinel-2.csv")

head(df)

##             Land    Area Classifiers
## 1    Agriculture 1242.40         MLC
## 2 Urban/Built-up  104.50         MLC
## 3         Mining  117.10         MLC
## 4         Forest 2001.90         MLC
## 5          Water   54.97         MLC
## 6    Agriculture 1530.10         ANN

COmparing TNMT area and Algorithms-based areas

library(ggplot2)

## Warning: package 'ggplot2' was built under R version 3.3.3

ggplot(data=df,aes(x=Land,y=Area,fill=Classifiers)) + 
  geom_bar(stat="identity",position = "dodge") + scale_fill_discrete(name="Classification Areas") + 
  xlab("Land Cover Types") + ylab("Area (square kilometres)") + theme_bw() + coord_flip()

df<-read.csv("https://raw.githubusercontent.com/tuyenhavan/Statistics/master/Area_Landsat_8.csv")

df1<-df[c(1:15),]

ggplot(data=df,aes(x=Land,y=Area,fill=Classifiers)) + 
  geom_bar(stat="identity",position = "dodge") + scale_fill_discrete(name="Classification Areas") + 
  xlab("Land Cover Types") + ylab("Area (square kilometres)") + theme_bw() + coord_flip()

ggplot(data=df1,aes(x=Land,y=Area,fill=Classifiers)) + 
  geom_bar(stat="identity",position = "dodge") + scale_fill_discrete(name="Classifiers") + 
  xlab("Land Cover Types") + ylab("Area (square kilometres)") + theme_bw()

df2<-read.csv("https://raw.githubusercontent.com/tuyenhavan/Statistics/master/Area_Landsat_Change.csv")

ggplot(data=df2,aes(x=Land,y=Area,fill=Year)) + 
  geom_bar(stat="identity",position = "dodge") + scale_fill_discrete(name="Legend") + 
  xlab("Land Cover Types") + ylab("Area (square kilometres)") + theme_bw()