1t.vect.observe.strds(1) Grass User's Manual t.vect.observe.strds(1)
2
6 t.vect.observe.strds - Observes specific locations in a space time
7 raster dataset over a period of time using vector points.
8
10 temporal, sampling, vector, time
11
13 t.vect.observe.strds
14 t.vect.observe.strds --help
15 t.vect.observe.strds input=name strds=name[,name,...] output=name vec‐
16 tor_output=name columns=string[,string,...] [where=sql_query]
17 [--overwrite] [--help] [--verbose] [--quiet] [--ui]
18 Flags:
20 --overwrite
21 Allow output files to overwrite existing files
22 --help
24 Print usage summary
25 --verbose
27 Verbose module output
28 --quiet
30 Quiet module output
31 --ui
33 Force launching GUI dialog
34 Parameters:
36 input=name [required]
37 Name of input vector map
38 Or data source for direct OGR access
39 strds=name[,name,...]Â [required]
41 Name of the input space time raster datasets
42 output=name [required]
44 Name of the output space time vector dataset
45 vector_output=name [required]
47 Name of the new created vector map that stores the sampled values
48 in different layers
49 columns=string[,string,...]Â [required]
51 Names of the vector columns to be created and to store sampled
52 raster values, one name for each STRDS
53 where=sql_query
55 WHERE conditions of SQL statement without ’where’ keyword
56 Example: income < 1000 and population >= 10000
57
59 The module t.vect.observe.strds is used to observe specific locations
60 in a space time raster dataset over a period of time using vector
61 points. The first input is a vector map layer with vector points. The
62 second input is one or several space time raster datasets (STRDS) that
63 should be sampled over time at the vector point positions. The space
64 time raster dataset will be sampled over its whole temporal extent
65 (from start to end). A column name must be specified for each input
66 space time raster dataset.
67 The result is a new space time vector dataset that contains a single
69 (new) vector map which links to as many time-stamped attribute tables
70 as raster map layers are present in the input space time raster
71 dataset. Hence, for each time step in the space time raster dataset a
72 new attribute table is created. The GRASS GIS Temporal Framework allows
73 to time stamp attribute tables that can be linked to a single vector
74 map layer.
75 The module v.what.rast is used internally for sampling the time stamped
77 raster map layers. All sampled values of a single time stamped raster
78 map layer are written into a new time stamped attribute table.
79 Use t.vect.db.select to print attribute values of the space time vector
81 dataset to stdout.
82
84 The example shows how to create a space time vector dataset and a vec‐
85 tor layer starting from a point vector and a space time raster dataset:
86 t.vect.observe.strds input=precip_30ynormals_3d strds=tempmean_monthly \
87 output=precip_stations vect=precip_stations_monthly \
88 columns=month
89 t.info precip_stations type=stvds
90 +-------------------- Space Time Vector Dataset -----------------------------+
91 | |
92 +-------------------- Basic information -------------------------------------+
93 | Id: ........................ precip_stations@climate_2009_2012
94 | Name: ...................... precip_stations
95 | Mapset: .................... climate_2009_2012
96 | Creator: ................... lucadelu
97 | Temporal type: ............. absolute
98 | Creation time: ............. 2014-12-02 00:42:39.187615
99 | Modification time:.......... 2014-12-02 00:42:55.215169
100 | Semantic type:.............. mean
101 +-------------------- Absolute time -----------------------------------------+
102 | Start time:................. 2009-01-01 00:00:00
103 | End time:................... 2013-01-01 00:00:00
104 | Granularity:................ 1 month
105 | Temporal type of maps:...... interval
106 +-------------------- Spatial extent ----------------------------------------+
107 | North:...................... 306221.830194
108 | South:...................... 27606.895351
109 | East:.. .................... 917004.829165
110 | West:....................... 151768.568246
111 | Top:........................ 1615.44
112 | Bottom:..................... 2.4384
113 +-------------------- Metadata information ----------------------------------+
114 | Vector register table:...... vector_map_register_be074525097c4088997c9a1979f17065
115 | Number of points ........... 6664
116 | Number of lines ............ 0
117 | Number of boundaries ....... 0
118 | Number of centroids ........ 0
119 | Number of faces ............ 0
120 | Number of kernels .......... 0
121 | Number of primitives ....... 6664
122 | Number of nodes ............ 0
123 | Number of areas ............ 0
124 | Number of islands .......... 0
125 | Number of holes ............ 0
126 | Number of volumes .......... 0
127 | Number of registered maps:.. 49
128 |
129 | Title:
130 | Observaion of space time raster dataset(s) tempmean_monthly
131 | Description:
132 | Observation of space time raster dataset(s) tempmean_monthly with vector map precip_30ynormals_3d
133 | Command history:
134 | # 2014-12-02 00:42:39
135 | t.vect.observe.strds input="precip_30ynormals_3d"
136 | strds="tempmean_monthly" output="precip_stations"
137 | vect="precip_stations_monthly" columns="month"
138 |
139 +----------------------------------------------------------------------------+
140 v.info precip_stations_monthly
141 +----------------------------------------------------------------------------+
142 | Name: precip_stations_monthly |
143 | Mapset: climate_2009_2012 |
144 | Location: nc_spm_temporal_workshop |
145 | Database: /grassdata |
146 | Title: North Carolina 30 year precipitation normals (3D) |
147 | Map scale: 1:1 |
148 | Name of creator: neteler |
149 | Organization: |
150 | Source date: Wed May 9 14:32:39 2007 |
151 | Timestamp (first layer): none |
152 |----------------------------------------------------------------------------|
153 | Map format: native |
154 |----------------------------------------------------------------------------|
155 | Type of map: vector (level: 2) |
156 | |
157 | Number of points: 136 Number of centroids: 0 |
158 | Number of lines: 0 Number of boundaries: 0 |
159 | Number of areas: 0 Number of islands: 0 |
160 | Number of faces: 0 Number of kernels: 0 |
161 | Number of volumes: 0 Number of holes: 0 |
162 | |
163 | Map is 3D: Yes |
164 | Number of dblinks: 49 |
165 | |
166 | Projection: Lambert Conformal Conic |
167 | |
168 | N: 306221.830194 S: 27606.895351 |
169 | E: 917004.829165 W: 151768.568246 |
170 | B: 2.4384 T: 1615.44 |
171 | |
172 | Digitization threshold: 0 |
173 | Comment: |
174 | |
175 +----------------------------------------------------------------------------+
176
178 t.create, t.info, t.vect.db.select, t.vect.what.strds
179
181 Sören Gebbert, Thünen Institute of Climate-Smart Agriculture
182
184 Available at: t.vect.observe.strds source code (history)
185 Main index | Temporal index | Topics index | Keywords index | Graphical
187 index | Full index
188 © 2003-2019 GRASS Development Team, GRASS GIS 7.8.2 Reference Manual
190GRASS 7.8.2 t.vect.observe.strds(1)