bdri: Band depth ratio indices

In hsdar: Manage, Analyse and Simulate Hyperspectral Data

Band depth ratio indices

Description

Calculate band depth ratio indices for objects of class Specfeat.

Usage

bdri(x, fnumber, index = "ndbi") 

Arguments

x	Object of class Specfeat.
fnumber	Integer. Index of feature to modify.
index	Method to be applied. Currently, "bdr", "ndbi" and "bna" are available.

Details

Method "bdr" calculates the normalised band depth ratio as

bdr=\frac{BD}{Dc},

with BD is the band depth calculated by transformSpeclib and Dc is the maximum band depth called band centre. Method "ndbi" calculates the the normalised band depth index as

ndbi= \frac{BD-Dc}{BD+Dc}.

Method "bna" calculates the band depth normalised to band area as

bna=\frac{BD}{Da},

where Da is the area of the absorption feature (see feature_properties). For further information see Mutanga and Skidmore (2004).

Value

Object of class specfeat containing the updated version of x.

Author(s)

Lukas Lehnert and Hanna Meyer

References

Mutanga, O. and Skidmore, A. (2004): Hyperspectral band depth analysis for a better estimation of grass biomass (Cenchrus ciliaris) measured under controlled laboratory conditions. International Journal of applied Earth Observation and Geoinformation, 5, 87-96

See Also

transformSpeclib, specfeat

Examples

data(spectral_data)

## Transform speclib
bd <- transformSpeclib(subset(spectral_data, season == "summer"),
                       method = "sh", out = "bd")

## Isolate the features around 450nm, 700nm, 1200nm and 1500nm and 
## convert to specfeat.
featureSelection <- specfeat(bd, c(450,700,1200,1500))

## Plot features
plot(featureSelection,1:4)

## Calculate normalized band depth index for first feature
featureSelection_bdri <- bdri(featureSelection, 1, index = "ndbi")

## Plot result
plot(featureSelection_bdri)

hsdar documentation built on March 18, 2022, 6:35 p.m.