This is a CouchApp providing spatial functions and a set of helper scripts for GeoCouch. You can find the CouchApp in the couchapp/ directory. For instructions on using GeoCouch, see the GeoCouch Readme

Replicate this CouchApp from @maxogden's public couch to your database:

curl -X POST http://YOURCOUCH/_replicate -d '{"source":"http://max.couchone.com/apps","target":"http://YOURCOUCH/DBNAME", "doc_ids":["_design/geo"]}'

If you wish to modify the functions in this repo before you use them, you can clone and push using the couchapp utility. Otherwise see the Quick install section above.

First you'll need to install the CouchApp command line utility.

A specific document structure is used consistently within all utilities and examples, assuming that location information is provided in doc.geometry containing a valid GeoJSON struct. If your document structure differs, don't forget to adapt the (spatial) views.

// add a document with a valid geometry into your database
$ curl -X PUT http://localhost:5984/DBNAME/myfeature -d '{"type":"Feature", "color":"orange" ,"geometry":{"type":"Point","coordinates":[11.395,48.949444]}}'
{"ok":true,"id":"myfeature","rev":"1-2eeb1e5eee6c8e7507b671aa7d5b0654"}

You can either replicate the couchapp from my public couch at http://max.couchone.com/apps/_design/geo (quickest option) or, if you want to hack on the source code first, you'll need to install the CouchApp command line utility and check out this repo.

If you want to hack on the code (aka build it yourself), once you have the couchapp utility working, git clone this repo and go into this folder and execute couchapp init. To upload these utils into your couch just run couchapp push http://YOURCOUCH/DATABASENAME. Otherwise see the Quick install section above.

This relies on https://github.com/maxogden/geojson-js-utils Make sure you also clone the submodules. This can be done simply with these git commands: git submodule init git submodule update

When you push these utils into your couch it will enhance your database with the magical geo sprinkles contained in this repo and teach your database how to do awesome things with geo data. At this point you can use the following commands:

The document structure is used consistently within all views and examples, assuming that location information is provided in doc.geometry containing a GeoJSON struct. If your document structure differs, don't forget to adapt the (spatial) views.

Example:

{
   "_id": "c0c048ad2770bb836a10f164cc0a3fc0",
   "_rev": "1-e2d2130da93ca435965d6d3efca22380",
   "geometry": {
       "type": "Point",
       "coordinates": [
           48.417,
           9.983
       ]
   },
   "etc" : "..."
}

A spatial view that additionally emits the original GeoJSON value (doc.geometry)

Example:

$ curl 'http://localhost:5984/yourdb/_design/geo/_spatial/points?bbox=80,88,90,90'
{
   "update_seq":203,
   "rows":[
      {
         "id":"c0c048ad2770bb836a10f164cc08a3e5",
         "bbox":[
            81.0876957164146,
            89.14168435614556,
            81.0876957164146,
            89.14168435614556
         ],
         "value":{
            "id":"c0c048ad2770bb836a10f164cc08a3e5",
            "geometry":{
               "type":"Point",
               "coordinates":[
                  81.0876957164146,
                  89.14168435614556
               ]
            }
         }
      }
   ]
}

A spatial view that emits both GeoJSON and the full document (as value).

Example:

$ curl 'http://localhost:5984/yourdb/_design/geo/_spatial/pointsFull?bbox=80,88,90,90'	
{
   "update_seq":203,
   "rows":[
      {
         "id":"c0c048ad2770bb836a10f164cc08a3e5",
         "bbox":[
            81.0876957164146,
            89.14168435614556,
            81.0876957164146,
            89.14168435614556
         ],
         "value":{
            "_id":"c0c048ad2770bb836a10f164cc08a3e5",
            "_rev":"1-0e087449742a73b5ce0df1415b1af3f3",
            "geometry":{
               "type":"Point",
               "coordinates":[
                  81.0876957164146,
                  89.14168435614556
               ]
            }
         }
      }
   ]
}

A spatial view that only emits GeoJSON and no additional value.

