3D entropy

Calculates 3D entropy

Usage

entropy_3d(data, bw, grid_size, relative = FALSE)

Arguments

data

data.frame with three columns for x, y, and z coordinates.

bw

Bandwidth to use in 2D kernel density estimator.

grid_size

Size of binning grid, in the unit of the data.

relative

Logical. Rescale entropy relative to the maximum entropy given the number of grid cells? Defaults to FALSE.

Value

Entropy value.

Details

3D entropy consists of three components, including the projected 2D entropy of the XY plane ($CE_xy$), the projected entropy of the XZ plane ($CE_xz$), and the projected entropy of the YZ plane ($CE_yz$), and the final entropy estimate is calculated as follows: $sqrt(CE_xy^2 + CE_xz^2 + CE_yz^2)$.

References

X. Liu, Q. Ma, X. Wu, T. Hu, Z. Liu, L. Liu, Q. Guo, Y. Su (2022). A novel entropy-based method to quantify forest canopy structural complexity from multiplatform lidar point clouds. Remote Sens. Environ. 282, 113280.

Examples

dta <- data.frame(x = rnorm(100,5,1), y = rnorm(100,5,1), z = rnorm(100,5,1))
entropy_3d(dta, bw = 0.5, 0.25)
#> [1] 10.13416
entropy_3d(dta, bw = 0.5, 0.25, relative = TRUE)
#> [1] 0.8444102