Enhanced Built-Up and Bareness Index {LSRS}

Enhanced Built-Up and Bareness Index

Description

Enhanced Built-Up and Bareness Index (EBBI): The EBBI is a remote sensing index that applies bands of NIR, SWIR, and TIR. The NIR and SWIR bands are associated with a high contrast level for detecting built-up and bare land areas In addition, in these bands, there is an inverse reflectance ratio with respect to detecting built-up or bare land areas compared to vegetation. Vegetation has a high reflectance in NIR band, but the reflectance of built-up or bare land in NIR band is low. subtraction of NIR band from SWIR band will result in positive values for built-up and barren pixels and will result in negative values for vegetation. In addition, a summation of SWIR band and TIR band will result in higher values pixel for built-up and bare land than for vegetation. The difference between the subtraction of NIR band from SWIR band and the summation of SWIR band and TIR band will result in virtually 0 water pixels as well as negative values for vegetation and positive values for built-up and barren pixels. This outcome allows for easy distinguishing between built-up and bare land areas.EBBI can be calculated as:

EBBI=SWIR-Red/10*sqrt(SWIR+TIR)

Usage

EBBI(x = "NIR", y = "SWIR", z = "TIR", Pixel.Depth)

Arguments

x

Red satellite band (format:TIF)

y

SWIR satellite band (format:TIF)

z

TIR satellite band (format:TIF)

Pixel.Depth

for satellite image with digital numbers (DN) of 0 to 255,Pixel.Depth=null and for the larger DN, Pixel.Depth=1

Author(s)

Mehdi Sarparast

References

[1] As syakur, A.R., Adnyana, I.W.S., Arthana, I.W., Nuarsa, I.W., 2012. Enhanced built-UP and bareness index (EBBI) for mapping built-UP and bare land in an urban area. Remote Sens. 4, 2957-2970. doi:10.3390/rs4102957

Examples

## The function is currently defined as
function (x = "NIR", y = "SWIR", z = "TIR", Pixel.Depth)
{
name <- EBBI (a,b,c,Pixel.Depth=1)
areaXY <-c(xmin, xmax, ymin, ymax)
cropXY <- crop(name, areaXY)
plot(cropXY,lwd=4,main=" EBBI ",
     xlab="easting", ylab="northing")
hist(cropXY,main="EBBI "
     ,
     xlab=" EBBI ",col="red", ylab="Frequency of Pixels")
  }