Changeset: fec8aa18d67b for MonetDB
URL: http://dev.monetdb.org/hg/MonetDB?cmd=changeset;node=fec8aa18d67b
Modified Files:
sql/test/sciql/Tests/teleios_noa_bsm.sql
Branch: sciql
Log Message:
some corrections while trying to run the queries one-by-one
diffs (122 lines):
diff --git a/sql/test/sciql/Tests/teleios_noa_bsm.sql
b/sql/test/sciql/Tests/teleios_noa_bsm.sql
--- a/sql/test/sciql/Tests/teleios_noa_bsm.sql
+++ b/sql/test/sciql/Tests/teleios_noa_bsm.sql
@@ -1,64 +1,66 @@
-DECLARE size_x INT, size_y INT;
-SET size_x = $img_len;
-SET size_y = $img_hei;
+SET SCHEMA rs;
--- Assuming the TIFF images have been imported as the following:
+-- Assuming these example TIF images are stored in /tmp
+-- The orthorectified images need the GDAL functions attach2() and import2()
+CALL rs.attach2('/tmp/img1_b3.tif');
+CALL rs.attach2('/tmp/img1_b4.tif');
+CALL rs.attach2('/tmp/img1_b7.tif');
+
+CALL rs.attach2('/tmp/img2_b3.tif');
+CALL rs.attach2('/tmp/img2_b4.tif');
+CALL rs.attach2('/tmp/img2_b7.tif');
+
+CALL rs.import2(1);
+CALL rs.import2(2);
+CALL rs.import2(3);
+CALL rs.import2(1);
+CALL rs.import2(2);
+CALL rs.import2(3);
+-- Now the TIF images have been imported as the following:
-- the b3, b4 and b7 of the 1st image as rs.image1, rs.image2 and rs.image3
-- the b3, b4 and b7 of the 2nd image as rs.image4, rs.image5 and rs.image6
--- Then, put the three bands of each image into one array:
-CREATE ARRAY landsat5_img1 (x INT DIMENSION[size_x], y INT DIMENSION[size_y],
b3 INT, b4 INT, b7 INT);
-CREATE ARRAY landsat5_img2 (x INT DIMENSION[size_x], y INT DIMENSION[size_y],
b3 INT, b4 INT, b7 INT);
-INSERT INTO landsat5_img1 (
- SELECT img1.x, img1.y, img1.intensity AS b3,
- img2.intensity AS b4, img3.intensity AS b7
- FROM rs.image1 AS img1, rs.image2 AS img2, rs.image3 AS img3
- WHERE img1.x = img2.x AND img1.x = img3.x
- AND img1.y = img2.y AND img1.y = img3.y);
-INSERT INTO landsat5_img2 (
- SELECT img4.x, img4.y, img4.intensity AS b3,
- img5.intensity AS b4, img6.intensity AS b7
- FROM rs.image4 AS img4, rs.image5 AS img5, rs.image6 AS img6
- WHERE img4.x = img5.x AND img4.x = img6.x
- AND img4.y = img5.y AND img4.y = img6.y);
+DECLARE size_x INT, size_y INT;
+SET size_x = (SELECT MAX(x) + 1 FROM rs.image1);
+SET size_y = (SELECT MAX(y) + 1 FROM rs.image1);
-- BSM classification (landsatFirePredicate()) using one image
CREATE ARRAY fire1 (x INT DIMENSION[size_x], y INT DIMENSION[size_y], f INT
DEFAULT 0);
INSERT INTO fire1 (
- SELECT x, y, 1
- FROM landsat5_img1
- WHERE b3 <> 0 AND b4 <> 0 AND b7 <> 0
- AND b4 <= 60 -- indexNIR
- AND FLOOR(CAST(b3+b4 AS DOUBLE)/2.0) <= 50.0 -- indexALBEDO
- AND b4 + b7 <> 0.0
- AND (CAST(b4-b7 AS DOUBLE)/(b4 + b7) + 1.0) * 127.0 <= 126.0 -- indexNBR,
255.0/2.0=127.0
+ SELECT b3.x, b3.y, 1
+ FROM rs.image1 AS b3, rs.image2 AS b4, rs.image3 AS b7
+ WHERE b3.intensity <> 0 AND b4.intensity <> 0 AND b7.intensity <> 0
+ AND b4.intensity <= 60 -- indexNIR
+ AND b3.x = b4.x AND b3.y = b4.y AND b3.x = b7.x AND b3.y = b3.y -- join
the images
+ AND FLOOR(CAST(b3.intensity+b4.intensity AS DOUBLE)/2.0) <= 50.0 --
