t.rast.what(1)

📦
version 8.4.2 · 8 versions
, in fedora 44

t.rast.what(1) 💖

okay bestie, welcome to the GRASS GIS User's Manual page for t.rast.what — and no, that is not a typo, that is the whole vibe. sit down, grab a strawberry 🍓, and let's get into it.

✨ NAME ✨

t.rast.what — sample a space time raster dataset at specific vector point coordinates and write the output to stdout using different layouts 🫶

🎀 KEYWORDS 🎀

temporal, sampling, raster, time

🌸 SYNOPSIS 🌸

t.rast.what
t.rast.what --help
t.rast.what [-niv]  [points=name]   [coordinates=east,north]  strds=name
[output=name]   [where=sql_query]   [null_value=string]
[separator=character]   [order=string[,string,...]]   [layout=string]
[nprocs=integer]   [--overwrite]  [--help]  [--verbose]  [--quiet]
[--ui]

🌈 Flags

  • -n — output header row (the little name tag row, she's giving organized 💅)
  • -i — use stdin as input and ignore the coordinates and points options
  • -v — show the category for the vector points map
  • --overwrite — allow output files to overwrite existing files (yes, she will delete your old file, no cap 💀)
  • --help — print usage summary
  • --verbose — verbose module output
  • --quiet — quiet module output
  • --ui — force launching GUI dialog

🦋 Parameters

  • points=name — name of input vector map
    • or data source for direct OGR access
  • coordinates=east,north — comma separated list of coordinates
  • strds=name [required] — name of the input space time raster dataset (this one is mandatory, bestie, she will not move without it 👑)
  • output=name — name for the output file or - in case stdout should be used
    • Default: -
  • where=sql_query — WHERE conditions of SQL statement without 'where' keyword used in the temporal GIS framework
    • Example: start_time > '2001-01-01 12:30:00'
  • null_value=string — string representing NULL value
  • separator=character — field separator
    • Special characters: pipe, comma, space, tab, newline
    • Default: pipe
  • order=string[,string,...] — sort the maps by category
    • Options: id, name, creator, mapset, creation_time, modification_time, start_time, end_time, north, south, west, east, min, max
    • Default: start_time
  • layout=string — the layout of the output. One point per row (row), one point per column (col), all timsteps in one row (timerow)
    • Options: row, col, timerow
    • Default: row
  • nprocs=integer — number of r.what processes to run in parallel
    • Default: 1

💜 DESCRIPTION 💜

t.rast.what is literally designed to sample space time raster datasets at specific point coordinates using r.what internally. the output of r.what gets transformed into different output layouts, and you get to pick which one using the layout option. main character energy, honestly ✨

Three layouts can be specified:

  • row — Row order, one vector sample point value per row
  • col — Column order, create a column for each vector sample point of a single time step/raster layer
  • timerow — Time order, create a column for each time step, this order is the original r.what output, except that the column names are the timestamps

please have a look at the example to see the supported layouts. i promise it's giving gorgeous 🎀

This module is designed to run several instances of r.what to sample subsets of a space time raster dataset in parallel. Several intermediate text files will be created that are merged into a single file at the end of the processing. (yes, she's doing all that behind the scenes and not even bragging about it 🌸)

Coordinates can be provided as vector map using the points option or as comma separated coordinate list with the coordinates option.

An output file can be specified using the output option. Stdout will be used if no output is specified or if the output option is set to -.

⭐ EXAMPLES ⭐

🌈 Data preparation

In the following examples we sample a space time raster dataset that contains 4 raster map layers. First we create the STRDS that will be sampled with t.rast.what.

g.region s=0 n=80 w=0 e=120 b=0 t=50 res=10
# Generate data
r.mapcalc expression="a_1 = 1" -s
r.mapcalc expression="a_2 = 2" -s
r.mapcalc expression="a_3 = 3" -s
r.mapcalc expression="a_4 = 4" -s
t.create type=strds output=A title="A test" descr="A test"
t.register -i type=raster input=A maps=a_1,a_2,a_3,a_4 \
    start='1990-01-01' increment="1 month"

