ST_SummaryStats — 返回一组总结统计信息,包括给定栅格或栅格覆盖的栅格带的计数、总和、均值、标准差、最小值和最大值。如果未指定带号,则假定为带1。
summarystats ST_SummaryStats(
raster rast, boolean exclude_nodata_value)
;
summarystats ST_SummaryStats(
raster rast, integer nband, boolean exclude_nodata_value)
;
返回栅格或栅格覆盖范围的给定栅格波段的summarystats统计信息,其中包含计数、总和、平均值、标准差、最小值、最大值。 如果未指定 band,则 nband
默认为 1。
默认情况下,仅考虑不等于 |
默认情况下将对所有像素进行采样。 为了获得更快的响应,请将 |
更改:3.1.0 ST_SummaryStats(rastertable, rastercolumn, ...) 变体已删除。 请改用 ST_SummaryStatsAgg。
可用性: 2.0.0
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
此示例在 64 位 PostGIS 窗口上花费了 574 毫秒,包含所有波士顿建筑物和空中图块(每个图块 150x150 像素 ~ 134,000 个图块),约 102,000 个建筑记录
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
-- 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