GIS QuerySet API Reference¶
Spatial Lookups¶
The spatial lookups in this section are available for GeometryField
and RasterField
.
For an introduction, see the spatial lookups introduction. For an overview of what lookups are compatible with a particular spatial backend, refer to the spatial lookup compatibility table.
Lookups with rasters¶
All examples in the reference below are given for geometry fields and inputs, but the lookups can be used the same way with rasters on both sides. Whenever a lookup doesn’t support raster input, the input is automatically converted to a geometry where necessary using the ST_Polygon function. See also the introduction to raster lookups.
The database operators used by the lookups can be divided into three categories:
 Native raster support
N
: the operator accepts rasters natively on both sides of the lookup, and raster input can be mixed with geometry inputs.  Bilateral raster support
B
: the operator supports rasters only if both sides of the lookup receive raster inputs. Raster data is automatically converted to geometries for mixed lookups.  Geometry conversion support
C
. The lookup does not have native raster support, all raster data is automatically converted to geometries.
The examples below show the SQL equivalent for the lookups in the different types of raster support. The same pattern applies to all spatial lookups.
Case  Lookup  SQL Equivalent 

N, B  rast__contains=rst 
ST_Contains(rast, rst) 
N, B  rast__1__contains=(rst, 2) 
ST_Contains(rast, 1, rst, 2) 
B, C  rast__contains=geom 
ST_Contains(ST_Polygon(rast), geom) 
B, C  rast__1__contains=geom 
ST_Contains(ST_Polygon(rast, 1), geom) 
B, C  poly__contains=rst 
ST_Contains(poly, ST_Polygon(rst)) 
B, C  poly__contains=(rst, 1) 
ST_Contains(poly, ST_Polygon(rst, 1)) 
C  rast__crosses=rst 
ST_Crosses(ST_Polygon(rast), ST_Polygon(rst)) 
C  rast__1__crosses=(rst, 2) 
ST_Crosses(ST_Polygon(rast, 1), ST_Polygon(rst, 2)) 
C  rast__crosses=geom 
ST_Crosses(ST_Polygon(rast), geom) 
C  poly__crosses=rst 
ST_Crosses(poly, ST_Polygon(rst)) 
Spatial lookups with rasters are only supported for PostGIS backends (denominated as PGRaster in this section).
bbcontains
¶
Availability: PostGIS, MySQL, SpatiaLite, PGRaster (Native)
Tests if the geometry or raster field’s bounding box completely contains the lookup geometry’s bounding box.
Example:
Zipcode.objects.filter(poly__bbcontains=geom)
Backend  SQL Equivalent 

PostGIS  poly ~ geom 
MySQL  MBRContains(poly, geom) 
SpatiaLite  MbrContains(poly, geom) 
bboverlaps
¶
Availability: PostGIS, MySQL, SpatiaLite, PGRaster (Native)
Tests if the geometry field’s bounding box overlaps the lookup geometry’s bounding box.
Example:
Zipcode.objects.filter(poly__bboverlaps=geom)
Backend  SQL Equivalent 

PostGIS  poly && geom 
MySQL  MBROverlaps(poly, geom) 
SpatiaLite  MbrOverlaps(poly, geom) 
contained
¶
Availability: PostGIS, MySQL, SpatiaLite, PGRaster (Native)
Tests if the geometry field’s bounding box is completely contained by the lookup geometry’s bounding box.
Example:
Zipcode.objects.filter(poly__contained=geom)
Backend  SQL Equivalent 

PostGIS  poly @ geom 
MySQL  MBRWithin(poly, geom) 
SpatiaLite  MbrWithin(poly, geom) 
contains
¶
Availability: PostGIS, Oracle, MySQL, SpatiaLite, PGRaster (Bilateral)
Tests if the geometry field spatially contains the lookup geometry.
Example:
Zipcode.objects.filter(poly__contains=geom)
Backend  SQL Equivalent 

