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 if no band is specified.
summarystats ST_SummaryStats(raster rast, boolean exclude_nodata_value);
summarystats ST_SummaryStats(raster rast, integer nband, boolean exclude_nodata_value);
Gibt summarystats aus, bestehend aus der Anzahl, der Summe, dem arithmetischen Mittel, der Standardabweichung, dem Minimum und dem Maximum der Werte eines Rasterbandes oder eines Rastercoverage. Wenn kein Band angegeben ist, wird Band 1 angenommen.
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Standardmäßig werden nur jene Pixelwerte berücksichtigt, die nicht den Wert |
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Standardmäßig werden alle Pixel abgetastet. Um eine schnellere Rückmeldung zu bekommen, können Sie den Parameter |
Geändert: 3.1.0 ST_SummaryStats(rastertable, rastercolumn, ...) Varianten wurden entfernt. Verwenden Sie stattdessen ST_SummaryStatsAgg.
Verfügbarkeit: 2.0.0
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
Summarize pixels that intersect buildings of interest.
This example selects the target buildings, clips band 2 of the raster tiles to each building boundary, computes statistics for each clipped region, and then summarizes those statistics by building. It 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
Raster coverage.
This example returns statistics 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, sampling less than 100% can improve speed. Here the sampling is set to 25%.
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