PostGIS: Calculate shortest distance between polygon
I have many polygons stored in a table. I want to filter out polygons where they separate too far away (say 1km).
My approach is:
calculate the minimum distance between a particular polygon to other polygons, and store the value in a new column in the table.
Then filter out polygon with minimum distance larger than 1 km.
I have tired to use:
ALTER TABLE "int_20190124" ADD "nearestDistance" float8;
INSERT INTO "int_20190124"("nearestDistance")
VALUES
(
SELECT ST_Distance("int_20190124".geom, "int_20190124".geom)
FROM "int_20190124"
ORDER BY ST_Distance("int_20190124".geom, "int_20190124".geom)
LIMIT 1
)
I am very new to postgis. Thanks for your help!
qgis postgis
asked 4 hours ago
JOHN JOHN
14817
add a comment |
I have many polygons stored in a table. I want to filter out polygons where they separate too far away (say 1km).
My approach is:
calculate the minimum distance between a particular polygon to other polygons, and store the value in a new column in the table.
Then filter out polygon with minimum distance larger than 1 km.
I have tired to use:
ALTER TABLE "int_20190124" ADD "nearestDistance" float8;
INSERT INTO "int_20190124"("nearestDistance")
VALUES
(
SELECT ST_Distance("int_20190124".geom, "int_20190124".geom)
FROM "int_20190124"
ORDER BY ST_Distance("int_20190124".geom, "int_20190124".geom)
LIMIT 1
)
I am very new to postgis. Thanks for your help!
qgis postgis
asked 4 hours ago
JOHN JOHN
14817
add a comment |
I have many polygons stored in a table. I want to filter out polygons where they separate too far away (say 1km).
My approach is:
calculate the minimum distance between a particular polygon to other polygons, and store the value in a new column in the table.
Then filter out polygon with minimum distance larger than 1 km.
I have tired to use:
ALTER TABLE "int_20190124" ADD "nearestDistance" float8;
INSERT INTO "int_20190124"("nearestDistance")
VALUES
(
SELECT ST_Distance("int_20190124".geom, "int_20190124".geom)
FROM "int_20190124"
ORDER BY ST_Distance("int_20190124".geom, "int_20190124".geom)
LIMIT 1
)
I am very new to postgis. Thanks for your help!
qgis postgis
asked 4 hours ago
JOHN JOHN
14817
I have many polygons stored in a table. I want to filter out polygons where they separate too far away (say 1km).
My approach is:
calculate the minimum distance between a particular polygon to other polygons, and store the value in a new column in the table.
Then filter out polygon with minimum distance larger than 1 km.
I have tired to use:
ALTER TABLE "int_20190124" ADD "nearestDistance" float8;
INSERT INTO "int_20190124"("nearestDistance")
VALUES
(
SELECT ST_Distance("int_20190124".geom, "int_20190124".geom)
FROM "int_20190124"
ORDER BY ST_Distance("int_20190124".geom, "int_20190124".geom)
LIMIT 1
)
I am very new to postgis. Thanks for your help!
qgis postgis
qgis postgis
asked 4 hours ago
JOHN JOHN
14817
asked 4 hours ago
JOHN JOHN
14817
asked 4 hours ago
JOHN JOHN
14817
asked 4 hours ago
JOHN JOHN
14817
asked 4 hours ago
JOHN JOHN
14817
14817
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
You can use ST_ClusterDBSCAN to group nearby geometries together and assigning them a cluster id. Cluster ID will be null for single geometries not within the specified distance of another.
Image taken from the help section showing cluster IDs:
This query should return only the records within 1000 m of Another. minpoints := 2 is to prevent single points from getting a cluster ID:
SELECT * FROM
(SELECT *, ST_ClusterDBSCAN(geom, eps := 1000, minpoints := 2) OVER () clust
FROM int_20190124) t1
WHERE t1.clust IS NOT NULL;
Example with points and 10000 m distance:
answered 4 hours ago
BERABERA
15.8k52042
Why minpoints := 2 and not minpoints := 1?
– John Powell
3 hours ago
With 1, single records with no other Points nearby will also get a cluster id. Dont you agree?
– BERA
3 hours ago
2
Yes, probably. I have always put array_agg(cluster_id) as cluster_ids in the inner select and then used WHERE array_length(cluster_ids, 1) > 1 for this kind of logic, but your approach is simpler. You should probably explain it in the answer, though, as ClusterDBScan is a bit non-obvious when you first see it +1 anyway, this really is one of my favourite functions, it has so many cool uses, that are really painful to do the old way with spatial self joins.
– John Powell
3 hours ago
@BERA Thank you! Although I still don't understand the query completely, it works! I will study more PostGIS later.
– JOHN
2 hours ago
The underlying theory for DBScan en.wikipedia.org/wiki/DBSCAN is worth a read. This is a somewhat tricky query as it also involves a window function, postgresql.org/docs/current/tutorial-window.html, so don't feel too bad if you don't get it immediately. The benefit of a window function is that you can return the actual geometry IDs in each cluster, which was not the case with the original Postgis clustering algorithms, such as, ST_ClusterIntersecting and ST_ClusterWithin.
