Server-side geo clustering for Drupal 7

Introduction
1. Motivation
  1. Usability
    1. summarize data at high zoom levels by clustering
    2. allow exploration of individual points at lower zoom levels
  2. Speed
    1. Browser javascript/memory limitations
    2. Even more for mobile
  3. http://blog.davebouwman.com/2012/03/24/server-side-clustering-why-you-need-it/
  4. http://www.svennerberg.com/2009/01/handling-large-amounts-of-markers-in-google-maps/
2. Problem statement
3. Aim of the work
  1. Use cases
  2. Examples
    1. http://www.crunchpanorama.com/
    2. http://gmaps-utility-library.googlecode.com/svn/trunk/markerclusterer/1.0/examples/speed_test_example.html
    3. http://www.panoramio.com/map/
    4. http://www.usda.gov/recovery/map/
4. Methodological approach
5. Structure of the work
6. Clustering
  1. Blog: exploring large sets of geodata
    1. http://groups.drupal.org/node/104014
  2. Benchmarking OpenLayers with Drupal
    1. http://rjsteinert.com/content/benchmarking-openlayers-module-views-and-openlayersjs
  3. WFS (D6 wenig user)
    1. http://drupal.org/project/wfs
Foundations
1. Theory
  1. Names, Keywords
    1. Geospatial clustering
    2. Analytical regionalization
    3. Spatially constrained clustering
  2. Approaches
    1. Where to cluster
      1. Clustering Client-side
      2. Clustering by Logic
      3. Clustering by Database
    2. When to cluster
      1. realtime / on-request
      2. Pre-cluster / store clusters in db
    3. How to cluster
      1. Basic
      2. Distance
      3. Advanced
      4. Feature-based clusters?
      5. article
      6. http://web.archive.org/web/20071121140547/http://trib.tv/tech/clustering-points-on-a-google-map/
      7. Basic Types
      8. Well-separated: Points belong to a cluster when they are closer to every point in the cluster than they are to any point not in the cluster. This requires each cluster of points to be separated by a distance at least equal to the diameter of the largest cluster at its longest point.
      9. Prototype-based: Points belong to a cluster when they are closer or more similar to the cluster’s prototype, ie. a point representing the cluster as a whole, than they are to any other cluster’s prototype. This tends to result in circular clusters since the prototype (in a geospatial dataset anyway) is usually the centrepoint of the cluster.
      10. Graph-based: A cluster is defined as a set of points that are all connected, directly or via a chain of other points, to each other, and which are not connected to any point not in the cluster.
      11. Density-based: A cluster exists where there is a region of high density surrounded by a region of low density. These clusters can end up being any shape, and vary widely in size.
      12. Conceptual: A cluster exists where all points in the cluster share a common attribute which is not present in any point outside the cluster.
      13. Implementation types
      14. Variable gridding
      15. Interleaved digits
      16. K-Means
      17. QT-Clust
      18. DBSCAN
      19. Agglomerative Hierarchical Clustering
      20. Grid based viral growth argorithm
      21. article2
      22. http://www.biomedware.com/files/documentation/boundaryseer/Cluster/About_spatially_constrained_clustering.htm
    4. Questions
      1. what about performance?
      2. how do filters work?
      3. how well does it integrate with current drupal mapping technologies?
      4. how does caching work?
      5. how does client interaction work?
      6. how does it work with and without spatial database capabilities?
