ST_SummaryStats
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## Name

ST_SummaryStats — Returns summarystats consisting of count, sum, mean, stddev, min, max for a given raster band of a raster or raster coverage. Band 1 is assumed is no band is specified.

## Synopsis

`summarystats ST_SummaryStats(`raster rast, boolean exclude_nodata_value`)`;

`summarystats ST_SummaryStats(`raster rast, integer nband, boolean exclude_nodata_value`)`;

## Description

Returns summarystats consisting of count, sum, mean, stddev, min, max for a given raster band of a raster or raster coverage. If no band is specified `nband` defaults to 1.

By default only considers pixel values not equal to the `nodata` value. Set `exclude_nodata_value` to false to get count of all pixels.

By default will sample all pixels. To get faster response, set `sample_percent` to lower than 1

Changed: 3.1.0 ST_SummaryStats(rastertable, rastercolumn, ...) variants are removed. Use ST_SummaryStatsAgg instead.

Availability: 2.0.0

## Example: Single raster tile

    SELECT rid, band, (stats).*
    FROM (SELECT rid, band, ST_SummaryStats(rast, band) As stats
        FROM dummy_rast CROSS JOIN generate_series(1,3) As band
         WHERE rid=2) As foo;

     rid | band | count | sum  |    mean    |  stddev   | min | max
    -----+------+-------+------+------------+-----------+-----+-----
       2 |    1 |    23 | 5821 | 253.086957 |  1.248061 | 250 | 254
       2 |    2 |    25 | 3682 |     147.28 | 59.862188 |  78 | 254
       2 |    3 |    25 | 3290 |      131.6 | 61.647384 |  62 | 254

## Example: Summarize pixels that intersect buildings of interest

This example took 574ms on PostGIS windows 64-bit with all of Boston Buildings and aerial Tiles (tiles each 150x150 pixels ~ 134,000 tiles), ~102,000 building records

    WITH
    -- our features of interest
       feat AS (SELECT gid As building_id, geom_26986 As geom FROM buildings AS b
        WHERE gid IN(100, 103,150)
       ),
    -- clip band 2 of raster tiles to boundaries of builds
    -- then get stats for these clipped regions
       b_stats AS
        (SELECT  building_id, (stats).*
    FROM (SELECT building_id, ST_SummaryStats(ST_Clip(rast,2,geom)) As stats
        FROM aerials.boston
            INNER JOIN feat
        ON ST_Intersects(feat.geom,rast)
     ) As foo
     )
    -- finally summarize stats
    SELECT building_id, SUM(count) As num_pixels
      , MIN(min) As min_pval
      ,  MAX(max) As max_pval
      , SUM(mean*count)/SUM(count) As avg_pval
        FROM b_stats
     WHERE count > 0
        GROUP BY building_id
        ORDER BY building_id;
     building_id | num_pixels | min_pval | max_pval |     avg_pval
    -------------+------------+----------+----------+------------------
             100 |       1090 |        1 |      255 | 61.0697247706422
             103 |        655 |        7 |      182 | 70.5038167938931
             150 |        895 |        2 |      252 | 185.642458100559

## Example: Raster coverage

    -- stats for each band --
    SELECT band, (stats).*
    FROM (SELECT band, ST_SummaryStats('o_4_boston','rast', band) As stats
        FROM generate_series(1,3) As band) As foo;

     band |  count  |  sum   |       mean       |      stddev      | min | max
    ------+---------+--------+------------------+------------------+-----+-----
        1 | 8450000 | 725799 | 82.7064349112426 | 45.6800222638537 |   0 | 255
        2 | 8450000 | 700487 | 81.4197705325444 | 44.2161184161765 |   0 | 255
        3 | 8450000 | 575943 |  74.682739408284 | 44.2143885481407 |   0 | 255

    -- For a table -- will get better speed if set sampling to less than 100%
    -- Here we set to 25% and get a much faster answer
    SELECT band, (stats).*
    FROM (SELECT band, ST_SummaryStats('o_4_boston','rast', band,true,0.25) As stats
        FROM generate_series(1,3) As band) As foo;

     band |  count  |  sum   |       mean       |      stddev      | min | max
    ------+---------+--------+------------------+------------------+-----+-----
        1 | 2112500 | 180686 | 82.6890480473373 | 45.6961043857248 |   0 | 255
        2 | 2112500 | 174571 |  81.448503668639 | 44.2252623171821 |   0 | 255
        3 | 2112500 | 144364 | 74.6765884023669 | 44.2014869384578 |   0 | 255

## See Also

summarystats, ST_SummaryStatsAgg, ST_Count, ST_Clip

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