GeoDjango Model API

This document explores the details of the GeoDjango Model API. Throughout this section, we’ll be using the following geographic model of a ZIP code as our example:

from django.contrib.gis.db import models

class Zipcode(models.Model):
    code = models.CharField(max_length=5)
    poly = models.PolygonField()
    objects = models.GeoManager()

Geometry Field Types

The following geometry fields are available:

• PointField
• LineStringField
• PolygonField
• MultiPointField
• MultiLineStringField
• MultiPolygonField
• GeometryCollectionField

Each of these fields correspond with OpenGIS Simple Features [1].

Geometry Field Options

In addition to the regular field options available for Django model fields, geometry fields have the following additional options:

Argument	Description
srid	Sets the SRID [2] (Spatial Reference System Identity) of the geometry field to the given value. Defaults to 4326 (also known as WGS84, units are in degrees of longitude and latitude).
spatial_index	Defaults to True. Creates a spatial index for the given geometry. Please note that this is different from the db_index field option because spatial indexes are created in a different manner than regular database indexes.

Selecting an SRID

Choosing an appropriate SRID for your model is an important decision that the develper should consider carefully. The SRID is an integer specifier that corresponds to the projection system that will be used to interpret the data in the spatial database. [3] Projection systems give the context to the coordinates that specify a location. Although the details of geodesy are beyond the scope of this documentation, the general problem is that the earth is spherical and representations of the earth (e.g., paper maps, web maps) are not.

Most people are familiar with using latitude and longitude to reference a location on the earth’s surface. However, latitude and longitude are angles, not distances. [4] In other words, while the shortest between two points on a flat surface is a line, the shortest distance between two points on a curved surface (such as the earth) is an arc of a great circle. [5] Thus, additional computation is required to obtain distances in planar units (e.g., kilometers and miles). Using a geographic coordinate system may introduce complications for the developer later on. For example, PostGIS does not have the capability to perform distance calculations between non-point geometries using geographic coordinate systems, e.g., constructing a query to find all points within 5 miles of a county boundary stored as WGS84. [6]

Portions of the earth’s surface may projected onto a two-dimensional, or cartesian, plane. Projected coordinate systems are especially convenient for region-specific applications, e.g., if you know that your database will only cover geometries in North Kansas, then you may consider using projection system specific to that region. Moreover, projected coordinate systems are defined in cartesian units (such as meters or feet), easing distance calculations.

Additional Resources:

• spatialreference.org: A Django-powered database of spatial reference systems.
• The State Plane Coordinate System: A website covering the various projection systems used in the United States. Much of the U.S. spatial data encountered will be in one of these coordinate systems rather than in a geographic coordinate system such as WGS84.

GeoManager

In order to conduct geographic queries, each geographic model requires a GeoManager model manager. This manager allows for the proper SQL construction for geographic queries; thus, without it, all geographic filters will fail. It should also be noted that GeoManager is required even if the model does not have a geographic field itself, i.e., in the case of a ForeignKey relation to a model with a geographic field. For example, if we had an Address model with a ForeignKey to our Zipcode model:

from django.contrib.gis.db import models

class Address(models.Model):
    num = models.IntegerField()
    street = models.CharField(max_length=100)
    city = models.CharField(max_length=100)
    state = models.USStateField()
    zipcode = models.ForeignKey(Zipcode)
    objects = models.GeoManager()

The geographic manager is needed to do spatial queries on related Zipcode objects, for example:

qs = Address.objects.filter(zipcode__poly__contains='POINT(-104.590948 38.319914)')

Footnotes

[1]	OpenGIS Consortium, Inc., Simple Feature Specification For SQL, Document 99-049 (May 5, 1999).

[2]	See id. at Ch. 2.3.8, p. 39 (Geometry Values and Spatial Reference Systems).

[3]	Typically, SRID integer corresponds to an EPSG (European Petroleum Survey Group) identifier. However, it may also be associated with custom projections defined in spatial database’s spatial refereyce systems table.

[4]	Harvard Graduate School of Design, An Overview of Geodesy and Geographic Referencing Systems. This is an excellent resource for an overview of principles relating to geographic and cartesian coordinate systems.

[5]	Terry A. Slocum, Robert B. McMaster, Fritz C. Kessler, & Hugh H. Howard, Thematic Cartography and Geographic Visualization (Prentice Hall, 2nd edition), at Ch. 7.1.3.

[6]	This isn’t impossible using GeoDjango; you could for example, take a known point in a projected coordinate system, buffer it to the appropriate radius, and then peform an intersection operation with the buffer transformed to the geographic coordinate system.