r.proj(1)	       Grass User's Manual		r.proj(1)



NNAAMMEE
       rr..pprroojj	- Allows the user to re-project a raster map from
       one location to the current location.
       _(_G_R_A_S_S _R_a_s_t_e_r _P_r_o_g_r_a_m_)

SSYYNNOOPPSSIISS
	rr..pprroojj	[[--ll]]   iinnppuutt==nnaammee   llooccaattiioonn==nnaammee   [[oouuttppuutt==nnaammee]]
       [[mmaappsseett==nnaammee]]	[[ddbbaassee==nnaammee]]	[[mmeetthhoodd==nnaammee]]	 [[rreessoolluu--
       ttiioonn==vvaalluuee]]



   FFllaaggss::
       --ll     List raster files in input location and exit


   PPaarraammeetteerrss::
       iinnppuutt  input raster map from source location

       llooccaattiioonn
	      source location of input map

       oouuttppuutt output raster map for current location

       mmaappsseett mapset of input map

       ddbbaassee  path to GRASS database of input location

       mmeetthhoodd interpolation method to use

	      options: nearest,bilinear,cubic

	      default: nearest

       rreessoolluuttiioonn
	      resolution of output map


NNOOTTEESS
       If oouuttppuutt is not specified it is set to	be  the  same  as
       input map name.
       If  ddbbaassee is not specified it is assumed to be the current
       database.
       If mmaappsseett is not specified, its name is assumed to be  the
       same as the current  mapset's name.


       r.proj  supports  transformations between nad27 and nad83.
       It performs the transformation automatically based on  the
       datum specified in the mapset region.  See BUGS section.



DDEESSCCRRIIPPTTIIOONN
       _r_._p_r_o_j  projects  a  raster map in a specified mapset of a
       specified location from the projection of the input  loca-
       tion  to a raster map in the current location. The projec-
       tion information is taken  from	the  momentary	PROJ_INFO
       files.

       IInnttrroodduuccttiioonn

       _M_a_p _p_r_o_j_e_c_t_i_o_n_s

       Map  projections  are a method of representing information
       from a curved surface (usually a spheroid) in  two  dimen-
       sions, typically to allow indexing through cartesian coor-
       dinates.  There are a wide variety  of  projections,  with
       common  ones  divided  into a number of classes, including
       cylindrical  and  pseudo-cylindrical,  conic  and  pseudo-
       conic, and azimuthal methods, each of which may be confor-
       mal, equal-area, or neither.

       The particular projection chosen depends on the purpose of
       the  project, and the size, shape and location of the area
       of interest.  For example, normal cylindrical  projections
       are  good  for  maps which are of greater extent east-west
       than north-south and in equatorial  regions,  while  conic
       projections   are  better  in  mid-latitudes;   transverse
       cylindrical projections are used for  maps  which  are  of
       greater	extent north-south than east-west; azimuthal pro-
       jections are used for polar regions.  Oblique versions  of
       any of these may also be used.  Conformal projections pre-
       serve angular  relationships,  and  better  preserve  arc-
       length,	while equal-area projections are more appropriate
       for statistical studies and work in which  the  amount  of
       material is important.

       Projections are defined by precise mathematical relations,
       so the method of projecting coordinates from a  geographic
       reference  frame  (latitude-longitude)  into  a	projected
       cartesian reference frame (eg metres) is governed by these
       equations.  Inverse projections can also be achieved.  The
       public-domain Unix software  package  _p_r_o_j  [1]	has  been
       designed  to perform these transformations, and the user's
       manual contains a detailed description of over 100  useful
       projections.   This also includes a programmers library of
       the projection methods to support other software  develop-
       ment.

       Thus,  converting  a  "vector"  map - in which objects are
       located with arbitrary spatial precision - from	one  pro-
       jection	into  another is usually accomplished by a simple
       two-step process:  first the location of all the points in
       the  map  are converted from the source through an inverse
       projection into latitude-longitude,  and  then  through	a
       forward projection into the target.  (Of course the proce-
       dure will be one-step if either the source or target is in
       geographic coordinates.)


       Converting  a  "raster  map",  or image, between different
       projections, however, involves additional  considerations.
       A  raster  may  be considered to represent a sampling of a
       process at a regular, ordered set of locations.	 The  set
       of  locations that lie at the intersections of a cartesian
       grid in one projection will not, in general, coincide with
       the  sample  points in another projection.  Thus, the con-
       version of raster maps involves an interpolation  step  in
       which the values of points at intermediate locations rela-
       tive to the source grid are estimated.



       _P_r_o_j_e_c_t_i_n_g _m_a_p_s _w_i_t_h_i_n _t_h_e _G_R_A_S_S _G_I_S


       GIS data capture, import and  transfer  often  requires	a
       projection  step,  since  the  source  or client will fre-
       quently be in a different projection to the  working  pro-
       jection.

