A node.js wrapper of Geohash Javascript Demonstration. geohash-js (c) 2008 David Troy

Refactored by Jose A. Villarreal (c) 2013. Realesed under the MIT License

The Geohash algorithm was first described by Gustavo Niemeyer in February 2008. By interleaving latitude and longitude information in a bitwise fashion, a composite value is generated that provides a high resolution geographic point, and is well suited for storage or transmission as a character string.

Geohash also has the property that as the number of digits decreases (from the right), accuracy degrades. This property can be used to do bounding box searches, as points near to one another will share similar Geohash prefixes.

However, because a given point may appear at the edge of a given Geohash bounding box, it is necessary to generate a list of Geohash values in order to perform a true proximity search around a point. Because the Geohash algorithm uses a base-32 numbering system, it is possible to derive the Geohash values surrounding any other given Geohash value using a simple lookup table.

So, for example, 1600 Pennsylvania Avenue, Washington DC resolves to: 38.897, -77.036

Using the geohash algorithm, this latitude and longitude is converted to: dqcjqcp84c6e

A simple bounding box around this point could be described by truncating this geohash to: dqcjqc

However, 'dqcjqcp84c6e' is not centered inside 'dqcjqc', and searching within 'dqcjqc' may miss some desired targets.

So instead, we can use the mathematical properties of the Geohash to quickly calculate the neighbors of 'dqcjqc'; we find that they are: 'dqcjqf','dqcjqb','dqcjr1','dqcjq9','dqcjqd','dqcjr4','dqcjr0','dqcjq8'

This gives us a bounding box around 'dqcjqcp84c6e' roughly 2km x 1.5km and allows for a database search on just 9 keys: SELECT * FROM table WHERE LEFT(geohash,6) IN ('dqcjqc', 'dqcjqf','dqcjqb','dqcjr1','dqcjq9','dqcjqd','dqcjr4','dqcjr0','dqcjq8');

GeoHash on Wikipedia (http://en.wikipedia.org/wiki/Geohash)