  3. Algorithms
    1. OPTICS
      1. http://en.wikipedia.org/wiki/OPTICS_algorithm
    2. Quadtrees + hilbert courve blog post
      1. http://blog.notdot.net/2009/11/Damn-Cool-Algorithms-Spatial-indexing-with-Quadtrees-and-Hilbert-Curves
    3. Region quadtree
      1. http://en.wikipedia.org/wiki/Quadtree#The_region_quadtree
      2. http://gis.stackexchange.com/questions/5394/incremental-spatial-clustering-algorithm
    4. K-Means
      1. http://en.wikipedia.org/wiki/K-means_clustering
      2. Polymaps k-means
      3. http://polymaps.org/ex/cluster.html
      4. no interactivity, static
      5. PostGIS
      6. http://pgxn.org/dist/kmeans/doc/kmeans.html
      7. how to use
      8. http://gis.stackexchange.com/questions/11567/spatial-clustering-with-postgis
      9. MySQL
      10. SQLDM – implementing k-means clustering using SQL
      11. http://www.abibasystems.com/white_paper/sqldm.pdf
      12. Java impl
      13. http://www.javaworld.com/javaworld/jw-11-2006/jw-1121-thread.html?page=1
      14. Drupal ideas
      15. http://groups.drupal.org/node/104014
      16. paper
      17. http://ilpubs.stanford.edu:8090/778/
      18. k-means++: The Advantages of Careful Seeding
    5. SnapToGrid
      1. http://postgis.refractions.net/docs/ST_SnapToGrid.html
    6. More
      1. http://en.wikipedia.org/wiki/Carrot2
      2. http://136.159.122.181:8080/geoclustering/help.php
      3. http://136.159.122.181:8080/geoclustering/
      4. http://chemometria.us.edu.pl/index.php?goto=downloads
    7. clusterPy algorithms
      1. AMOEBA A Multidirectional Optimum Ecotope-Based Algorithm
      2. AriSeL - Automatic Rationalization with Initial Seed Location
      3. Automatic Zoning Procedure (AZP)
      4. Reactive tabu variant of Automatic Zoning Procedure (AZP-R-Tabu)
      5. Simulated Annealing variant of Automatic Zoning Procedure (AZP-SA)
      6. Tabu variant of Automatic Zoning Procedure (AZP-Tabu)
      7. Geo Self Organizing Map(geoSOM)
      8. Max-p-regions model (Tabu)
      9. Generate random regions
      10. Self Organizing Map(SOM)
  4. Articles
    1. Google maps with lots of data, comparison of libs
      1. http://www.svennerberg.com/2009/01/handling-large-amounts-of-markers-in-google-maps/
    2. Thesis
      1. Spatial clustering of structured objects Antonio Varlaro
      2. www.di.uniba.it/~varlaro/Varlaro_PhDThesis.pdf
      3. CORSO
    3. Higher Order Voronoi Diagram
      1. http://gis.stackexchange.com/questions/18330/would-it-be-possible-to-use-geohash-for-proximity-searches
2. Related
  1. Mapping Tech
    1. Projections
    2. Mapping JS
      1. Compare them
      2. http://www.spatialanalysis.ca/2012/alternatives-to-google-maps/
      3. http://geotux.tuxfamily.org/index.php/en/geo-blogs/item/291-comparacion-clientes-web-v6