       In  some  cases it is convenient to do the conversion out-
       side the package, prior to import or after  export,  using
       software  such as _p_r_o_j [1].  This is certainly the easiest
       method for ssiittee--lliissttss,, since there is no  topology  to  be
       preserved,  and	_p_r_o_j  can be used to process simple lists
       with a one-line command.

       The format of files describing maps containing  lliinneess  and
       aarrccss  is generally more complex, as even in ascii parts of
       the files will describe topology, and not just  locations.
       In  the	GRASS GIS package a program _v_._p_r_o_j is provided to
       convert	 "vector"   maps,   transferring   topology   and
       attributes  as  well as node locations.	This program uses
       the projection definition and parameters which are  stored
       in  the	PROJ_INFO  and	PROJ_UNITS files in the PERMANENT
       mapset directory for every GRASS location.

       However, although it is oriented mainly towards operations
       on  rraasstteerr  mmaappss, the standard GRASS distribution includes
       this _r_._p_r_o_j module to convert raster maps.   That  is  the
       purpose of the program described here.

       DDeessiiggnn ooff rr..pprroojj

       As  discussed  briefly  above, the fundamental step in re-
       projecting a raster is resampling the source grid at loca-
       tions  corresponding to the intersections of a grid in the
       target projection.  The basic procedure for  accomplishing
       this, therefore, is as follows:


       _r_._p_r_o_j  converts  a map to a new geographic projection. It
       reads a map from a different  location,	projects  it  and
       write it out to the current location.
       The  projected data is resampled with one of three differ-
       ent methods: nearest neighbor, bilinear and cubic convolu-
       tion.


       The  nearest  option,  which  performs  a nearest neighbor
       assignment is the fastest of the three resampling methods.
       It  is  primarily used for categorical data such as a land
       use classification, since it will not change the values of
       the  data  cells.  The  bilinear option determines the new
       value of the cell based on a weighted distance average  of
       the 4 surrounding cells in the input map. The cubic option
       determines the new value of the cell based on  a  weighted
       distance  average of the 16 surrounding cells in the input
       map.


       The bilinear and  cubic	interpolation  methods	are  most
       appropriate  for continuous data and cause some smoothing.
       Both options shouldn't  be  used  with  categorical  data,
       since  the cell values will be altered.	If nearest neigh-
       bor assignment is used, the output map has the same raster
       format as the input map. If any of the both interpolations
       is used, the output map is written as floating point.

       Note that, following normal GRASS conventions, the  cover-
       age  and  resolution  of  the resulting grid is set by the
       current region  settings,  which  may  be  adjusted  using
       _g_._r_e_g_i_o_n.   The	target raster will be relatively unbiased
       for all cases if its grid has a similar resolution to  the
       source,	so that the resampling/interpolation step is only
       a local operation.  If the resolution is changed  signifi-
       cantly,	then  the  behaviour  of  the  generalisation  or
       refinement will depend on the model of the  process  being
       represented.   This will be very different for categorical
       versus numerical data.  Note that three	methods  for  the
       local interpolation step are provided.

BBUUGGSS
       Currently  r.proj  does	not support general datum conver-
       sions.  It only	supports  conversion  between  nad27  and
       nad83,  and  only  within  the  CONUS  conversion grid; 20
       degrees to 50 degrees north latitude, 63  degrees  to  131
       degrees	west longitude.  That covers all of the contermi-
       nous USA plus Mexico north of  Mexico  City  and  most  of
       Canada farther south than Winnipeg, Manitoba.


       The  entire input map is read into memory even if portions
       only are transformed. This requires a large amount of mem-
       ory if large raster layers where projected.

RReeffeerreenncceess::
       [1]Evenden,  G.I.   (1990)  Cartographic projection proce-
       dures for the UNIX environment - a  user's  manual.   USGS
       Open-File  Report  90-284 (Also see Interim Report and 2nd
       Interim Report on Release 4, Evenden 1994).


       Richards, John A. (1993),  Remote  Sensing  Digital  Image
       Analysis, Springer-Verlag, Berlin, 2nd edition.

SSEEEE AALLSSOO
       _m_._p_r_o_j_,	_s_._p_r_o_j_, _v_._p_r_o_j_, _g_._s_e_t_p_r_o_j_, _i_._r_e_c_t_i_f_y_, _i_._r_e_c_t_i_f_y_3_,
       _r_._s_u_p_p_o_r_t_, _r_._s_t_a_t_s_, _s_._s_a_m_p_l_e_, _s_._s_u_r_f_._i_d_w_, _s_._s_u_r_f_._r_s_t


AAUUTTHHOORR
       Martin Schroeder, University of Heidelberg, Germany


       Man page text from S.J.D. Cox, AGCRC, CSIRO Exploration	&
       Mining, Nedlands, WA


       Updated by Morten Hulden

       _L_a_s_t _c_h_a_n_g_e_d_: _$_D_a_t_e_: _2_0_0_2_/_0_4_/_2_2 _1_6_:_0_7_:_4_9 _$



GRASS 5.0						r.proj(1)
