SpatialVx (version 0.6-5)

Sindex: Shape Index

Description

Calculate the shape index (Sindex) as described in AghaKouchak et al. (2011)

Usage

Sindex(x, thresh = NULL, ...)
# S3 method for default
Sindex(x, thresh = NULL, ...,
    loc = NULL)
# S3 method for SpatialVx
Sindex(x, thresh = NULL, ...,
    time.point = 1, obs = 1, model = 1)

Arguments

x

Default: m by n numeric matrix giving the field for which the shape index is to be calculated.

Sindex.SpatialVx: list object of class “SpatialVx”.

thresh

numeric giving a threshold under which (and including, i.e., <=) all values are set to zero, and the shape index is calculated for the non-zero (positive-valued) grid-points.

loc

(optional) mn by 2 numeric matrix giving the grid point locations. If NULL, the expanded grid with x=1:m and y=1:n is used.

time.point

numeric or character indicating which time point from the “SpatialVx” verification set to select for analysis.

obs, model

numeric indicating which observation/forecast model to select for the analysis.

…

Not used.

Value

numeric with named components:

Sindex

the shape index

Pmin,P

the numerator and denominator (perimeter) that make the Sindex.

For SpatialVx objects, the routine is applied to both the verification and forecast objects so that a two-row matrix is returned containing the above vectors for each field.

Details

The shape index introduced in AghaKouchak et al. (2011) is defined as

Sindex = Pmin/P,

where for n = the number of positive-valued grid points, Pmin = 4*sqrt(n) if floor(sqrt(n)) = sqrt(n), and Pmin = 2 * floor(2*sqrt(n)+1) otherwise. P is the permieter of the non-zero grid points. Range is 0 to 1. Values closer to 1 indicate shapes that are closer to circular.

References

AghaKouchak, A., Nasrohllahi, N., Li, J., Imam, B. and Sorooshian, S. (2011) Geometrical characterization of precipitation patterns. J. Hyrdometeorology, 12, 274--285, doi:10.1175/2010JHM1298.1.

See Also

Cindex, Aindex

Examples

# NOT RUN {
# Re-create Fig. 7a from AghaKouchak et al. (2011).
tmp <- matrix(0, 8, 8)
tmp[3,2:4] <- 1
tmp[5,4:6] <- 1
tmp[7,6:7] <- 1
Sindex(tmp)

# }
# NOT RUN {
# Two separate areas with highly structured shapes, but far away from each other.
data( "pert000" )
data( "pert006" )
data( "ICPg240Locs" )

hold <- make.SpatialVx( pert000, pert006, loc = ICPg240Locs,
    projection = TRUE, map = TRUE, loc.byrow = TRUE,
    field.type = "Precipitation", units = "mm/h",
    data.name = "ICP Perturbed Cases", obs.name = "pert000",
    model.name = "pert006" )

plot( hold )

Sindex( hold )
# }
# NOT RUN {
# }