PostGIS  ST_Contains(poly, geom) 
Oracle  SDO_CONTAINS(poly, geom) 
MySQL  MBRContains(poly, geom) 
SpatiaLite  Contains(poly, geom) 
contains_properly
¶
Availability: PostGIS, PGRaster (Bilateral)
Returns true if the lookup geometry intersects the interior of the geometry field, but not the boundary (or exterior).
Example:
Zipcode.objects.filter(poly__contains_properly=geom)
Backend  SQL Equivalent 

PostGIS  ST_ContainsProperly(poly, geom) 
coveredby
¶
Availability: PostGIS, Oracle, PGRaster (Bilateral)
Tests if no point in the geometry field is outside the lookup geometry. [3]
Example:
Zipcode.objects.filter(poly__coveredby=geom)
Backend  SQL Equivalent 

PostGIS  ST_CoveredBy(poly, geom) 
Oracle  SDO_COVEREDBY(poly, geom) 
covers
¶
Availability: PostGIS, Oracle, PGRaster (Bilateral)
Tests if no point in the lookup geometry is outside the geometry field. [3]
Example:
Zipcode.objects.filter(poly__covers=geom)
Backend  SQL Equivalent 

PostGIS  ST_Covers(poly, geom) 
Oracle  SDO_COVERS(poly, geom) 
crosses
¶
Availability: PostGIS, SpatiaLite, PGRaster (Conversion)
Tests if the geometry field spatially crosses the lookup geometry.
Example:
Zipcode.objects.filter(poly__crosses=geom)
Backend  SQL Equivalent 

PostGIS  ST_Crosses(poly, geom) 
SpatiaLite  Crosses(poly, geom) 
disjoint
¶
Availability: PostGIS, Oracle, MySQL, SpatiaLite, PGRaster (Bilateral)
Tests if the geometry field is spatially disjoint from the lookup geometry.
Example:
Zipcode.objects.filter(poly__disjoint=geom)
Backend  SQL Equivalent 

PostGIS  ST_Disjoint(poly, geom) 
Oracle  SDO_GEOM.RELATE(poly, 'DISJOINT', geom, 0.05) 
MySQL  MBRDisjoint(poly, geom) 
SpatiaLite  Disjoint(poly, geom) 
intersects
¶
Availability: PostGIS, Oracle, MySQL, SpatiaLite, PGRaster (Bilateral)
Tests if the geometry field spatially intersects the lookup geometry.
Example:
Zipcode.objects.filter(poly__intersects=geom)
Backend  SQL Equivalent 

PostGIS  ST_Intersects(poly, geom) 
Oracle  SDO_OVERLAPBDYINTERSECT(poly, geom) 
MySQL  MBRIntersects(poly, geom) 
SpatiaLite  Intersects(poly, geom) 
isvalid
¶
Availability: MySQL (≥ 5.7.5), PostGIS, Oracle, SpatiaLite
Tests if the geometry is valid.
Example:
Zipcode.objects.filter(poly__isvalid=True)
Backend  SQL Equivalent 

