t.vect.observe.strds - Observes specific locations
in a space time raster dataset over a period of time using vector
points.
temporal, sampling, vector, time
t.vect.observe.strds
t.vect.observe.strds --help
t.vect.observe.strds input=name
strds=name[,name,...] output=name
vector_output=name
columns=string[,string,...]
[where=sql_query] [--overwrite] [--help]
[--verbose] [--quiet] [--ui]
The module t.vect.observe.strds is used to observe specific
locations in a space time raster dataset over a period of time using vector
points. The first input is a vector map layer with vector points. The second
input is one or several space time raster datasets (STRDS) that should be
sampled over time at the vector point positions. The space time raster
dataset will be sampled over its whole temporal extent (from start to end).
A column name must be specified for each input space time raster
dataset.
The result is a new space time vector dataset that contains a
single (new) vector map which links to as many time-stamped attribute tables
as raster map layers are present in the input space time raster dataset.
Hence, for each time step in the space time raster dataset a new attribute
table is created. The GRASS GIS Temporal Framework allows to time stamp
attribute tables that can be linked to a single vector map layer.
The module v.what.rast is used internally for sampling the
time stamped raster map layers. All sampled values of a single time stamped
raster map layer are written into a new time stamped attribute table.
Use t.vect.db.select to print attribute values of the space
time vector dataset to stdout.
The example shows how to create a space time vector dataset and a
vector layer starting from a point vector and a space time raster dataset:
t.vect.observe.strds input=precip_30ynormals_3d strds=tempmean_monthly \
output=precip_stations vect=precip_stations_monthly \
columns=month
t.info precip_stations type=stvds
+-------------------- Space Time Vector Dataset -----------------------------+
| |
+-------------------- Basic information -------------------------------------+
| Id: ........................ precip_stations@climate_2009_2012
| Name: ...................... precip_stations
| Mapset: .................... climate_2009_2012
| Creator: ................... lucadelu
| Temporal type: ............. absolute
| Creation time: ............. 2014-12-02 00:42:39.187615
| Modification time:.......... 2014-12-02 00:42:55.215169
| Semantic type:.............. mean
+-------------------- Absolute time -----------------------------------------+
| Start time:................. 2009-01-01 00:00:00
| End time:................... 2013-01-01 00:00:00
| Granularity:................ 1 month
| Temporal type of maps:...... interval
+-------------------- Spatial extent ----------------------------------------+
| North:...................... 306221.830194
| South:...................... 27606.895351
| East:.. .................... 917004.829165
| West:....................... 151768.568246
| Top:........................ 1615.44
| Bottom:..................... 2.4384
+-------------------- Metadata information ----------------------------------+
| Vector register table:...... vector_map_register_be074525097c4088997c9a1979f17065
| Number of points ........... 6664
| Number of lines ............ 0
| Number of boundaries ....... 0
| Number of centroids ........ 0
| Number of faces ............ 0
| Number of kernels .......... 0
| Number of primitives ....... 6664
| Number of nodes ............ 0
| Number of areas ............ 0
| Number of islands .......... 0
| Number of holes ............ 0
| Number of volumes .......... 0
| Number of registered maps:.. 49
|
| Title:
| Observaion of space time raster dataset(s) tempmean_monthly
| Description:
| Observation of space time raster dataset(s) tempmean_monthly with vector map precip_30ynormals_3d
| Command history:
| # 2014-12-02 00:42:39
| t.vect.observe.strds input="precip_30ynormals_3d"
| strds="tempmean_monthly" output="precip_stations"
| vect="precip_stations_monthly" columns="month"
|
+----------------------------------------------------------------------------+
v.info precip_stations_monthly
+----------------------------------------------------------------------------+
| Name: precip_stations_monthly |
| Mapset: climate_2009_2012 |
| Project: nc_spm_temporal_workshop |
| Database: /grassdata |
| Title: North Carolina 30 year precipitation normals (3D) |
| Map scale: 1:1 |
| Name of creator: neteler |
| Organization: |
| Source date: Wed May 9 14:32:39 2007 |
| Timestamp (first layer): none |
|----------------------------------------------------------------------------|
| Map format: native |
|----------------------------------------------------------------------------|
| Type of map: vector (level: 2) |
| |
| Number of points: 136 Number of centroids: 0 |
| Number of lines: 0 Number of boundaries: 0 |
| Number of areas: 0 Number of islands: 0 |
| Number of faces: 0 Number of kernels: 0 |
| Number of volumes: 0 Number of holes: 0 |
| |
| Map is 3D: Yes |
| Number of dblinks: 49 |
| |
| Projection: Lambert Conformal Conic |
| |
| N: 306221.830194 S: 27606.895351 |
| E: 917004.829165 W: 151768.568246 |
| B: 2.4384 T: 1615.44 |
| |
| Digitization threshold: 0 |
| Comment: |
| |
+----------------------------------------------------------------------------+
t.create, t.info, t.vect.db.select,
t.vect.what.strds
Sören Gebbert, Thünen Institute of Climate-Smart
Agriculture
Available at: t.vect.observe.strds source code (history)
Latest change: Tuesday Dec 17 20:17:20 2024 in commit:
d962e90c026708a4815ea2b9f46c0e84c17de22d
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