      4. http://www.smartmapbrowsing.org/html/index_en.html
      5. OpenLayers
      6. The Wary Guide to OpenLayers
      7. http://macwright.org/2012/01/12/openlayers.html
      8. OpenLayers with Canvas
      9. http://trac.osgeo.org/openlayers/wiki/Future/OpenLayersWithCanvas
      10. Leaflet
      11. geojson
      12. http://leaflet.cloudmade.com/examples/geojson.html
      13. https://github.com/CloudMade/Leaflet/issues/13
      14. https://github.com/CloudMade/Leaflet/issues/420
      15. multitouch
      16. https://github.com/CloudMade/Leaflet/issues/150
      17. Modest Maps
      18. polymaps
      19. http://polymaps.org/
      20. SVG-based large-scale data overlays on interactive maps
      21. d3 / Protovis
      22. http://mbostock.github.com/d3/
      23. http://mbostock.github.com/d3/tutorial/protovis.html
      24. D3 + maps
      25. https://groups.google.com/forum/?fromgroups#!topic/d3-js/4CQ7tmpDi-E
      26. basic d3maps integration
      27. https://github.com/bloomtime/d3map
      28. Tile5
      29. http://www.tile5.org/
      30. Canvas
      31. Openlayers heatmap canvas
      32. http://www.websitedev.de/temp/openlayers-heatmap-layer.html
      33. SVG vs Canvas in Openlayers
      34. http://unterbahn.com/2010/07/comparison-of-svg-and-canvas-in-openlayers/
    3. Overlays
      1. SVG vs Canvas
      2. https://groups.google.com/d/msg/d3-js/4CQ7tmpDi-E/0auSzBMu10gJ
      3. Paging Strategy
      4. http://drupal.org/node/1516610#comment-5967508
      5. OpenLayers locator drupal feature
      6. http://drupal.org/project/ol_locator
    4. Basemap Tiles
      1. Ready to go
      2. MapQuest
      3. MapBox
      4. OpenStreetMap
      5. CloudMade
      6. Google, ...
      7. Customize Services
      8. Tile Tools
      9. TileMill
      10. mapquest background tiles
      11. einfach beim embed generieren 'World baselayer' anhaken
      12. http://map.peoplesdistrict.com/fullmap.html
      13. Maperitive
      14. http://maperitive.net/
    5. MapBox
      1. Fast
      2. http://mapbox.com/wax/getting-fast.html
      3. http://www.slideshare.net/devseed/fast-map-interaction-without-flash
      4. Denver Slides
      5. Automatic Updates
    6. More
      1. daten regelmaessig von drupal in sqlite pushen
      2. http://developmentseed.org/blog/2011/sep/28/gains-dynamic-maps-bridging-couchdb-sqlite/
      3. MapProxy
      4. reproject existing tiles
      5. http://mapproxy.org/
    7. Interaction
      1. None
      2. Per-point
      3. Hybrid
      4. UTFGrid
      5. http://mapbox.com/mbtiles-spec/utfgrid/
    8. More
      1. Ushahidi
      2. http://www.ushahidi.com/products/crowdmap
  2. Drupal Mapping
    1. General
      1. Drupal Geo Stack
      2. http://groups.drupal.org/node/138884
      3. http://groups.drupal.org/node/89769
      4. Mapping Book
      5. Mapping
      6. http://drupal.org/project/mapping
      7. http://groups.drupal.org/node/91114
      8. Podcast
      9. http://drupaleasy.com/podcast/2012/01/drupaleasy-podcast-73-lots-options
      10. 05:35; Drupal was one of the first CMS to integrate with Maps
      11. 13:30; TileMill
      12. 19:00; Client-side performance issues & clustering
      13. 24:35; Geocode & center map on users location by using HTML5 Geolocation
      14. 29:53; OpenLayers complexities, CTools, Display using Views, Panels or API
      15. 34:05; OpenLayers related modules: Geofield, Geocoder, ...
      16. 35:20; Geofield in Drupal 7 instead of Location module before
      17. 37:40; Recommended setup - Quickstart for storing locations and displaying them
      18. OpenLayers + Geofield + Addressfield
      19. GMap + Location
      20. 42:10; Leaflet (Cloudmade)
      21. 44:55; Book wrapup
      22. 46:25; Book introduction chapters + Motivation on mapping
      23. 49:25; Popular mapping blogs, cartography, best map of the year
      24. 1:06; Location CCK migrate sandbox
      25. transforms D6 location_cck fields into D7 geofields
      26. 1:07; Geocoder, get geospatial data from address field into geofield
      27. 1:09:20; Baraka samsara films - map site use case
      28. http://barakasamsara.com/
      29. http://stanford.edu/group/ruralwest/cgi-bin/drupal/visualizations/us_newspapers
      30. http://brandonmorrison.com/sites/default/files/presentations-deckjs/drupal-geospatial/index.html
    2. Storage
      1. Geofield
      2. Presentation
      3. http://drupal.org/node/1570972
      4. PostGIS
      5. http://drupal.org/project/postgis
      6. Sync PostGIS
      7. http://drupal.org/project/sync_postgis
    3. Query + Display
      1. OpenLayers
      2. 3.x
      3. http://drupal.org/node/1353122
      4. Polymaps (depends on mapping)
      5. http://drupal.org/project/polymaps
      6. Views GeoJSON
      7. http://drupal.org/project/views_geojson
      8. OL intergration
      9. http://drupal.org/node/1370448
      10. Documentaion, use cases
      11. http://drupal.org/node/1471026
      12. Bounding box filter