MySQL, PostGIS, SpatiaLite  ST_IsValid(poly) 
Oracle  SDO_GEOM.VALIDATE_GEOMETRY_WITH_CONTEXT(poly, 0.05) = 'TRUE' 
MySQL support was added.
relate
¶
Availability: PostGIS, Oracle, SpatiaLite, PGRaster (Conversion)
Tests if the geometry field is spatially related to the lookup geometry by
the values given in the given pattern. This lookup requires a tuple parameter,
(geom, pattern)
; the form of pattern
will depend on the spatial backend:
PostGIS & SpatiaLite¶
On these spatial backends the intersection pattern is a string comprising
nine characters, which define intersections between the interior, boundary,
and exterior of the geometry field and the lookup geometry.
The intersection pattern matrix may only use the following characters:
1
, 2
, T
, F
, or *
. This lookup type allows users to “fine tune”
a specific geometric relationship consistent with the DE9IM model. [1]
Geometry example:
# A tuple lookup parameter is used to specify the geometry and
# the intersection pattern (the pattern here is for 'contains').
Zipcode.objects.filter(poly__relate=(geom, 'T*T***FF*'))
PostGIS SQL equivalent:
SELECT ... WHERE ST_Relate(poly, geom, 'T*T***FF*')
SpatiaLite SQL equivalent:
SELECT ... WHERE Relate(poly, geom, 'T*T***FF*')
Raster example:
Zipcode.objects.filter(poly__relate=(rast, 1, 'T*T***FF*'))
Zipcode.objects.filter(rast__2__relate=(rast, 1, 'T*T***FF*'))
PostGIS SQL equivalent:
SELECT ... WHERE ST_Relate(poly, ST_Polygon(rast, 1), 'T*T***FF*')
SELECT ... WHERE ST_Relate(ST_Polygon(rast, 2), ST_Polygon(rast, 1), 'T*T***FF*')
Oracle¶
Here the relation pattern is comprised of at least one of the nine relation
strings: TOUCH
, OVERLAPBDYDISJOINT
, OVERLAPBDYINTERSECT
,
EQUAL
, INSIDE
, COVEREDBY
, CONTAINS
, COVERS
, ON
, and
ANYINTERACT
. Multiple strings may be combined with the logical Boolean
operator OR, for example, 'inside+touch'
. [2] The relation
strings are caseinsensitive.
Example:
Zipcode.objects.filter(poly__relate=(geom, 'anyinteract'))
Oracle SQL equivalent:
SELECT ... WHERE SDO_RELATE(poly, geom, 'anyinteract')
touches
¶
Availability: PostGIS, Oracle, MySQL, SpatiaLite
Tests if the geometry field spatially touches the lookup geometry.
Example:
Zipcode.objects.filter(poly__touches=geom)
Backend  SQL Equivalent 

PostGIS  ST_Touches(poly, geom) 
MySQL  MBRTouches(poly, geom) 
Oracle  SDO_TOUCH(poly, geom) 
SpatiaLite  Touches(poly, geom) 
within
¶
Availability: PostGIS, Oracle, MySQL, SpatiaLite, PGRaster (Bilateral)
Tests if the geometry field is spatially within the lookup geometry.
Example:
Zipcode.objects.filter(poly__within=geom)
Backend  SQL Equivalent 

