r.surf.idw(1)		      Grass User's Manual		 r.surf.idw(1)



NNAAMMEE
       rr..ssuurrff..iiddww - Surface interpolation utility for raster map layers.

SSYYNNOOPPSSIISS
       rr..ssuurrff..iiddww [--ee] iinnppuutt==_n_a_m_e oouuttppuutt==_n_a_m_e [nnppooiinnttss==_v_a_l_u_e]

DDEESSCCRRIIPPTTIIOONN
       _r_._s_u_r_f_._i_d_w  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 val-
       ues 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
       file.  Only those cells falling within the mask will be assigned inter-
       polated values. The search  procedure  for  the	selection  of  nearest
       neighboring  points will consider all input data, without regard to the
       mask.

OOPPTTIIOONNSS
       The command line input is as follows:

   FFllaagg::
       --ee     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).


   PPaarraammeetteerrss::
       iinnppuutt==_n_a_m_e
	      Name of an input raster map layer containing an  incomplete  set
	      of data values. (i.e., some grid cells contain known data values
	      while the rest contain zero (0)).

       oouuttppuutt==_n_a_m_e
	      Name to be assigned to new output raster map that represents the
	      surface generated from the known data values in the input layer.

       nnppooiinnttss==_v_a_l_u_e
	      Number of nearest data points used to determine the interpolated
	      value of an output raster cell.
	      Default: 12


NNOOTTEESS
       _r_._s_u_r_f_._i_d_w  is a surface generation utility which uses inverse distance
       squared weighting (as described	in  AApppplliieedd  GGeeoossttaattiissttiiccss  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 effi-
       ciency with which nearest data points are selected.  For  latitude/lon-
       gitude  projections, distances are calculated from point to point along
       a geodesic.


       Unlike _r_._s_u_r_f_._i_d_w_2, which processes  all  input	data  points  in  each
       interpolation  cycle,  _r_._s_u_r_f_._i_d_w  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 appre-
       ciably with the number of input data points.


       _r_._s_u_r_f_._i_d_w will generally outperform _r_._s_u_r_f_._i_d_w_2 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_._s_u_r_f_._i_d_w_2.   The  relative performance of these utilities will depend
       on the comparative speed of boolean, integer and floating point	opera-
       tions on a particular platform.


       Worst  case  search  performance by _r_._s_u_r_f_._i_d_w occurs when the interpo-
       lated cell is located outside of the region in  which  input  data  are
       distributed.  It therefore behooves the user to employ a mask when geo-
       graphic 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  nonconformi-
       ties in the surface pattern.


       The  --ee flag option provides a standard surface-generation error analy-
       sis 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	neigh-
       bors considered for surface generation.

SSEEEE AALLSSOO
       _r_._m_a_s_k

       _r_._s_u_r_f_._c_o_n_t_o_u_r

       _r_._s_u_r_f_._i_d_w_2

       _s_._s_u_r_f_._i_d_w

       _s_._s_u_r_f_._r_s_t

       _r_._s_u_r_f_._g_a_u_s_s

       _r_._s_u_r_f_._f_r_a_c_t_a_l

       _r_._s_u_r_f_._r_a_n_d_o_m

       _p_a_r_s_e_r

AAUUTTHHOORR
       Greg Koerper
       Global Climate Research Project
       U.S. EPA Environmental Research Laboratory
       200 S.W. 35th Street, JSB
       Corvallis, OR 97333

       _L_a_s_t _c_h_a_n_g_e_d_: _$_D_a_t_e_: _2_0_0_2_/_0_1_/_2_5 _0_5_:_4_5_:_3_4 _$



GRASS 5.0							 r.surf.idw(1)
