Beschreibung

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.

	Standardmäßig werden nur jene Pixelwerte berücksichtigt, die nicht den Wert NODATA haben. Setzen Sie bitte exclude_nodata_value auf FALSE um die Anzahl sämtlicher Pixel zu erhalten.

	Standardmäßig werden alle Pixel abgetastet. Um eine schnellere Rückmeldung zu bekommen, können Sie den Parameter sample_percent auf einen Wert kleiner als 1 setzen.

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

Verfügbarkeit: 2.0.0

Beispiel: Einzelne Rasterkachel

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
                

Beispiel: Zusammenfassen der Pixel, die interessante Bauwerke schneiden

Dieses Beispiel benötigte 574ms in PostGIS unter Windows 64-Bit, mit allen Bauwerken und Luftbildkacheln von Boston (Kacheln jeweils 150x150 Pixel ~ 134.000 Kacheln; ~ 102.000 Datensätze mit Bauwerken)

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

Beispiel: Rastercoverage

-- 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
                

Siehe auch

summarystats, ST_SummaryStatsAgg, ST_Count, ST_Clip