ADW: Angular Distance Weighting interpolation
In rrodrigojrr/ADW: A toolbox for spatial interpolation of meteorogical data

Description Usage Arguments Value Author(s) Examples

View source: R/ADW.R

Apply the Angular Distance Weighting interpolation method on the irregular points of meteorological observations to a regular grid.

1 2	ADW(xy, z, xrange, yrange, res = 0.5, n.station = 8, m = 4, CDD = 50)

`xy`	A matrix (N,2) with longitude and latitude of points of data observed
`z`	A vector (N) with the values observeds in the points
`xrange`	A vector with extremes longitudes of grid eg: c(-45,-35)
`yrange`	A vector with extremes latitudes of grid. eg: c(-1,-5)
`res`	The resolution of grid in degree
`n.station`	Number of stations used per point for interpolation. The default is 8.
`m`	The param m of distance weight. The default is 4.
`CDD`	Correlation distance decay param (Km).The default is 100 km.

A data.frame with longitude, latitude and interpoled points

Rodrigo Lins R. Jr., Fabricio Daniel S. S.

data(TempBrazil) # Temperature for some poins of Brazil


LonLat=TempBrazil[,1:2] #Data.frame with Longtude and Latitude
Temp=TempBrazil[,3] # Vector with observations in points

LonInterval=c(-78,-34.10)  # Coordinates of extremes poins of longitude to grid
LatInterval=c(-36,5)  # Coordinates of extremes poins of latitude to grid

Interpoled=ADW(xy=LonLat,z=Temp,xrange = LonInterval,yrange = LatInterval)