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6

I'd suggest to use the ST_ClusterDBSCAN Window function rather than the Aggregate function ST_ClusterWithin: SELECT *, ST_ClusterDBSCAN(the_geom, eps := <distance>, minpoints := 1) OVER() AS clst_id FROM all_locations ; clst_id will hold INT values representing the cluster each rows geometry belongs to. As stated in the comments, ...


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Based on the discussion above, I further explored the respective literature and found a very suitable algorithm addressing my question. The method is capable of defining neighborhood through rows and columns in the grid rather than distances between pixel centroids. I can directly choose between Queen's and Rook's case contiguity. Distances do not have to be ...


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I came across an R package that will help you do this, called "Clustgeo". https://cran.r-project.org/web/packages/ClustGeo/index.html You can adjust the values for a parameter. "alpha", to control the weight placed on the spatial proximity of the cells to one another. The value can be adjusted between 0-1, where 0 represents no weight on the spatial data (...


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replace the code by : var markers = L.markerClusterGroup(); const geojsonGroup = L.geoJSON(street, { onEachFeature : function(feature, layer){ var popupContent = '<h4 class = "text-primary">Street Light</h4>' + '<div class="container"><table class="table table-striped">' + ...


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