indexALBEDO
+ AND b4.intensity + b7.intensity <> 0.0
+ AND (CAST(b4.intensity-b7.intensity AS DOUBLE)/(b4.intensity +
b7.intensity) + 1.0) * 127.0 <= 126.0 -- indexNBR, 255.0/2.0=127.0
);
-- BSM classification (landsatFirePredicate()) using two images
CREATE ARRAY fire2 (x INT DIMENSION[size_x], y INT DIMENSION[size_y], f INT
DEFAULT 0);
INSERT INTO fire2 (
SELECT img1.x, img1.y, 1
- FROM landsat5_img1 AS img1, landsat5_img2 AS img2
- WHERE img1.b3 <> 0 AND img1.b4 <> 0 AND img1.b7 <> 0
- AND img1.b4 <= 60 -- indexNIR_img1
- AND FLOOR(CAST(img1.b3+img1.b4 AS DOUBLE)/2.0) <= 50.0 -- indexALBEDO_img1
- AND img1.b4 + img1.b7 <> 0.0
- AND (CAST(img1.b4-img1.b7 AS DOUBLE)/(img1.b4 + img1.b7) + 1.0) * 127.0 <=
126.0 -- indexNBR_img1
- AND img1.b4 + img1.b3 <> 0.0 AND img2.b4 + img2.b3 <> 0.0
- AND ABS( CAST(img1.b4-img1.b3 AS DOUBLE)/(img1.b4 + img1.b3) -
- CAST(img2.b4-img2.b3 AS DOUBLE)/(img2.b4 + img2.b3) ) >
$__ndviThreshold
- AND img1.x = img2.x AND img1.y = img2.y
+ FROM rs.image1 AS img1_b3, rs.image2 AS img1_b4, rs.image3 AS img1_b7,
+ rs.image4 AS img2_b3, rs.image5 AS img2_b4
+ WHERE img1_b3.intensity <> 0 AND img1_b4.intensity <> 0 AND
img1_b7.intensity <> 0
+ AND img1_b4.intensity <= 60 -- indexNIR_img1
+ AND img1_b3.x = img1_b4.x AND img1_b3.y = img1_b4.y AND img1_b3.x =
img1_b7.x AND img1_b3.y = img1_b3.y -- join the images
+ AND FLOOR(CAST(img1_b3.intensity+img1_b4.intensity AS DOUBLE)/2.0) <= 50.0
-- indexALBEDO_img1
+ AND img1_b4.intensity + img1_b7.intensity <> 0.0
+ AND (CAST(img1_b4.intensity-img1_b7.intensity AS
DOUBLE)/(img1_b4.intensity + img1_b7.intensity) + 1.0) * 127.0 <= 126.0 --
indexNBR_img1
+ AND img1_b3.x = img2_b3.x AND img1_b3.y = img2_b3.y AND img1_b3.x =
img2_b4.x AND img1_b3.y = img2_b4.y -- join the images
+ AND img1_b4.intensity + img1_b3.intensity <> 0.0 AND img2_b4.intensity +
img2_b3.intensity <> 0.0
+ AND ABS( CAST(img1_b4.intensity-img1_b3.intensity AS
DOUBLE)/(img1_b4.intensity + img1_b3.intensity) -
+ CAST(img2_b4.intensity-img2_b3.intensity AS
DOUBLE)/(img2_b4.intensity + img2_b3.intensity) ) > $__ndviThreshold
);
--- BSM cloud-water mask filter
----- TODO
-
-- BSM majority filter
DECLARE half_wsize INT;
SET half_wsize = $WINDOW_SIZE/2; -- using a 3x3 or 5x5 window
-CREATE ARRAY fire_marjority (x INT DIMENSION[size_x], y INT DIMENSION[size_y],
f INT DEFAULT 0);
+CREATE ARRAY fire_majority (x INT DIMENSION[size_x], y INT DIMENSION[size_y],
f INT DEFAULT 0);
CREATE VIEW neighbours AS
- SELECT [x], [y], SUM(v)-v AS neighbour_cnt
+ SELECT [x], [y], SUM(f)-f AS neighbour_cnt
FROM fire1
GROUP BY fire1[x-half_wsize:x+half_wsize+1][y-half_wsize:y+half_wsize+1];
@@ -70,6 +72,10 @@ INSERT INTO fire_majority (
AND neighbour_cnt > half_wsize
);
+-------------------------------------------------------------------------------
+-- above queries are tested
+-------------------------------------------------------------------------------
+
-- BSM clump&eliminate filter
CREATE ARRAY fire_eliminated (x INT DIMENSION[size_x], y INT
DIMENSION[size_y], gid INT);
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