      13. http://drupal.org/node/1333324
      14. SOLR
      15. Drupal Apachesolr Geo sandbox
      16. http://drupal.org/sandbox/pwolanin/1497066
      17. Search API Location
      18. http://drupal.org/project/search_api_location
    4. More
      1. http://denver2012.drupal.org/program/sessions/nodejs-javascript-and-future
      2. Drupal Mapping presentation by levelos (overview + openlayers & leaflet focus)
      3. http://www.slideshare.net/loubabe/drupal-mapping-9713919
      4. Drupal Mapping presentation by zzolo 2012
      5. https://github.com/zzolo/spatially-drupal
      6. vector tiles
      7. [2:01pm] friedjoff: dasjo: maybe vector tiles might be worth looking into
      8. [2:01pm] tnightingale: some data doens't make sense to be pushed into drupal
      9. [2:01pm] tnightingale: vector tiles++
      10. [2:02pm] tnightingale: though last i looked, polymaps was the only lib that supported them
      11. tilestash + drupal + leaflet
      12. https://github.com/affinitybridge/drupal-tilestache
      13. https://img.skitch.com/20120426-jfu9fj5c17y5rfa9392y48xmb7.jpg
      14. GeoServer + PostGIS
      15. http://www.geops.de/blog/64-spatial-data-and-drupal-7
      16. Mapping Office hours log
      17. Notes + log
      18. https://docs.google.com/document/d/19F8XCwyxQc4JwouNxDDspiDCjPAWFsVb--xxOyedpmw/edit?pli=1
      19. server-side-clustering
      20. [1:52pm] zzolo: there is still a pretty big hole when trying to map (and handle) lots of geospatial features in Drupal
      21. [1:53pm] phayes: zzolo - I think the answer there is a combination of ViewsGeoJSON / server-side clustering
      22. [1:58pm] dasjo: final question before i have to leave: do we need a server-side clustering like nod_ and me discussed? http://drupal.org/node/1547610
      23. [1:59pm] nod_: dasjo: phayes seems to agree, see backscroll
      24. [1:59pm] Brandonian: dasjo: Definitlely think it'd be a cool feature, not sure what other work is being done with that in php/drupal land though
      25. [2:00pm] zzolo: dasjo: my initial thought is no, if we can focus on toolking up thinks like postgis and tilestache. but since that is not really going to happen overnight, a good stop gap solon could be server side clustering
      26. [2:00pm] phayes: dasjo: Yes we need it! That's going to be critical as we scale to support larger data sets
      27. [2:00pm] dasjo: yep Brandonian zzolo. basically some parts of the database implementation and client-side handling should be pluggable
      28. [2:01pm] dasjo: but maybe we can come with some basic out-of-the-box implementations and leave it open to a database to optimize the clustering
      29. tilestash + drupal + leaflet
      30. log
      31. [1:59pm] tnightingale: yeah - tilestache is (using mapnik) is able to generate tiles on demand from a postgis backend
      32. [1:59pm] mackh: of data from the oil and gas commksion - like pipeline right-of-ways, access roads, wellsites, watercrossings
      33. [2:00pm] tnightingale: zzolo: so we can sync drupal data into postgis and render that data into tiles using mapnik+tilestache
      34. [2:00pm] zzolo: tnightingale: and mackh just to confirm, the postgi data is drupal data? (from sync_postgis, i assume)
      35. [2:00pm] zzolo: sweet
      36. [2:00pm] mackh: yes and no?
      37. [2:00pm] tnightingale: yep
      38. [2:01pm] mackh: stored in drupal, synced to postgis
      39. [2:01pm] tnightingale: but doesn't have to be
      40. [2:01pm] zzolo: awesome. thats what i was hoping. this is the stack i have been envisioning, but i don't get paid to do any of this stuff so i don't have time.
      41. [2:02pm] Brandonian: for the more python/mapnik literate in the room: How feasible is it to do mapnik renders based directly off drupal field data if the database is Postgres/postgis and stored properly?
      42. [2:02pm] tnightingale: Brandonian: that's essentially what we're doing with sync_postgis & tilestache
      43. [2:03pm] zzolo: Brandonian: what i image is getting your design in tile mill, export out the mapnik xml file, then it should be pretty easy
      44. [2:03pm] tnightingale: using a mapnik xml file produced in tilemill as our style guide
      45. [2:06pm] tnightingale: zzolo: we also have a rough cut at a tilestache config management module on g.h
      46. [2:06pm] phayes: ooo! link tnightingale?
      47. [2:07pm] phayes: Oh tnightingale, what's the status of D7 Spatial-tools?
      48. [2:07pm] zzolo: tnightingale: you have a link. i am actually gonna try to get this stack running locally this week as part of my presentation at the TC Drupal camp
      49. [2:07pm] mackh: https://github.com/affinitybridge/drupal-tilestache]
      50. [2:07pm] zzolo: i think this is definitely the future of geo
      51. [2:07pm] tnightingale: re: tilestache module - still pretty rough, be warned
      52. [2:08pm] zzolo: and i think postgis sync is the way to go to handle goespatial data and spatial querying.
