t.vect.observe.strds(1)

NAME
t.vect.observe.strds.py - Observes specific locations in a space time raster dataset over a period of time using vector points.

KEYWORDS
temporal, sampling, vector, time

SYNOPSIS
t.vect.observe.strds.py
t.vect.observe.strds.py --help
t.vect.observe.strds.py input=name strds=name[,name,...] output=name vector_output=name columns=string[,string,...] [where=sql_query] [--overwrite] [--help] [--verbose] [--quiet] [--ui]

  Flags:

--overwrite
    Allow output files to overwrite existing files

--help
    Print usage summary

--verbose
    Verbose module output

--quiet
    Quiet module output

--ui
    Force launching GUI dialog

  Parameters:

input=name [required]
    Name of input vector map
    Or data source for direct OGR access

strds=name[,name,...] [required]
    Name of the input space time raster datasets

output=name [required]
    Name of the output space time vector dataset

vector_output=name [required]
    Name of the new created vector map that stores the sampled values in different layers

columns=string[,string,...] [required]
    Names of the vector columns to be created and to store sampled raster values, one name for each STRDS

where=sql_query
    WHERE conditions of SQL statement without ’where’ keyword
    Example: income < 1000 and population >= 10000

DESCRIPTION
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.

EXAMPLE
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                                         |
 | Location:        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:                                                                 |
 |                                                                            |
 +----------------------------------------------------------------------------+

SEE ALSO
t.create, t.info, t.vect.db.select, t.vect.what.strds

AUTHOR
Sören Gebbert, Thünen Institute of Climate-Smart Agriculture

SOURCE CODE

Available at: t.vect.observe.strds source code (history)

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