1v.qcount(1) GRASS GIS User's Manual v.qcount(1)
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6 v.qcount - Indices for quadrat counts of vector point lists.
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9 vector, statistics, point pattern
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12 v.qcount
13 v.qcount --help
14 v.qcount [-g] input=name [layer=string] [output=name] nquadrats=in‐
15 teger radius=float [--overwrite] [--help] [--verbose] [--quiet]
16 [--ui]
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18 Flags:
19 -g
20 Print results in shell script style
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22 --overwrite
23 Allow output files to overwrite existing files
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25 --help
26 Print usage summary
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28 --verbose
29 Verbose module output
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31 --quiet
32 Quiet module output
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34 --ui
35 Force launching GUI dialog
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37 Parameters:
38 input=name [required]
39 Name of input vector map
40 Or data source for direct OGR access
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42 layer=string
43 Layer number or name (’-1’ for all layers)
44 A single vector map can be connected to multiple database tables.
45 This number determines which table to use. When used with direct
46 OGR access this is the layer name.
47 Default: -1
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49 output=name
50 Name for output quadrat centers map (number of points is written as
51 category)
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53 nquadrats=integer [required]
54 Number of quadrats
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56 radius=float [required]
57 Quadrat radius
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60 v.qcount computes six different quadrat count statistics that provide a
61 measure of how much an user defined point pattern departs from a com‐
62 plete spatial random point pattern.
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64 Points are distributed following a complete spatial randomness (CSR)
65 pattern if events are equally likely to occur anywhere within an area.
66 There are two types departure from a CSR: regularity and clustering.
67 Figure 1 gives an example of a complete random, regular and a clustered
68 pattern.
69 Figure 1: Realization of two-dimensional Poisson processes of 50 points
70 on the unit square exhibiting (a) complete spatial randomness, (b) reg‐
71 ularity, and (c) clustering.
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73 Various indices and statistics measure departure from CSR. The v.qcount
74 function implements six different quadrat count indices that are de‐
75 scribed in Cressie (1991; p. 590-591)[1] and in Ripley (1981; p.
76 102-106)[2] and summarized in Table 1.
77 Table 1: Indices for Quadrat Count Data. Adapted from Cressie [1], this
78 table shows the statistics computed for the quadrats in Figure 2.
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80 These indices are computed as follows: v.qcount chooses nquadrads cir‐
81 cular quadrats of radius radius such that they are completely within
82 the bounds of the current region and no two quadrats overlap. The num‐
83 ber of points falling within each quadrat are counted and indices are
84 calculated to estimate the departure of point locations from complete
85 spatial randomness. This is illustrated in Figure 2.
86 Figure 2: Randomly placed quadrats (n = 100) with 584 sample points.
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88 The number of points is written as category to the output map (and not
89 to an attribute table).
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92 This program may not work properly with lat-long data. It uses hypot()
93 in two files: count.c and findquads.c.
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96 Timestamp not working for header part of counts output. (2000-10-28)
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99 General references include:
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101 [1] Noel A. C. Cressie. Statistics for Spatial Data. Wiley Series in
102 Probability and Mathematical Statistics. John Wiley & Sons, New York,
103 NY, 1st edition, 1991.
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105 [2] Brian D. Ripley. Spatial Statistics. John Wiley \& Sons, New York,
106 NY, 1981.
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108 References to the indices include:
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110 [3] R. A. Fisher, H. G. Thornton, and W. A. Mackenzie. The accuracy of
111 the plating method of estimating the density of bacterial populations.
112 Annals of Applied Biology, 9:325-359, 1922.
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114 [4] F. N. David and P. G. Moore. Notes on contagious distributions in
115 plant populations. Annals of Botany, 18:47-53, 1954.
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117 [5] J. B. Douglas. Clustering and aggregation. Sankhya B, 37:398-417,
118 1975.
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120 [6] M. Lloyd. Mean crowding. Journal of Animal Ecology, 36:1-30, 1967.
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122 [7] M. Morista. Measuring the dispersion and analysis of distribution
123 patterns. Memoires of the Faculty of Science, Kyushu University, Series
124 E. Biology, 2:215-235, 1959.
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126 A more detailed background is given in the tutorial:
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128 [8] James Darrell McCauley 1993. Complete Spatial Randomness and
129 Quadrat Methods - GRASS Tutorial on v.qcount
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132 v.random, v.distance, v.neighbors, v.perturb
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135 James Darrell McCauley
136 when he was at: Agricultural Engineering Purdue University
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138 Modified for GRASS 5.0 by Eric G. Miller (2000-10-28)
139 Modified for GRASS 5.7 by R. Blazek (2004-10-14)
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142 Available at: v.qcount source code (history)
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144 Accessed: Saturday Jan 21 20:40:12 2023
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146 Main index | Vector index | Topics index | Keywords index | Graphical
147 index | Full index
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149 © 2003-2023 GRASS Development Team, GRASS GIS 8.2.1 Reference Manual
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153GRASS 8.2.1 v.qcount(1)