      53. https://github.com/affinitybridge/drupal-tilestache
      54. https://img.skitch.com/20120426-jfu9fj5c17y5rfa9392y48xmb7.jpg
      55. search api
      56. [2:08pm] mackh: i also want to extend search api to return WKT onto maps
      57. [2:08pm] mackh: from faceted results, hoping to get that client funded in the next 3 months
      58. Office hours finishing
      59. log
      60. [2:07pm] tom_o_t: Brandonian: perhaps schedule dedicated Q&A time for stuff general questions that aren't related to module development?
      61. [2:08pm] Brandonian: tom_o_t: Not a bad idea.
      62. [2:09pm] jeffschuler: tom_o_t++ … this has been super useful, but It's been more of a facilitated discussion on high-level geo in drupal topics rather than a time for folks to come get help or figure out how they can pitch in… different from core office hours http://drupal.org/node/1242856
      63. Use Case
      64. Online-Biodiversitätsportale mit Indicia, Drupal und OpenLayers
      65. http://www.fossgis.de/konferenz/2011/programm/events/239.en.html
      66. CivicApps
      67. http://civicapps.org/
      68. OpenPublic Map Visualization Feature
      69. http://www.openpublicapp.com/map-visualization-feature
      70. broken?
      71. Geofield proximity updates by brandonian
      72. http://drupal.org/node/1469956#comment-6025452
      73. http://en.wikipedia.org/wiki/Haversine_formula
  3. Database
    1. MySQL Spatial
      1. http://dev.mysql.com/doc/refman/5.0/en/spatial-extensions.html
    2. PostGIS PostreSQL
      1. http://postgis.org/
    3. SOLR
      1. MetaCarta - GeoSearch Toolkit for Solr (prorietary)
      2. http://www.metacarta.com/products-overview.htm
  4. Logic
    1. GEOS
      1. https://github.com/phayes/geoPHP/wiki/GEOS
  5. Steps
    1. Cluster center
      1. http://www.biomedware.com/files/documentation/boundaryseer/Wombling/Irregular_(point)_wombling.htm
      2. http://www.biomedware.com/files/documentation/boundaryseer/Wombling/Raster_wombling.htm#wombling_equations
  6. More
    1. Open
      1. Interactive Map Visualization Techniques for Open Data in Austria with Drupal
      2. Open Data
      3. Open Data Handbook
      4. http://blog.okfn.org/2012/02/22/announcing-the-open-data-handbook-version-1-0/
      5. Berlin Open Data Strategy
      6. http://www.scribd.com/doc/83193044/Berlin-Open-Data-Strategy-English-Abstract
      7. Open Data in Austria
      8. Open3 - Netzwerk zur Förderung von OpenSociety, OpenGov und OpenData in Österreich
      9. http://www.open3.at
      10. Datenplattformen Österreichs
      11. http://data.linz.gv.at/
      12. http://data.wien.gv.at/
      13. Open Data Visualization
      14. visualization of time-oriented data (buch)
      15. http://visweek.org/visweek/2011/paper-session/all/infovis
      16. Open Data Visualization in Austria
      17. Open Data & Data Driven Journalism - Tools & Best Practices (Robert Harm)
      18. http://www.slideshare.net/robertharm/open-data-data-driven-journalism-tools-best-practices
      19. Open Data Mapping
      20. geocommons
      21. http://geocommons.com/
      22. degree confluence
      23. http://www.confluence.org/
      24. Open Data Mapping in Austria
      25. Geo-Datenplattformen Österreichs
      26. http://data.linz.gv.at/daten/Geodaten
      27. http://data.wien.gv.at/katalog/basiskarten
      28. http://www.kartenwerkstatt.at
      29. AustroFeedr - Drupal + OpenLayers Use Case
      30. http://www.austrofeedr.at
      31. http://demo.austrofeedr.at
      32. Linked Open Data Austria - Drupal + OpenLayers
      33. http://austria.drupaldata.com
      34. Linked Open Geodata Meetup
      35. http://www.meetup.com/Vienna-Semantic-Web-Meetup/events/23088111/
      36. geoland.at
      37. http://www.slideshare.net/langegger/linked-open-geodata
    2. Web Mapping
      1. http://en.wikipedia.org/wiki/Web_mapping
      2. Classification
      3. static vs dynamic
      4. http://kartoweb.itc.nl/webcartography/webmaps/classification.htm
