{"id":20482827,"url":"https://github.com/oliverhennhoefer/arcpy-supercluster","last_synced_at":"2025-07-12T23:38:20.139Z","repository":{"id":173469486,"uuid":"194427568","full_name":"OliverHennhoefer/arcpy-supercluster","owner":"OliverHennhoefer","description":"Python-Implementation of the Spatial Clustering Algorithm 'Supercluster' for ArcGIS and ArcPy.","archived":false,"fork":false,"pushed_at":"2022-07-18T14:29:46.000Z","size":1232,"stargazers_count":5,"open_issues_count":0,"forks_count":2,"subscribers_count":0,"default_branch":"master","last_synced_at":"2025-05-30T03:38:43.573Z","etag":null,"topics":["algorithm","arcgis","arcpy","arcpython","clustering","clustering-algorithm","spatial","spatial-analysis","spatial-clustering","supercluser"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/OliverHennhoefer.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2019-06-29T16:41:17.000Z","updated_at":"2025-02-02T14:47:39.000Z","dependencies_parsed_at":null,"dependency_job_id":"472ffd48-a94c-4ed8-90f1-f851428c4faa","html_url":"https://github.com/OliverHennhoefer/arcpy-supercluster","commit_stats":null,"previous_names":["oliverhennhoefer/arcpy-supercluster"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/OliverHennhoefer/arcpy-supercluster","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/OliverHennhoefer%2Farcpy-supercluster","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/OliverHennhoefer%2Farcpy-supercluster/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/OliverHennhoefer%2Farcpy-supercluster/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/OliverHennhoefer%2Farcpy-supercluster/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/OliverHennhoefer","download_url":"https://codeload.github.com/OliverHennhoefer/arcpy-supercluster/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/OliverHennhoefer%2Farcpy-supercluster/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":263585900,"owners_count":23484488,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["algorithm","arcgis","arcpy","arcpython","clustering","clustering-algorithm","spatial","spatial-analysis","spatial-clustering","supercluser"],"created_at":"2024-11-15T16:14:42.847Z","updated_at":"2025-07-04T17:10:50.952Z","avatar_url":"https://github.com/OliverHennhoefer.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# ArcPy \"Supercluster\" algorithm for ArcGIS\nAn Implementation of the simple and fast spatial clustering algorithm *'supercluster'* (e.g. used by *Mapbox*) for ArcGIS that efficiently  clusters huge datasets of points. Primarily suitable for creating maps of smaller scales. \n\n\u0026#x1F4D7; Trial project. Primarily implemented to get familiar with the python syntax and the ArcPy interface for ArcGIS.\n\n## Parameters:\u003cbr/\u003e\n- Input: FeatureClass (Point)\u003cbr/\u003e\n- Input: Cluster radius (in meter)\u003cbr/\u003e\n- Output: FeatureClass (Point)\u003cbr/\u003e\n\n## Steps:\u003cbr/\u003e\n1. Start with a random point of the dataset\u003cbr/\u003e\n2. Find every point that lies within the given radius around this point\u003cbr/\u003e\n3. Form a cluster with the nearby points\u003cbr/\u003e\n4. Randomly select a new point of the dataset that isn't part of a cluster and repeat the previous steps.\n\n## Result:\u003cbr/\u003e\nOriginal point data \u003c/br\u003e\nResult for a (cluster-)radius of 500 meters \u003c/br\u003e\nResult for a (cluster-)radius of 1000 meters \u003c/br\u003e\n\n![alt text](https://github.com/OliverHennhoefer/ArcPy_Supercluster/blob/master/supercluster_result.PNG)\n*Note: Since the algorithm randomly chooses points for clustering, the results vary for every application of 'supercluster'*\n\n## Future Improvements:\u003cbr/\u003e\n- Calculate the mean position out of the points of one cluster to get more representative cluster locations.\n- Add the possibility to fit additional attributes to the corresponding cluster (e.g. by calculating the mean for the points of the same cluster)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Foliverhennhoefer%2Farcpy-supercluster","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Foliverhennhoefer%2Farcpy-supercluster","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Foliverhennhoefer%2Farcpy-supercluster/lists"}