# v.qcount.1grass - Man Page

Indices for quadrat counts of vector point lists.

## Keywords

vector, statistics, point pattern

## Synopsis

`v.qcountv.qcount --helpv.qcount [-g] input=name  [layer=string]   [output=name]  nquadrats=integer radius=float  [--overwrite]  [--help]  [--verbose]  [--quiet]  [--ui]`

### Flags

-g

Print results in shell script style

--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=nameÂ [required]

Name of input vector map
Or data source for direct OGR access

layer=string

Layer number or name (’-1’ for all layers)
A single vector map can be connected to multiple database tables. This number determines which table to use. When used with direct OGR access this is the layer name.
Default: -1

output=name

Name for output quadrat centers map (number of points is written as category)

nquadrats=integerÂ [required]

Number of quadrats

radius=floatÂ [required]

Quadrat radius

## Description

v.qcount computes six different quadrat count statistics that provide a measure of how much an user defined point pattern departs from a complete spatial random point pattern.

Points are distributed following a complete spatial randomness (CSR) pattern if events are equally likely to occur anywhere within an area. There are two types departure from a CSR: regularity and clustering. Figure 1 gives an example of a complete random, regular and a clustered pattern.
Figure 1: Realization of two-dimensional Poisson processes of 50 points on the unit square exhibiting (a) complete spatial randomness, (b) regularity, and (c) clustering.

Various indices and statistics measure departure from CSR. The v.qcount function implements six different quadrat count indices that are described in Cressie (1991; p. 590-591) and in Ripley (1981; p. 102-106) and summarized in Table 1.
Table 1: Indices for Quadrat Count Data. Adapted from Cressie , this table shows the statistics computed for the quadrats in Figure 2.

These indices are computed as follows: v.qcount chooses nquadrads circular quadrats of radius radius such that they are completely within the bounds of the current region and no two quadrats overlap. The number of points falling within each quadrat are counted and indices are calculated to estimate the departure of point locations from complete spatial randomness. This is illustrated in Figure 2.
Figure 2: Randomly placed quadrats (n = 100) with 584 sample points.

The number of points is written as category to the output map (and not to an attribute table).

## See Also

v.random, v.distance, v.neighbors, v.perturb

## Known Issues

Timestamp not working for header part of counts output. (2000-10-28)

## Authors

James Darrell McCauley
when he was at: Agricultural Engineering Purdue University

Modified for GRASS 5.0 by Eric G. Miller (2000-10-28)
Modified for GRASS 5.7 by R. Blazek (2004-10-14)

## Source Code

Available at: v.qcount source code (history)

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Â© 2003-2020 GRASS Development Team, GRASS GIS 7.8.5 Reference Manual

## Info

GRASS 7.8.5 GRASS GIS User's Manual