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]] [[rreessoolluuttiioonn==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 loca-
       tion from the projection of the input location to a raster map  in  the
       current	location.  The projection information is taken from the momen-
       tary 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 dimensions, typically to allow
       indexing through cartesian coordinates.	There are a  wide  variety  of
       projections, with common ones divided into a number of classes, includ-
       ing cylindrical and pseudo-cylindrical,	conic  and  pseudo-conic,  and
       azimuthal  methods, each of which may be conformal, equal-area, or nei-
       ther.

       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  projections  are  used  for  polar  regions.
       Oblique	versions  of any of these may also be used.  Conformal projec-
       tions preserve angular relationships, and better  preserve  arc-length,
       while equal-area projections are more appropriate for statistical stud-
       ies 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 con-
       tains a detailed description of over 100 useful projections.  This also
       includes  a  programmers  library  of the projection methods to support
       other software development.

       Thus, converting a "vector" map - in which  objects  are  located  with
       arbitrary  spatial precision - from one projection into another is usu-
       ally 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 procedure 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 consid-
       ered 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 conversion of
       raster maps involves an interpolation  step  in	which  the  values  of
       points  at intermediate locations relative to the source grid are esti-
       mated.



       _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 frequently be in a different projection
       to the working projection.

       In some cases it is convenient to do the conversion outside  the  pack-
       age,  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 gener-
       ally  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 locations 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 different methods:
       nearest neighbor, bilinear and cubic convolution.


       The nearest option, which performs a nearest neighbor assignment is the
       fastest of the three resampling methods. It is primarily used for cate-
       gorical 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  sur-
       rounding 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 neighbor 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 coverage and resolu-
       tion 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 oper-
       ation.	If the resolution is changed significantly, 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  interpo-
       lation step are provided.

BBUUGGSS
       Currently  r.proj  does not support general datum conversions.  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  conterminous  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 memory if large raster
       layers where projected.

RReeffeerreenncceess::
       [1]Evenden, G.I.  (1990) Cartographic  projection  procedures  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, Ned-
       lands, 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)
