I have a dataset with around 900 points and I want to cluster them into groups of 44 based on proximity.
Is this possible in QGIS?
I have tried to use the convex hull tool with no success.
[GIS] Creating Groups of points based on proximity in QGIS
clusteringgroupingqgisspatial-cluster
Related Solutions
I'm not at a computer that has access to PostGIS right now, but I feel as though this algorithm might work. Of course if you have vertical groups, you would need to use an exclusion or inclusion clause for ST_Y().
DECLARE @totalUnique int = 0
DECLARE @lastUnique int = 1
CREATE TABLE #TABLEX (ID1 int, ID2 int)
CREATE TABLE #TABLEX2 (ID1 int, ID2 int)
--Get distances of objects
INSERT INTO #TABLEX
SELECT ID1, ID2
FROM (
SELECT T1.ID AS ID1,
T2.ID AS ID2
FROM BaseTable AS T1
INNER JOIN
BaseTable AS T2
ON ST_Distance(T1.Shape, T2.Shape) <= SeparationDistance
) AS X
--Loop for as long as new connections can be made
WHILE(@lastUnique <> @totalUnique)
BEGIN
--Count the number of current connections
SELECT @lastUnique = COUNT(*)
FROM (
SELECT * FROM #TABLEX
GROUP BY ID1, ID2
) AS XX
--Look for new connections via current known paths
INSERT INTO #TABLEX (ID1, ID2)
SELECT A.ID1, B.ID2
FROM #TABLEX AS A
INNER JOIN
#TABLEX AS B
ON A.ID2 = B.ID1
AND
A.ID1 <> B.ID2
--Count the number of current connections
SELECT @totalUnique = COUNT(*)
FROM (
SELECT * FROM #TABLEX
GROUP BY ID1, ID2
) AS XX
--Group each path set by the lowest ID
INSERT INTO #TABLEX2(ID1, ID2)
SELECT MIN(ID1) AS theGroup, ID2
FROM #TABLEX
GROUP BY ID2
TRUNCATE TABLE #TABLEX
--Reload our new path sets
INSERT INTO #TABLEX (ID1, ID2)
SELECT ID1, ID2 FROM #TABLEX2
TRUNCATE TABLE #TABLEX2
END
--Show final results
SELECT ID1 AS theGroup, ID2
FROM #TABLEX
DROP TABLE #TABLEX
DROP TABLE #TABLEX2
you can try this (did this in QGIS 2.16)
- fixed distance buffer each point by 250m (this is half the required distance between points)
- then dissolve all on the result of that
- then use multipart to singlepart to split each cluster into its own feature
- add a field (using the expression @row_number) to assign a unique ID to each cluster.
you then get something like this...
Now use join attributes by location on your points layer to find out which cluster each point falls inside (using 'within'/'take attributes of first selected feature').
Finally the Concave hull plugin. Sadly this doesn't appear to support "by field" concave hulls like the Convex hull functionality. So you'll need to select and export each cluster yourself and run Concave Hull on each one separately. Here's what cluster #1 looks like as a concave hull...
So each point within that cluster is within 500m of another point in that cluster.
Note that a point with no neighbours within 500m will probably have a concave hull which collapses to a point. And one with only one neighbour will probably have a concave hull which is a line. I haven't tested these, though.
Tip - 800k is a lot of points. For your own productivity and to avoid frustration, I suggest you try this on a small region, or a small random selection of your data first. It's easy to get an option wrong, and this could take some time on a set that large ;) This might be done faster with postgis
Best Answer
You can use ClusterPoint plugin. After installing the plugin, a tool named doCluster is added to Processing Toolbox.
Cluster Points adds a new field
Cluster_IDto the attribute table as output. (In the image, points are styled categorically byCluster_ID)