1t.rast.to.rast3(1) GRASS GIS User's Manual t.rast.to.rast3(1)
2
6 t.rast.to.rast3 - Converts a space time raster dataset into a 3D
7 raster map.
8
10 temporal, conversion, raster, raster3d, voxel, time
11
13 t.rast.to.rast3
14 t.rast.to.rast3 --help
15 t.rast.to.rast3 input=name output=name [--overwrite] [--help]
16 [--verbose] [--quiet] [--ui]
17 Flags:
19 --overwrite
20 Allow output files to overwrite existing files
21 --help
23 Print usage summary
24 --verbose
26 Verbose module output
27 --quiet
29 Quiet module output
30 --ui
32 Force launching GUI dialog
33 Parameters:
35 input=name [required]
36 Name of the input space time raster dataset
37 output=name [required]
39 Name for output 3D raster map
40
42 t.rast.to.rast3 is designed to convert a space time raster dataset
43 (STRDS) into a space time voxel cube. A space time voxel cube is a 3
44 dimensional raster map layer (3D raster map or voxel map layer) that as
45 time as unit for the z-dimension.
46 A space time raster dataset that should be converted into a space time
48 voxel cube must have a valid temporal topology. Hence, overlapping or
49 inclusion of time stamps is not allowed. The granularity of the STRDS
50 is used to set the resolution of the 3D raster map layer and to sample
51 the registered time stamped raster map layers.
52 Gaps between raster map layer in the STRDS will be represented by NULL
54 values in the voxel map layer.
55
57 The reference time for all space time voxel cubes is
58 1900-01-0100:00:00. This allows the alignment space time voxel cubes
59 with different granularities.
60 Be aware that the granularity of a STRDS is used to sample time stamped
62 map layers! If you have gaps between monthly intervals that have the
63 size of a second, the monthly intervals will be sampled by a second
64 based granularity as well. This may result in millions of space time
65 voxel cube layers!
66 Management of open file limits
68 The maximum number of raster maps that can be processed is given by the
69 per-user limit of the operating system. For example, both the the hard
70 and soft limit for users is typically 1024. The soft limit can be
71 changed with e.g. ulimit -n 4096 (UNIX-based operating systems) but
72 not higher than the hard limit. If the latter is too low, you can as
73 superuser add an entry in
74 /etc/security/limits.conf
75 # <domain> <type> <item> <value>
76 your_username hard nofile 4096
77 This will raise the hard limit to 4096 files. Also have a look at the
78 overall limit of the operating system
79 cat /proc/sys/fs/file-max
80 which, on modern Linux systems, is several 100,000 files.
81
83 To create a voxel map layer from a subset of the tempmean_monthly space
84 time dataset, run:
85 # create the subset for 2012 data
86 t.rast.extract input=tempmean_monthly output=tempmean_monthly_later_2012 \
87 where="start_time >= ’2012-01-01’"
88 # set the right 3D region
89 g.region -p3 res3=500
90 # convert to 3D raster map
91 t.rast.to.rast3 input=tempmean_monthly_later_2012@climate_2009_2012 output=tempmean_monthly_2012
92 t.info type=raster_3d input=tempmean_monthly_2012
93 +-------------------- 3D Raster Dataset -------------------------------------+
94 | |
95 +-------------------- Basic information -------------------------------------+
96 | Id: ........................ tempmean_monthly_2012@climate_2009_2012
97 | Name: ...................... tempmean_monthly_2012
98 | Mapset: .................... climate_2009_2012
99 | Creator: ................... lucadelu
100 | Temporal type: ............. absolute
101 | Creation time: ............. 2014-11-28 11:10:51.679294
102 +-------------------- Absolute time -----------------------------------------+
103 | Start time:................. 2012-01-01 00:00:00
104 | End time:................... 2013-01-01 00:00:00
105 +-------------------- Spatial extent ----------------------------------------+
106 | North:...................... 320000.0
107 | South:...................... 10000.0
108 | East:.. .................... 935000.0
109 | West:....................... 120000.0
110 | Top:........................ 1357.0
111 | Bottom:..................... 1345.0
112 +-------------------- Metadata information ----------------------------------+
113 | Datatype:................... DCELL
114 | Number of columns:.......... 620
115 | Number of rows:............. 1630
116 | Number of cells:............ 12127200
117 | North-South resolution:..... 500.0
118 | East-west resolution:....... 500.0
119 | Minimum value:.............. -0.534994
120 | Maximum value:.............. 28.794653
121 | Number of depths:........... 12
122 | Top-Bottom resolution:...... 1.0
123 | Registered datasets ........
124 +----------------------------------------------------------------------------+
125 r3.info tempmean_monthly_2012
126 +----------------------------------------------------------------------------+
127 | Layer: tempmean_monthly_2012 Date: Fri Nov 28 11:10:50 2014 |
128 | Mapset: climate_2009_2012 Login of Creator: lucadelu |
129 | Location: nc_spm_temporal_workshop |
130 | DataBase: /grassdata |
131 | Title: Space time voxel cube |
132 | Units: none |
133 | Vertical unit: months |
134 | Timestamp: none |
135 |----------------------------------------------------------------------------|
136 | |
137 | Type of Map: 3d cell Number of Categories: 0 |
138 | Data Type: DCELL |
139 | Rows: 620 |
140 | Columns: 1630 |
141 | Depths: 12 |
142 | Total Cells: 12127200 |
143 | Total size: 28414287 Bytes |
144 | Number of tiles: 4230 |
145 | Mean tile size: 6717 Bytes |
146 | Tile size in memory: 23520 Bytes |
147 | Number of tiles in x, y and z: 47, 45, 2 |
148 | Dimension of a tile in x, y, z: 35, 14, 6 |
149 | |
150 | Projection: Lambert Conformal Conic (zone 0) |
151 | N: 320000 S: 10000 Res: 500 |
152 | E: 935000 W: 120000 Res: 500 |
153 | T: 1357 B: 1345 Res: 1 |
154 | Range of data: min = -0.53499434 max = 28.79465315 |
155 | |
156 | Data Source: |
157 | |
158 | |
159 | |
160 | Data Description: |
161 | This space time voxel cube was created with t.rast.to.rast3 |
162 | |
163 | Comments: |
164 | r.to.rast3 input="2012_01_tempmean@climate_2009_2012,2012_02_tempmea\ |
165 | n@climate_2009_2012,2012_03_tempmean@climate_2009_2012,2012_04_tempm\ |
166 | ean@climate_2009_2012,2012_05_tempmean@climate_2009_2012,2012_06_tem\ |
167 | pmean@climate_2009_2012,2012_07_tempmean@climate_2009_2012,2012_08_t\ |
168 | empmean@climate_2009_2012,2012_09_tempmean@climate_2009_2012,2012_10\ |
169 | _tempmean@climate_2009_2012,2012_11_tempmean@climate_2009_2012,2012_\ |
170 | 12_tempmean@climate_2009_2012" output="tempmean_monthly_2012" tilesi\ |
171 | ze=32 |
172 | |
173 +----------------------------------------------------------------------------+
174
176 r3.mapcalc, r3.info
177
179 Sören Gebbert, Thünen Institute of Climate-Smart Agriculture
180
182 Available at: t.rast.to.rast3 source code (history)
183 Accessed: Saturday Jan 21 21:17:05 2023
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188 © 2003-2023 GRASS Development Team, GRASS GIS 8.2.1 Reference Manual
190GRASS 8.2.1 t.rast.to.rast3(1)