t.rast.univar(1)

📦
version 8.4.2 · 8 versions
, in fedora 44

💖 t.rast.univar — the manual, but make it make sense 💖

okay bestie, gather round, because t.rast.univar is about to become your new obsession. it's a GRASS GIS module that calculates univariate statistics from the non-null cells for each registered raster map of a space time raster dataset. that's the whole vibe. periodt. ✨

KEYWORDS: temporal, statistics, raster, time, parallel 🌈

✨ SYNOPSIS ✨

t.rast.univar
t.rast.univar --help
t.rast.univar [-eru] input=name  [zones=name]   [nprocs=integer]
[output=name]   [percentile=float[,float,...]]   [where=sql_query]
[region_relation=string]   [separator=character]   [--overwrite]
[--help]  [--verbose]  [--quiet]  [--ui]

🎀 Flags

  • -e — Calculate extended statistics. the little upgrade that changes everything 💅
  • -r — Use the raster map regions for univar statistical calculation instead of the current region
  • -u — Suppress printing of column names. no headers, no small talk 🫶
  • --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 the input space time raster dataset. yes queen, this one's mandatory, no skipping 💖
  • zones=name — Raster map used for zoning, must be of type CELL
  • nprocs=integer — Number of threads for parallel computing. Default: 1
  • output=name — Name for output file
  • percentile=float[,float,...] — Percentile to calculate (requires extended statistics flag). Options: 0-100
  • 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'
  • region_relation=string — Process only maps with this spatial relation to the current computational region. Options: overlaps, contains, is_contained
  • separator=character — Field separator character between the output columns. Special characters: pipe, comma, space, tab, newline. Default: pipe

✨ DESCRIPTION ✨

so, t.rast.univar calculates univariate statistics from the non-null cells for each registered raster map of a space time raster dataset. that's the mission statement, and it ate. 🔥

By default it returns the name of the map, the semantic label of the map, the start and end date of the map and the following values: mean, minimum and maximum vale, mean_of_abs, standard deviation, variance, coeff_var, number of null cells, total number of cells. (yes, "vale" — that's what the original says, i'm not gonna gaslight you about it 😭)

Using the e flag it can calculate also extended statistics: first quartile, median value, third quartile and percentile 90. lowkey iconic behavior tbh.

If a zones raster map is provided, statistics are computed for each zone (category) in that input raster map. The zones option does not support space time raster datasets (STRDS) but only a single, static raster map. > heads up bestie: single static raster only, don't try to slide a STRDS in there, it will not work 💀

Space time raster datasets may contain raster maps with varying spatial extent like for example series of scenes of satellite images. With the region_relation option, computations can be limited to maps of the space time raster dataset that have a given spatial relation to the current computational region. Supported spatial relations are:

  • "overlaps": process only maps that spatially overlap ("intersect") with the current computational region
  • "is_contained": process only maps that are fully within the current computational region
  • "contains": process only maps that contain (fully cover) the current computational region

🌈 EXAMPLE 🌈

Obtain the univariate statistics for the raster space time dataset "tempmean_monthly" (precision reduced to 2 decimals in this example):

t.rast.univar -e tempmean_monthly
id|start|end|mean|min|max|mean_of_abs|stddev|variance|coeff_var|sum|null_cells|cells|first_quartile|median|third_quartile|percentile_90
2009_01_tempmean@climate_2009_2012|2009-01-01 00:00:00|2009-02-01 00:00:00|3.90|-3.38|7.43|3.95|1.79|3.20|45.91|1977967.31|503233|1010600|2.80|3.92|5.21|6.23
2009_02_tempmean@climate_2009_2012|2009-02-01 00:00:00|2009-03-01 00:00:00|5.91|-1.82|8.01|5.92|1.63|2.65|27.53|2999555.60|503233|1010600|5.44|6.26|7.07|7.48
...
2012_11_tempmean@climate_2009_2012|2012-11-01 00:00:00|2012-12-01 00:00:00|8.03|1.79|10.91|8.03|1.32|1.73|16.41|4072472.77|503233|1010600|7.49|8.13|8.96|9.48
2012_12_tempmean@climate_2009_2012|2012-12-01 00:00:00|2013-01-01 00:00:00|8.71|1.76|11.98|8.71|1.72|2.95|19.74|4418403.77|503233|1010600|7.84|8.95|9.99|10.67

look at all those columns go 😍

🦋 SEE ALSO 🦋

t.create, t.info t.create,

👑 AUTHOR 👑

  • Sören Gebbert, Thünen Institute of Climate-Smart Agriculture
  • Stefan Blumentrath (support for zones, parallel processing, and spatial relations)

💜 SOURCE CODE 💜

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

Accessed: Saturday Jan 17 05:41:53 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

and that's the whole page bestie 💖 this was GRASS 8.4.2, manual for t.rast.univar (1), accessed Saturday Jan 17 05:41:53 2026, © 2003-2025 GRASS Development Team 🎀

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