      5. http://en.wikipedia.org/wiki/Geosocial_networking
      6. Collaborative mapping
      7. http://en.wikipedia.org/wiki/Collaborative_mapping
      8. OpenStreetMap
      9. Google Map Maker
      10. Licensing
      11. http://mashable.com/2012/01/19/google-maps-world-bank/
      12. Wikimapia
      13. http://wikimapia.org/
      14. Österreich
      15. Gomogi
      16. http://www.gomogi.com/
      17. micheal diener
      18. FOSSGIS UG AT
      19. fossgis@spektral.at
      20. http://wiki.alpine-geckos.at/wiki/FOSSGIS_UserGroup_Austria
      21. http://www.alpine-geckos.at/category/geowissenschaften/
    3. Animation
      1. Examples
      2. Windhistory
      3. http://windhistory.com/map.html#9.00/40.1737/-113.1458
    4. People
      1. Underdark GIS
3. Implementations
  1. Solr clustering
    1. http://stackoverflow.com/questions/8399152/how-to-best-do-server-side-geo-clustering
    2. Outdated localsolr
      1. https://issues.apache.org/jira/browse/SOLR-773
    3. Implementierung
      1. http://blog.sybit.de/2010/11/geografische-suche-mit-solr/
    4. Good discussion
      1. http://www.mail-archive.com/solr-user@lucene.apache.org/msg40651.html
  2. clusterPy
    1. http://code.google.com/p/clusterpy/
    2. http://www.rise-group.org/risem/clusterpy/index.html
  3. Google maps Perl impl + discussion
    1. http://flylib.com/books/en/2.367.1.102/1/
    2. siehe auch downloaded chm ebook
    3. K-mean
      1. Method
      2. 1. Select a center point for each of k clusters, where k is a small integer.
      3. 2. Assign each data point to the cluster whose center point is closest.
      4. 3. After all the data points are assigned, move each cluster's center point to the arithmetic mean of the coordinates of all the points in that cluster, treating each dimension separately.
      5. 4. Repeat from Step 2, until the center points stop moving.
    4. Hierachical clustering
      1. Method
      2. 1. Assign each point to its own cluster.
      3. 2. Calculate the distance from each cluster to every other cluster, either from their respective mean centers, or from the two nearest points from each cluster.
      4. 3. Take the two closest clusters and combine them into one cluster.
      5. 4. Repeat from Step 2, until you have the right number of clusters, or the clusters are some minimum distance apart from each other, or until you have one big cluster.
    5. Naïve grid-based clustering
      1. grid by display pixels / marker size
      2. assign points to clusters within grid
      3. order clusters by points
      4. make superclusters (heavy clusters claim their neighbors)
  4. Vizmo
    1. Hierarchical Clustering by Meaningful Units
    2. PHP, Symphony2, closed source?
    3. www.globalimpactstudy.org/wp-content/uploads/.../vizmo-poster.pdf
    4. http://www.globalimpactstudy.org/2011/12/open-source-presentation/
  5. Google MarkerClustering
    1. http://code.google.com/p/google-maps-utility-library-v3/wiki/Libraries#MarkerClusterer
    2. http://googlegeodevelopers.blogspot.com/2009/04/markerclusterer-solution-to-too-many.html
    3. http://google-maps-utility-library-v3.googlecode.com/svn/trunk/markerclusterer/docs/reference.html
  6. Google maps php example
    1. Google maps haversine php example
    2. https://github.com/tuupola/php_google_maps/tree
    3. http://www.appelsiini.net/projects/php_google_maps/cluster.html?center=17.41075008,85.46194978&infowindow=&zoom=1
    4. http://www.appelsiini.net/2008/11/introduction-to-marker-clustering-with-google-maps
  7. PHp example
    1. http://web.archive.org/web/20071011143643/http://forum.sydphp.org/?a=topic&t=1074
    2. request
      1. http://uwmike.com/maps/dams/index.php.source
      2. http://uwmike.com/maps/dams/map_functions.js.source
      3. http://uwmike.com/maps/dams/map_data.php.source
      4. http://uwmike.com/maps/dams/style.css.source
    3. prep
      1. http://uwmike.com/maps/dams/data/dams_au.txt.source
      2. http://uwmike.com/maps/dams/data/create_inserts.php.source
