v.vect.statsgrass - Online in the Cloud

PROGRAM:

NAME

v.vect.stats - Count points in areas, calculate statistics from point attributes.

KEYWORDS

vector, attribute table, database, univariate statistics, zonal statistics

SYNOPSIS

v.vect.stats
v.vect.stats --help
v.vect.stats [-p] points=name areas=name [type=string[,string,...]]
[points_layer=string] [areas_layer=string] [method=string] [points_column=name]
[count_column=string] [stats_column=string] [separator=character] [--help]
[--verbose] [--quiet] [--ui]

Flags:
-p
Print output to stdout, do not update attribute table
First column is always area category

--help
Print usage summary

--verbose
Verbose module output

--quiet
Quiet module output

--ui
Force launching GUI dialog

Parameters:
points=name [required]
Name of input vector map
Name of existing vector map with points

areas=name [required]
Name of input vector map
Name of existing vector map with areas

type=string[,string,...]
Feature type
Input feature type
Options: point, centroid
Default: point

points_layer=string
Layer number for points map
Vector features can have category values in different layers. This number determines
which layer to use. When used with direct OGR access this is the layer name.
Default: 1

areas_layer=string
Layer number for area map
Vector features can have category values in different layers. This number determines
which layer to use. When used with direct OGR access this is the layer name.
Default: 1

method=string
Method for aggregate statistics
Options: sum, average, median, mode, minimum, min_cat, maximum, max_cat, range,
stddev, variance, diversity

points_column=name
Column name of points map to use for statistics
Column of points map must be numeric

count_column=string
Column name to upload points count
Column to hold points count, must be of type integer, will be created if not existing

stats_column=string
Column name to upload statistics
Column to hold statistics, must be of type double, will be created if not existing

separator=character
Field separator
Special characters: pipe, comma, space, tab, newline
Default: pipe

DESCRIPTION

v.vect.stats counts the number of points in vector map points falling into each area in
vector map areas. Optionally statistics on point attributes in points are calculated for
each area. The results are either uploaded to the attribute table of the vector map areas
or printed to stdout.

Statistical Methods: Using numeric attribute values of all points falling into a given
area, a new value is detmined with the selected method. v.vect.stats can perform the
following operations:

sum
The sum of values.

average
The average value of all point attributes (sum / count).

median
The value found half-way through a list of the attribute values, when these are ranged
in numerical order.

mode
The most frequently occurring value.

minimum
The minimum observed value.

min_cat
The point category corresponding to the minimum observed value.

maximum
The maximum observed value.

max_cat
The point category corresponding to the maximum observed value.

range
The range of the observed values.

stddev
The statistical standard deviation of the attribute values.

variance
The statistical variance of the attribute values.

diversity
The number of different attribute values.

NOTES

Points not falling into any area are ignored. Areas without category (no centroid attached
or centroid without category) are ignored. If no points are falling into a given area,
the point count is set to 0 (zero) and the statistics result to "null".

The columns count_column and stats_column are created if not existing. If they do already
exist, the count_column must be of type integer and the stats_column of type double
precision.

EXAMPLES

Preparation for examples
The subsequent examples are based on randomly sampled elevation data (North Carolina
sample database):
# work on map copy for attribute editing
g.copy vector=zipcodes_wake,myzipcodes_wake
# set computational region: extent of ZIP code map, raster pixels
# aligned to raster map
g.region vector=myzipcodes_wake align=elev_state_500m -p
# generate random elevation points
r.random elev_state_500m vector=rand5000 n=5000
v.colors rand5000 color=elevation
# visualization
d.mon wx0
d.vect myzipcodes_wake -c
d.vect rand5000
These vector maps are used for the examples below.

Count points per polygon with printed output
See above for the creation of the input maps.

Counting points per polygon, print results to terminal:
v.vect.stats points=rand5000 area=myzipcodes_wake -p

Count points per polygon with column update
See above for the creation of the input maps.

Counting of points per polygon, with update of "num_points" column (will be automatically
created):
v.vect.stats points=rand5000 area=myzipcodes_wake count_column=num_points
# verify result
v.db.select myzipcodes_wake column=ZIPCODE_,ZIPNAME,num_points

Average values of points in polygon with printed output
See above for the creation of the input maps.

Calculation of average point elevation per ZIP code polygon, printed to terminal in comma
separated style:
# check name of point map column:
v.info -c rand5000
v.vect.stats points=rand5000 area=myzipcodes_wake \
method=average points_column=value separator=comma -p

Average values of points in polygon with column update
See above for the creation of the input maps.

Calculation of average point elevation per ZIP code polygon, with update of "avg_elev"
column and counting of points per polygon, with update of "num_points" column (new columns
will be automatically created):
# check name of point map column:
v.info -c rand5000
v.vect.stats points=rand5000 area=myzipcodes_wake count_column=num_points \
method=average points_column=value stats_column=avg_elev
# verify result
v.db.select myzipcodes_wake column=ZIPCODE_,ZIPNAME,avg_elev

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