## DESCRIPTION

r.volume is a tool for summing cell values within clumps and calculating volumes and centroids of patches or clumps.

r.volume generates a table containing the sum of all cells from a input raster map sorted by category on a clump raster map, and optionally generates a vector points map of the centroids for each clump. If a clump map is not specified, the current raster mask is used. The raster mask can be defined by r.mask. The sum is multiplied by the area of a cell to give the volume occupied by that cell. See below for an example of the output table.

## NOTES

If a clump map is not given and a raster mask is not set, the program exits with an error message.

r.volume works in the current region and respects the current raster mask.

### CENTROIDS

The centroid coordinates are the same as those stored in the vector map (if one was requested by centroids parameter). They are guaranteed to fall on a cell of the appropriate category, thus they are not always the true, mathematical centroid. They will always fall at a cell center.

Attribute table linked to the vector map with centroids contains several columns:

- `cat` - category value (integer)
- `volume` - volume value (double precision)
- `average` - average value in the clump (double precision)
- `sum` - sum of cell values in the clump (double precision)
- `count` - number of cells with the category (integer)

Vector points can be converted directly to a raster map with each point a separate category using v.to.rast.

### APPLICATIONS

By preprocessing the elevation raster map with r.mapcalc and using suitable masking or clump maps, very interesting applications can be done with r.volume. Such as, calculating the volume of rock in a potential quarry; calculating cut/fill volumes for roads; finding water volumes in potential reservoirs.

## EXAMPLE

### Computation of a water basin volume

The example is based on the North Carolina sample dataset:

    # set computational region to small basin within extent of LiDAR elevation model
    g.region n=220361 s=220123 w=638527 e=638894 align=elev_lid792_1m -p
    # generate shared relief map for better terrain visualization
    r.relief input=elev_lid792_1m output=elev_lid792_1m_shaded
    d.shade shade=elev_lid792_1m_shaded color=elev_lid792_1m

    # query terrain height at a position within the basin
    r.what map=elev_lid792_1m coordinates=638684.0,220210.0
    # 638684.0|220210.0||112.2362

    # fill the basin with water, approx 1.5m above terrain
    r.lake elevation=elev_lid792_1m water_level=113.7 lake=mylake coordinates=638684.0,220210.0
    #  Lake depth from 0.000000 to 1.622047 (specified water level is taken as zero)
    #  Lake area 764.000000 square meters
    #  Lake volume 648.875328 cubic meters

    # compute water volume
    r.volume input=elev_lid792_1m clump=mylake
    #
    # Category   Average   Data   # Cells        Centroid             Total
    # Number     in clump  Total  in clump   Easting     Northing     Volume
    # -----------------------------------------------------------------------------
    #        1    112.66     54188     481   638683.50   220210.50         54188.35
    #        2    112.14      6504      58   638679.50   220215.50          6504.14
    # -----------------------------------------------------------------------------
    #                                                 Total Volume =       60692.49

Figure: Water filled based shown on shaded elevation map

### Report of geological data

The following report was generated by the command (North Carolina sample dataset):

    # set computational region
    g.region raster=elevation -p

    # compute volume
    r.volume input=elevation clump=geology_30m
    #
    # Volume report on data from <elevation> using clumps on <geology_30m> raster map
    #
    # Category   Average   Data   # Cells        Centroid             Total
    # Number     in clump  Total  in clump   Easting     Northing     Volume
    # -----------------------------------------------------------------------------
    #      217    118.93  86288828  725562   635325.00   221535.00    8628882798.63
    #      262    108.97  21650560  198684   638935.00   222495.00    2165056037.02
    #      270     92.23  63578874  689373   642405.00   221485.00    6357887443.53
    #      405    132.96  33732662  253710   631835.00   224095.00    3373266208.59
    #      583    139.35   3011288   21609   630205.00   224665.00     301128821.55
    #      720    124.30    599618    4824   634075.00   227995.00      59961816.06
    #      766    132.43    936791    7074   631425.00   227845.00      93679120.08
    #      862    118.31   7302317   61722   630505.00   218885.00     730231746.74
    #      910     94.20   4235816   44964   639215.00   216365.00     423581613.11
    #      921    135.22   1693985   12528   630755.00   215445.00     169398523.05
    #      945    127.24      1145       9   630015.00   215015.00        114512.03
    #      946     89.91    365748    4068   639085.00   215255.00      36574833.85
    #      948    129.02    112632     873   630185.00   215115.00      11263181.57
    # -----------------------------------------------------------------------------
    #                                                 Total Volume = 22351026655.81

The `Data Total` column is the sum of the elevations for each in each of the fields. The `Total Volume` is the sum multiplied by the east-west resolution times the north-south resolution. Note that the units on the volume may be difficult if the units of cell values on the input raster map and the resolution units differ.

## SEE ALSO

r.clump, r.mask, r.mapcalc

## AUTHORS

Dr. James Hinthorne, Central Washington University GIS Laboratory, December 1988.
Updated to GRASS 7 by Martin Landa, Czech Technical University in Prague, Czech Republic