      3. http://uwmike.com/maps/dams/data/create_clusters.php.source
  8. More
    1. PostGIS
      1. http://postgis.refractions.net/pipermail/postgis-users/2006-March/011431.html
    2. R-Project
      1. SGCS
      2. Spatial Graph based Clustering Summaries for spatial point patterns
      3. http://www.inside-r.org/packages/sgcs
      4. http://cran.r-project.org/web/packages/SGCS/
    3. Flex
      1. http://thunderheadxpler.blogspot.co.at/2008/12/clustering-20k-map-points.html
  9. Openlayers (client side)
    1. http://dev.openlayers.org/releases/OpenLayers-2.11/lib/OpenLayers/Strategy/Cluster.js
  10. Drupal 6 github
    1. https://github.com/ahtih/Geoclustering
    2. beschreibung
      1. * source data (points) is in the form of Drupal nodes
      2. * a new Drupal module maintains a DB table of multi-level geographic clusters, using hook_nodeapi() to track changes to source nodes and update the clusters table accordingly. Clusters table is accessible via a Views plugin
      3. * WFS module accesses clusters view and serves out both clusters and source nodes, with clustering level and bbox as request parameters
      4. * a new OpenLayers Strategy or layer type displays the map, selecting a suitable clustering level based on zoom and/or number of points in map view area
      5. http://drupal.org/node/622720#comment-3239286
      6. http://www.letsdoitworld.org/wastemap
  11. Geohash
    1. http://en.wikipedia.org/wiki/Geohash
    2. good presenation
      1. http://www.lucidimagination.com/sites/default/files/Lucene%20Rev%20Preso%20Smiley%20Spatial%20Search.pdf
    3. geohash explanation demo
      1. http://openlocation.org/geohash/geohash-js/
    4. SOLR-2155
      1. edge n-gram'ed geohashes with a PrefixTree/Trie search algorithm
      2. https://github.com/dsmiley/SOLR-2155
      3. http://wiki.apache.org/solr/SpatialSearch#SOLR-2155
    5. SOLR
      1. http://lucene.apache.org/core/3_6_0/api/contrib-spatial/index.html?org/apache/lucene/spatial/geohash/GeoHashDistanceFilter.html
      2. https://issues.apache.org/jira/browse/SOLR-2155
      3. A new geospatial framework for Lucene and Solr
      4. https://github.com/spatial4j/spatial4j
    6. MongoDB
      1. http://www.mongodb.org/display/DOCS/Geospatial+Indexing
    7. PHP additional hilbert-curve
      1. http://www.phpclasses.org/package/6202-PHP-Generate-points-of-an-Hilbert-curve.html
      2. http://stackoverflow.com/a/9645315
    8. geoPHP integration
      1. https://github.com/phayes/geoPHP/issues/32
  12. Geohash with Drupal
    1. Geospatial searching with solr 3.x
      1. http://drupal.org/node/1187888
    2. Apachesolr geo sandbox
      1. http://drupal.org/sandbox/pwolanin/1497066
4. Libraries / Vendors
  1. http://www.maptimize.com/
    1. Maptimize can deal with up to 50,000 markers - but the underlying algorithm can handle over one million!
    2. http://v2.maptimize.com/faq#
    3. http://seb.box.re/2009/5/1/maps-geolocalization-and-optimization-with-maptimize
5. Comparison, state of the art
Use cases
1. GeoRecruiter
Conception
1. Geocluster
  1. geocluster_views_post_execute
    1. not very flexible, prefer to do plugins
  2. views_plugin_style_geocluster extends views_plugin_style_geojson
    1. views_geojson has complicated _views_geojson_render_fields
  3. geocluster_plugin_style_geofield_map extends geofield_map_plugin_style_map
    1. fields already rendered by field handler post execute
  4. geocluster_handler_field_geofield extends geofield_handler_field
  5. ähnlich wie groupby, get_aggregation_info ?
  6. display that uses another display
    1. datenquelle = andere view
    2. Subtopic 2
  7. queryhandler clustering
Implementation
1. GeoRecruiter
  1. Daten
    1. GeoTaxonomie verwenden / geofield
      1. jobs
      2. bezirke
  2. Suche
    1. Search API integration
      1. http://drupal.org/project/search_api_location
  3. Job
    1. Job location auf karte anzeigen
  4. Mapping & Recruiter
    1. http://drupal.org/node/1254716
    2. by Adam S, based on OpenPublic