NAME¶
r.surf.idw - Surface interpolation utility for raster map.
KEYWORDS¶
raster, interpolation
SYNOPSIS¶
r.surf.idw
r.surf.idw help
r.surf.idw [-
e]
input=
name output=
name
[
npoints=
integer] [--
overwrite] [--
verbose]
[--
quiet]
Flags:¶
- -e
-
Output is the interpolation error
- --overwrite
-
Allow output files to overwrite existing files
- --verbose
-
Verbose module output
- --quiet
-
Quiet module output
Parameters:¶
- input=name
-
Name of input raster map
- output=name
-
Name for output raster map
- npoints=integer
-
Number of interpolation points
Default: 12
DESCRIPTION¶
r.surf.idw fills a grid cell (raster) matrix with interpolated values
generated from a set of input layer data points. It uses a numerical
approximation technique based on distance squared weighting of the values of
nearest data points. The number of nearest data points used to determined the
interpolated value of a cell can be specified by the user (default: 12 nearest
data points).
If there is a current working mask, it applies to the output raster map. Only
those cells falling within the mask will be assigned interpolated values. The
search procedure for the selection of nearest neighboring points will consider
all input data, without regard to the mask. The
-e flag is the error
analysis option that interpolates values only for those cells of the input
raster map which have non-zero values and outputs the difference (see NOTES
below).
The
npoints parameter defines the number of nearest data points used to
determine the interpolated value of an output raster cell.
NOTES¶
r.surf.idw is a surface generation utility which uses inverse distance
squared weighting (as described in
Applied Geostatistics by E. H.
Isaaks and R. M. Srivastava, Oxford University Press, 1989) to assign
interpolated values. The implementation includes a customized data structure
somewhat akin to a sparse matrix which enhances the efficiency with which
nearest data points are selected. For latitude/longitude projections,
distances are calculated from point to point along a geodesic.
Unlike
r.surf.idw2, which processes all input data points in each
interpolation cycle,
r.surf.idw attempts to minimize the number of
input data for which distances must be calculated. Execution speed is
therefore a function of the search effort, and does not increase appreciably
with the number of input data points.
r.surf.idw will generally outperform
r.surf.idw2 except when the
input data layer contains few non-zero data, i.e. when the cost of the search
exceeds the cost of the additional distance calculations performed by
r.surf.idw2. The relative performance of these utilities will depend on
the comparative speed of boolean, integer and floating point operations on a
particular platform.
Worst case search performance by
r.surf.idw occurs when the interpolated
cell is located outside of the region in which input data are distributed. It
therefore behooves the user to employ a mask when geographic region boundaries
include large areas outside the general extent of the input data.
The degree of smoothing produced by the interpolation will increase relative to
the number of nearest data points considered. The utility may be used with
regularly or irregularly spaced input data. However, the output result for the
former may include unacceptable nonconformities in the surface pattern.
The
-e flag option provides a standard surface-generation error analysis
facility. It produces an output raster map of the difference of interpolated
values minus input values for those cells whose input data are non-zero. For
each interpolation cycle, the known value of the cell under consideration is
ignored, and the remaining input values are used to interpolate a result. The
output raster map may be compared to the input raster map to analyze the
distribution of interpolation error. This procedure may be helpful in choosing
the number of nearest neighbors considered for surface generation.
SEE ALSO¶
r.surf.contour,
r.surf.idw2,
r.surf.gauss,
r.surf.fractal,
r.surf.random,
v.surf.idw,
v.surf.rst
AUTHOR¶
Greg Koerper
Global Climate Research Project
U.S. EPA Environmental Research Laboratory
200 S.W. 35th Street, JSB
Corvallis, OR 97333
Last changed: $Date: 2011-11-08 10:42:51 +0100 (Tue, 08 Nov 2011) $
Full index
© 2003-2014 GRASS Development Team