1r.proj(1) Grass User's Manual r.proj(1)
2
6 r.proj - Re-project a raster map from one location to the current
7 location.
8
10 raster
11
13 r.proj
14 r.proj help
15 r.proj [-ln] input=string location=string [mapset=string]
16 [dbase=string] [output=name] [method=string] [resolution=float]
17 [--overwrite]
18 Flags:
20 -l List raster files in input location and exit
21 -n Do not perform region cropping optimization
23 --overwrite
25 Parameters:
27 input=string
28 Input raster map
29 location=string
31 Location of input map
32 mapset=string
34 Mapset of input map
35 dbase=string
37 Path to GRASS database of input location
38 output=name
40 Name for output raster map
41 method=string
43 Interpolation method to use Options: nearest,bilinear,cubic
44 Default: nearest
45 resolution=float
47 Resolution of output map
48
50 r.proj projects a raster map in a specified mapset of a specified loca‐
51 tion from the projection of the input location to a raster map in the
52 current location. The projection information is taken from the current
53 PROJ_INFO files, as set with g.setproj
54 and viewed with g.proj.
55 Introduction
57 Map projections Map projections are a method of representing informa‐
58 tion from a curved surface (usually a spheroid) in two dimensions, typ‐
59 ically to allow indexing through cartesian coordinates. There are a
60 wide variety of projections, with common ones divided into a number of
61 classes, including cylindrical and pseudo-cylindrical, conic and
62 pseudo-conic, and azimuthal methods, each of which may be conformal,
63 equal-area, or neither.
64 The particular projection chosen depends on the purpose of the project,
66 and the size, shape and location of the area of interest. For example,
67 normal cylindrical projections are good for maps which are of greater
68 extent east-west than north-south and in equatorial regions, while
69 conic projections are better in mid-latitudes; transverse cylindrical
70 projections are used for maps which are of greater extent north-south
71 than east-west; azimuthal projections are used for polar regions.
72 Oblique versions of any of these may also be used. Conformal projec‐
73 tions preserve angular relationships, and better preserve arc-length,
74 while equal-area projections are more appropriate for statistical stud‐
75 ies and work in which the amount of material is important.
76 Projections are defined by precise mathematical relations, so the
78 method of projecting coordinates from a geographic reference frame
79 (latitude-longitude) into a projected cartesian reference frame (eg
80 metres) is governed by these equations. Inverse projections can also
81 be achieved. The public-domain Unix software package proj [1] has been
82 designed to perform these transformations, and the user's manual con‐
83 tains a detailed description of over 100 useful projections. This also
84 includes a programmers library of the projection methods to support
85 other software development.
86 Thus, converting a "vector" map - in which objects are located with
88 arbitrary spatial precision - from one projection into another is usu‐
89 ally accomplished by a simple two-step process: first the location of
90 all the points in the map are converted from the source through an
91 inverse projection into latitude-longitude, and then through a forward
92 projection into the target. (Of course the procedure will be one-step
93 if either the source or target is in geographic coordinates.)
94 Converting a "raster map", or image, between different projections,
96 however, involves additional considerations. A raster may be consid‐
97 ered to represent a sampling of a process at a regular, ordered set of
98 locations. The set of locations that lie at the intersections of a
99 cartesian grid in one projection will not, in general, coincide with
100 the sample points in another projection. Thus, the conversion of
101 raster maps involves an interpolation step in which the values of
102 points at intermediate locations relative to the source grid are esti‐
103 mated. Projecting vector maps within the GRASS GIS GIS data capture,
104 import and transfer often requires a projection step, since the source
105 or client will frequently be in a different projection to the working
106 projection.
107 In some cases it is convenient to do the conversion outside the pack‐
109 age, prior to import or after export, using software such as PROJ4's
110 cs2cs [1]. This is an easy method for converting an ASCII file contain‐
111 ing a list of coordinate points, since there is no topology to be pre‐
112 served and cs2cs can be used to process simple lists using a one-line
113 command.
114 The format of vector files describing maps containing lines and arcs is
116 generally more complex, as parts of the data stored in the files will
117 describe topology, and not just coordinates. In GRASS GIS the v.proj
118 module is provided to reproject "vector" maps, transferring topology
119 and attributes as well as node coordinates. This program uses the pro‐
120 jection definition and parameters which are stored in the PROJ_INFO and
121 PROJ_UNITS files in the PERMANENT mapset directory for every GRASS
122 location.