– John Powell
2 hours ago
|
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1 Answer
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active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
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active
oldest
votes
You can use ST_ClusterDBSCAN to group nearby geometries together and assigning them a cluster id. Cluster ID will be null for single geometries not within the specified distance of another.
Image taken from the help section showing cluster IDs:
This query should return only the records within 1000 m of Another. minpoints := 2 is to prevent single points from getting a cluster ID:
SELECT * FROM
(SELECT *, ST_ClusterDBSCAN(geom, eps := 1000, minpoints := 2) OVER () clust
FROM int_20190124) t1
WHERE t1.clust IS NOT NULL;
Example with points and 10000 m distance:
answered 4 hours ago
BERABERA
15.8k52042
Why minpoints := 2 and not minpoints := 1?
– John Powell
3 hours ago
With 1, single records with no other Points nearby will also get a cluster id. Dont you agree?
– BERA
3 hours ago
2
Yes, probably. I have always put array_agg(cluster_id) as cluster_ids in the inner select and then used WHERE array_length(cluster_ids, 1) > 1 for this kind of logic, but your approach is simpler. You should probably explain it in the answer, though, as ClusterDBScan is a bit non-obvious when you first see it +1 anyway, this really is one of my favourite functions, it has so many cool uses, that are really painful to do the old way with spatial self joins.
– John Powell
3 hours ago
@BERA Thank you! Although I still don't understand the query completely, it works! I will study more PostGIS later.
– JOHN
2 hours ago
The underlying theory for DBScan en.wikipedia.org/wiki/DBSCAN is worth a read. This is a somewhat tricky query as it also involves a window function, postgresql.org/docs/current/tutorial-window.html, so don't feel too bad if you don't get it immediately. The benefit of a window function is that you can return the actual geometry IDs in each cluster, which was not the case with the original Postgis clustering algorithms, such as, ST_ClusterIntersecting and ST_ClusterWithin.
– John Powell
2 hours ago
|
show 1 more comment
You can use ST_ClusterDBSCAN to group nearby geometries together and assigning them a cluster id. Cluster ID will be null for single geometries not within the specified distance of another.
Image taken from the help section showing cluster IDs:
This query should return only the records within 1000 m of Another. minpoints := 2 is to prevent single points from getting a cluster ID:
SELECT * FROM
(SELECT *, ST_ClusterDBSCAN(geom, eps := 1000, minpoints := 2) OVER () clust
FROM int_20190124) t1
WHERE t1.clust IS NOT NULL;
Example with points and 10000 m distance:
answered 4 hours ago
BERABERA
15.8k52042
Why minpoints := 2 and not minpoints := 1?
– John Powell
3 hours ago
With 1, single records with no other Points nearby will also get a cluster id. Dont you agree?
– BERA
3 hours ago
2
Yes, probably. I have always put array_agg(cluster_id) as cluster_ids in the inner select and then used WHERE array_length(cluster_ids, 1) > 1 for this kind of logic, but your approach is simpler. You should probably explain it in the answer, though, as ClusterDBScan is a bit non-obvious when you first see it +1 anyway, this really is one of my favourite functions, it has so many cool uses, that are really painful to do the old way with spatial self joins.
– John Powell
3 hours ago
@BERA Thank you! Although I still don't understand the query completely, it works! I will study more PostGIS later.
– JOHN
2 hours ago
The underlying theory for DBScan en.wikipedia.org/wiki/DBSCAN is worth a read. This is a somewhat tricky query as it also involves a window function, postgresql.org/docs/current/tutorial-window.html, so don't feel too bad if you don't get it immediately. The benefit of a window function is that you can return the actual geometry IDs in each cluster, which was not the case with the original Postgis clustering algorithms, such as, ST_ClusterIntersecting and ST_ClusterWithin.
– John Powell
2 hours ago
|
show 1 more comment
You can use ST_ClusterDBSCAN to group nearby geometries together and assigning them a cluster id. Cluster ID will be null for single geometries not within the specified distance of another.
Image taken from the help section showing cluster IDs:
This query should return only the records within 1000 m of Another. minpoints := 2 is to prevent single points from getting a cluster ID:
SELECT * FROM
(SELECT *, ST_ClusterDBSCAN(geom, eps := 1000, minpoints := 2) OVER () clust
FROM int_20190124) t1
WHERE t1.clust IS NOT NULL;
Example with points and 10000 m distance:
answered 4 hours ago
BERABERA
15.8k52042
You can use ST_ClusterDBSCAN to group nearby geometries together and assigning them a cluster id. Cluster ID will be null for single geometries not within the specified distance of another.
Image taken from the help section showing cluster IDs:
This query should return only the records within 1000 m of Another. minpoints := 2 is to prevent single points from getting a cluster ID:
SELECT * FROM
(SELECT *, ST_ClusterDBSCAN(geom, eps := 1000, minpoints := 2) OVER () clust
FROM int_20190124) t1
WHERE t1.clust IS NOT NULL;
Example with points and 10000 m distance:
answered 4 hours ago
BERABERA
15.8k52042
edited 3 hours ago
answered 4 hours ago
BERABERA
15.8k52042
answered 4 hours ago
BERABERA
15.8k52042
answered 4 hours ago
BERABERA
15.8k52042
15.8k52042
Why minpoints := 2 and not minpoints := 1?