🧚 Example 1

The first approach uses text coordinates as input and stdout as output, the layout is one coordinate(point per column:

t.rast.what strds=A coordinates="115,36,79,45" layout=col -n
start|end|115.0000000000;36.0000000000|79.0000000000;45.0000000000
1990-01-01 00:00:00|1990-02-01 00:00:00|1|1
1990-02-01 00:00:00|1990-03-01 00:00:00|2|2
1990-03-01 00:00:00|1990-04-01 00:00:00|3|3
1990-04-01 00:00:00|1990-05-01 00:00:00|4|4

🦋 Example 2

A vector map layer can be used as input to sample the STRDS. All three available layouts are demonstrated using the vector map for sampling.

# First create the vector map layer based on random points
v.random output=points n=3 seed=1
# Row layout using a text file as output
t.rast.what strds=A points=points output=result.txt layout=row -n
cat result.txt
115.0043586274|36.3593955783|1990-01-01 00:00:00|1990-02-01 00:00:00|1
115.0043586274|36.3593955783|1990-02-01 00:00:00|1990-03-01 00:00:00|2
115.0043586274|36.3593955783|1990-03-01 00:00:00|1990-04-01 00:00:00|3
115.0043586274|36.3593955783|1990-04-01 00:00:00|1990-05-01 00:00:00|4
79.6816763826|45.2391522853|1990-01-01 00:00:00|1990-02-01 00:00:00|1
79.6816763826|45.2391522853|1990-02-01 00:00:00|1990-03-01 00:00:00|2
79.6816763826|45.2391522853|1990-03-01 00:00:00|1990-04-01 00:00:00|3
79.6816763826|45.2391522853|1990-04-01 00:00:00|1990-05-01 00:00:00|4
97.4892579600|79.2347263950|1990-01-01 00:00:00|1990-02-01 00:00:00|1
97.4892579600|79.2347263950|1990-02-01 00:00:00|1990-03-01 00:00:00|2
97.4892579600|79.2347263950|1990-03-01 00:00:00|1990-04-01 00:00:00|3
97.4892579600|79.2347263950|1990-04-01 00:00:00|1990-05-01 00:00:00|4
# Column layout order using stdout as output
t.rast.what strds=A points=points layout=col -n
start|end|115.0043586274;36.3593955783|79.6816763826;45.2391522853|97.4892579600;79.2347263950
1990-01-01 00:00:00|1990-02-01 00:00:00|1|1|1
1990-02-01 00:00:00|1990-03-01 00:00:00|2|2|2
1990-03-01 00:00:00|1990-04-01 00:00:00|3|3|3
1990-04-01 00:00:00|1990-05-01 00:00:00|4|4|4
# Timerow layout, one time series per row
# using the where statement to select a subset of the STRDS
# and stdout as output
t.rast.what strds=A points=points \
    where="start_time >= '1990-03-01'" layout=timerow -n
x|y|1990-03-01 00:00:00;1990-04-01 00:00:00|1990-04-01 00:00:00;1990-05-01 00:00:00
115.004358627375|36.3593955782903|3|4
79.681676382576|45.2391522852909|3|4
97.4892579600048|79.2347263950131|3|4

👑 SEE ALSO 👑

g.region, r.mask r.neighbors, r.what, t.info, t.rast.aggregate.ds, t.rast.extract, v.what.strds

💅 AUTHOR 💅

Sören Gebbert, Thünen Institute of Climate-Smart Agriculture

🌟 SOURCE CODE 🌟

Available at: t.rast.what source code (history)

Accessed: Saturday Jan 17 05:41:54 2026

Main index | Temporal index | Topics index | Keywords index | Graphical index | Full index

© 2003-2025 GRASS Development Team, GRASS GIS 8.4.2 Reference Manual

okay that's the whole page, bestie, you ate that 🫶 this was GRASS 8.4.2, t.rast.what(1), and i'm obsessed with you for reading the whole thing 💖✨🎀 bye mwah 💋

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