Example:

$ curl 'http://localhost:5984/yourdb/_design/geo/_spatial/pointsOnly?bbox=80,88,90,90'	
{
   "update_seq":203,
   "rows":[
      {
         "id":"c0c048ad2770bb836a10f164cc08a3e5",
         "bbox":[
            81.0876957164146,
            89.14168435614556,
            81.0876957164146,
            89.14168435614556
         ],
         "value":null
      }
   ]
}

A simple map function that returns all documents. It's like _all_docs, but you can use it as a regular view.

This list function generates a simple KML feed

Example:

$ curl http://localhost:5984/yourdb/_design/geo/_spatiallist/kml/points?bbox=0,0,45,45

<?xml version="1.0" encoding="UTF-8"?>
<kml xmlns="http://www.opengis.net/kml/2.2">
<Document>
<name>GeoCouch Result - KML Feed</name>      
<Placemark>
  <name>b7f31f5062745b6ca1c1adfc0c2351a1</name>
  <Point><coordinates>-122.676375038274,45.5233877497394,0</coordinates></Point>
</Placemark>
</Document>
</kml>

This function outputs a GeoJSON FeatureCollection (compatible with OpenLayers).

Example:

$curl -X GET 'http://localhost:5984/yourdb/_design/geo/_spatiallist/geojson/points?bbox=80,88,90,90'	
{
   "type":"FeatureCollection",
   "features":[
      {
         "type":"Feature",
         "geometry":{
            "type":"Point",
            "coordinates":[
               81.0876957164146,
               89.14168435614556
            ]
         },
         "properties":{
            "id":"c0c048ad2770bb836a10f164cc08a3e5"
         }
      }
   ]
}

This will take the centroid of the bbox parameter and a supplied radius parameter in meters and filter the rectangularly shaped bounding box result set by circular radius.

WARNING This only works with on points, not lines or polygons yet

Example:

$ curl -X GET http://localhost:5984/yourdb/_design/geo/_spatiallist/radius/points?bbox=-122.67,45.52,-122.67,45.52&radius=50
{
   "type":"FeatureCollection",
   "features":[
      {
	 "type":"Feature",
	 "geometry":{
	    "coordinates":[
	       -122.676375038274,
	       45.5233877497394
	    ],
	    "type":"Point"
	 },
	 "properties":{
	    "id":"b7f31f5062745b6ca1c1adfc0c2351a1"
	 }
      }
   ]
}

This groups points into clusters based on proximity. You can supply a threshold (distance in km) which detrimines how much area each cluster covers.

Some code inspiration from Marker Clusterer - found here: http://code.google.com/p/gmaps-utility-library/

WARNING This only works with on points, not lines or polygons (not sure how that would be useful yet)

Example: $ curl -X GET 'http://localhost:5984/mydb/_design/geo/_spatiallist/cluster/points?bbox=-122.677,45.523,-122.675,45.524&threshold=50' {"rows": [{ "center": { "type": "Point", "coordinates": [ 41.35646666666667, 1.6144666666666663 ] }, "points": [{ "id": "20132885373657090", "geometry": { "type": "Point", "coordinates": [ 41.3401, 1.3596 ] } }, { "id": "20138805986066430", "geometry": { "type": "Point", "coordinates": [ 41.3493, 1.3631 ] } }], "size": 2 }]}

In the folder misc you can find helpful scripts or snippets for GeoCouch.

This node.js script can be handy for generating test data. It creates random documents within given value ranges. The script expects the following parameters:

• The URI of the database to fill
• A bounding box of the area to fill (as bbox JSON array)
• The number of documents to generate

Example call:

node geocouch-filler.js http://localhost:5984/yourdb [-180,-90,180,90] 1000

This will create 1000 documents with random locations spread over the whole world.

Licensed under the MIT License.