123 Design of r.proj
125 As discussed briefly above, the fundamental step in re-projecting a
126 raster is resampling the source grid at locations corresponding to the
127 intersections of a grid in the target projection. The basic procedure
128 for accomplishing this, therefore, is as follows:
129 r.proj converts a map to a new geographic projection. It reads a map
131 from a different location, projects it and write it out to the current
132 location.
133 The projected data is resampled with one of three different methods:
134 nearest neighbor, bilinear and cubic convolution.
135 The nearest option, which performs a nearest neighbor assignment is the
137 fastest of the three resampling methods. It is primarily used for cate‐
138 gorical data such as a land use classification, since it will not
139 change the values of the data cells. The bilinear option determines the
140 new value of the cell based on a weighted distance average of the 4
141 surrounding cells in the input map. The cubic option determines the new
142 value of the cell based on a weighted distance average of the 16 sur‐
143 rounding cells in the input map.
144 The bilinear and cubic interpolation methods are most appropriate for
146 continuous data and cause some smoothing. Both options should not be
147 used with categorical data, since the cell values will be altered. If
148 nearest neighbor assignment is used, the output map has the same raster
149 format as the input map. If any of the both interpolations is used, the
150 output map is written as floating point.
151 Note that, following normal GRASS conventions, the coverage and resolu‐
153 tion of the resulting grid is set by the current region settings, which
154 may be adjusted using g.region. The target raster will be relatively
155 unbiased for all cases if its grid has a similar resolution to the
156 source, so that the resampling/interpolation step is only a local oper‐
157 ation. If the resolution is changed significantly, then the behaviour
158 of the generalisation or refinement will depend on the model of the
159 process being represented. This will be very different for categorical
160 versus numerical data. Note that three methods for the local interpo‐
161 lation step are provided.
162 r.proj supports general datum transformations, making use of the PROJ.4
164 co-ordinate system translation library.
165
167 To avoid excessive time consumption when reprojecting a map the region
168 and resolution of the target location should be set appropriately
169 beforehand. A simple way to do this is to generate a vector "box" map
170 of the region in the source location using v.in.region. This "box" map
171 is then reprojected into the target location with v.proj. Next the
172 region in the target location is set to the extent of the new vector
173 map with g.region along with the desired raster resolution (g.region -m
174 can be used in Latitude/Longitude locations to measure the geodetic
175 length of a pixel). r.proj is then run for the raster map the user
176 wants to reproject. In this case a little preparation goes a long way.
177 When reprojecting whole-world maps the user should disable map-trimming
179 with the -n flag. Trimming is not useful here because the module has
180 the whole map in memory anyway. Besides that, world "edges" are hard
181 (or impossible) to find in projections other than latitude-longitude so
182 results may be odd with trimming.
183
185 [1] Evenden, G.I. (1990) Cartographic projection procedures for the
186 UNIX environment - a user's manual. USGS Open-File Report 90-284
187 (OF90-284.pdf) See also there: Interim Report and 2nd Interim Report on
188 Release 4, Evenden 1994).
189 Richards, John A. (1993), Remote Sensing Digital Image Analysis,
191 Springer-Verlag, Berlin, 2nd edition.
192 PROJ 4: Projection/datum support library.
194 Further reading
196 ASPRS Grids and Datum
198 MapRef - The Collection of Map Projections and Reference
200 Systems for Europe
201 Projections Transform List (PROJ4)
203
205 g.region, g.proj, g.setproj, i.rectify, r.support, r.stats, v.proj,
206 v.in.region
207 The 'gdalwarp' and 'gdal_translate' utilities are available from the
209 GDAL project.
210
212 Martin Schroeder, University of Heidelberg, Germany
213 Man page text from S.J.D. Cox, AGCRC, CSIRO Exploration & Mining, Ned‐
215 lands, WA
216 Updated by Morten Hulden
218 Datum tranformation support and cleanup by Paul Kelly
220 Last changed: $Date: 2006/05/02 14:09:18 $
222 Full index
224GRASS 6.2.2 r.proj(1)