– John Powell
3 hours ago
With 1, single records with no other Points nearby will also get a cluster id. Dont you agree?
– BERA
3 hours ago
2
Yes, probably. I have always put array_agg(cluster_id) as cluster_ids in the inner select and then used WHERE array_length(cluster_ids, 1) > 1 for this kind of logic, but your approach is simpler. You should probably explain it in the answer, though, as ClusterDBScan is a bit non-obvious when you first see it +1 anyway, this really is one of my favourite functions, it has so many cool uses, that are really painful to do the old way with spatial self joins.
– John Powell
3 hours ago
@BERA Thank you! Although I still don't understand the query completely, it works! I will study more PostGIS later.
– JOHN
2 hours ago
The underlying theory for DBScan en.wikipedia.org/wiki/DBSCAN is worth a read. This is a somewhat tricky query as it also involves a window function, postgresql.org/docs/current/tutorial-window.html, so don't feel too bad if you don't get it immediately. The benefit of a window function is that you can return the actual geometry IDs in each cluster, which was not the case with the original Postgis clustering algorithms, such as, ST_ClusterIntersecting and ST_ClusterWithin.
– John Powell
2 hours ago
|
show 1 more comment
Why minpoints := 2 and not minpoints := 1?
– John Powell
3 hours ago
With 1, single records with no other Points nearby will also get a cluster id. Dont you agree?
– BERA
3 hours ago
2
Yes, probably. I have always put array_agg(cluster_id) as cluster_ids in the inner select and then used WHERE array_length(cluster_ids, 1) > 1 for this kind of logic, but your approach is simpler. You should probably explain it in the answer, though, as ClusterDBScan is a bit non-obvious when you first see it +1 anyway, this really is one of my favourite functions, it has so many cool uses, that are really painful to do the old way with spatial self joins.
– John Powell
3 hours ago
@BERA Thank you! Although I still don't understand the query completely, it works! I will study more PostGIS later.
– JOHN
2 hours ago
The underlying theory for DBScan en.wikipedia.org/wiki/DBSCAN is worth a read. This is a somewhat tricky query as it also involves a window function, postgresql.org/docs/current/tutorial-window.html, so don't feel too bad if you don't get it immediately. The benefit of a window function is that you can return the actual geometry IDs in each cluster, which was not the case with the original Postgis clustering algorithms, such as, ST_ClusterIntersecting and ST_ClusterWithin.
– John Powell
2 hours ago
Why minpoints := 2 and not minpoints := 1?
– John Powell
3 hours ago
Why minpoints := 2 and not minpoints := 1?
– John Powell
3 hours ago
With 1, single records with no other Points nearby will also get a cluster id. Dont you agree?
– BERA
3 hours ago
With 1, single records with no other Points nearby will also get a cluster id. Dont you agree?
– BERA
3 hours ago
2
2
Yes, probably. I have always put array_agg(cluster_id) as cluster_ids in the inner select and then used WHERE array_length(cluster_ids, 1) > 1 for this kind of logic, but your approach is simpler. You should probably explain it in the answer, though, as ClusterDBScan is a bit non-obvious when you first see it +1 anyway, this really is one of my favourite functions, it has so many cool uses, that are really painful to do the old way with spatial self joins.
– John Powell
3 hours ago
Yes, probably. I have always put array_agg(cluster_id) as cluster_ids in the inner select and then used WHERE array_length(cluster_ids, 1) > 1 for this kind of logic, but your approach is simpler. You should probably explain it in the answer, though, as ClusterDBScan is a bit non-obvious when you first see it +1 anyway, this really is one of my favourite functions, it has so many cool uses, that are really painful to do the old way with spatial self joins.
– John Powell
3 hours ago
@BERA Thank you! Although I still don't understand the query completely, it works! I will study more PostGIS later.
– JOHN
2 hours ago
@BERA Thank you! Although I still don't understand the query completely, it works! I will study more PostGIS later.
– JOHN
2 hours ago
The underlying theory for DBScan en.wikipedia.org/wiki/DBSCAN is worth a read. This is a somewhat tricky query as it also involves a window function, postgresql.org/docs/current/tutorial-window.html, so don't feel too bad if you don't get it immediately. The benefit of a window function is that you can return the actual geometry IDs in each cluster, which was not the case with the original Postgis clustering algorithms, such as, ST_ClusterIntersecting and ST_ClusterWithin.
– John Powell
2 hours ago
The underlying theory for DBScan en.wikipedia.org/wiki/DBSCAN is worth a read. This is a somewhat tricky query as it also involves a window function, postgresql.org/docs/current/tutorial-window.html, so don't feel too bad if you don't get it immediately. The benefit of a window function is that you can return the actual geometry IDs in each cluster, which was not the case with the original Postgis clustering algorithms, such as, ST_ClusterIntersecting and ST_ClusterWithin.
– John Powell
2 hours ago
|
show 1 more comment
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