PostGIS  ST_Within(poly, geom) 
MySQL  MBRWithin(poly, geom) 
Oracle  SDO_INSIDE(poly, geom) 
SpatiaLite  Within(poly, geom) 
left
¶
Availability: PostGIS, PGRaster (Conversion)
Tests if the geometry field’s bounding box is strictly to the left of the lookup geometry’s bounding box.
Example:
Zipcode.objects.filter(poly__left=geom)
PostGIS equivalent:
SELECT ... WHERE poly << geom
right
¶
Availability: PostGIS, PGRaster (Conversion)
Tests if the geometry field’s bounding box is strictly to the right of the lookup geometry’s bounding box.
Example:
Zipcode.objects.filter(poly__right=geom)
PostGIS equivalent:
SELECT ... WHERE poly >> geom
overlaps_left
¶
Availability: PostGIS, PGRaster (Bilateral)
Tests if the geometry field’s bounding box overlaps or is to the left of the lookup geometry’s bounding box.
Example:
Zipcode.objects.filter(poly__overlaps_left=geom)
PostGIS equivalent:
SELECT ... WHERE poly &< geom
overlaps_right
¶
Availability: PostGIS, PGRaster (Bilateral)
Tests if the geometry field’s bounding box overlaps or is to the right of the lookup geometry’s bounding box.
Example:
Zipcode.objects.filter(poly__overlaps_right=geom)
PostGIS equivalent:
SELECT ... WHERE poly &> geom
overlaps_above
¶
Availability: PostGIS, PGRaster (Conversion)
Tests if the geometry field’s bounding box overlaps or is above the lookup geometry’s bounding box.
Example:
Zipcode.objects.filter(poly__overlaps_above=geom)
PostGIS equivalent:
SELECT ... WHERE poly &> geom
overlaps_below
¶
Availability: PostGIS, PGRaster (Conversion)
Tests if the geometry field’s bounding box overlaps or is below the lookup geometry’s bounding box.
Example:
Zipcode.objects.filter(poly__overlaps_below=geom)
PostGIS equivalent:
SELECT ... WHERE poly &< geom
Distance Lookups¶
Availability: PostGIS, Oracle, MySQL, SpatiaLite, PGRaster (Native)
For an overview on performing distance queries, please refer to the distance queries introduction.
Distance lookups take the following form:
<field>__<distance lookup>=(<geometry/raster>, <distance value>[, 'spheroid'])
<field>__<distance lookup>=(<raster>, <band_index>, <distance value>[, 'spheroid'])
<field>__<band_index>__<distance lookup>=(<raster>, <band_index>, <distance value>[, 'spheroid'])
The value passed into a distance lookup is a tuple; the first two
values are mandatory, and are the geometry to calculate distances to,
and a distance value (either a number in units of the field, a
Distance
object, or a query expression
<ref/models/expressions>). To pass a band index to the lookup, use a 3tuple
where the second entry is the band index.
On every distance lookup except dwithin
, an optional element,
'spheroid'
, may be included to use the more accurate spheroid distance
calculation functions on fields with a geodetic coordinate system.
On PostgreSQL, the 'spheroid'
option uses ST_DistanceSpheroid instead of
ST_DistanceSphere. The
simpler ST_Distance function is
used with projected coordinate systems. Rasters are converted to geometries for
spheroid based lookups.
MySQL support was added.
distance_gt
¶
Returns models where the distance to the geometry field from the lookup geometry is greater than the given distance value.
Example:
Zipcode.objects.filter(poly__distance_gt=(geom, D(m=5)))
Backend  SQL Equivalent 

PostGIS  ST_Distance/ST_Distance_Sphere(poly, geom) > 5 
Oracle  SDO_GEOM.SDO_DISTANCE(poly, geom, 0.05) > 5 
SpatiaLite  Distance(poly, geom) > 5 
distance_gte
¶
Returns models where the distance to the geometry field from the lookup geometry is greater than or equal to the given distance value.
Example:
Zipcode.objects.filter(poly__distance_gte=(geom, D(m=5)))
Backend  SQL Equivalent 

PostGIS  ST_Distance/ST_Distance_Sphere(poly, geom) >= 5 
Oracle  SDO_GEOM.SDO_DISTANCE(poly, geom, 0.05) >= 5 
SpatiaLite  Distance(poly, geom) >= 5 
distance_lt
¶
Returns models where the distance to the geometry field from the lookup geometry is less than the given distance value.
Example:
Zipcode.objects.filter(poly__distance_lt=(geom, D(m=5)))
Backend  SQL Equivalent 

PostGIS  ST_Distance/ST_Distance_Sphere(poly, geom) < 5 
Oracle  SDO_GEOM.SDO_DISTANCE(poly, geom, 0.05) < 5 
SpatiaLite  Distance(poly, geom) < 5 
distance_lte
¶
Returns models where the distance to the geometry field from the lookup geometry is less than or equal to the given distance value.
Example:
Zipcode.objects.filter(poly__distance_lte=(geom, D(m=5)))
Backend  SQL Equivalent 

PostGIS  ST_Distance/ST_Distance_Sphere(poly, geom) <= 5 
Oracle  SDO_GEOM.SDO_DISTANCE(poly, geom, 0.05) <= 5 
SpatiaLite  Distance(poly, geom) <= 5 
dwithin
¶
Returns models where the distance to the geometry field from the lookup
geometry are within the given distance from one another. Note that you can only
provide Distance
objects if the targeted
geometries are in a projected system. For geographic geometries, you should use
units of the geometry field (e.g. degrees for WGS84
) .
Example:
Zipcode.objects.filter(poly__dwithin=(geom, D(m=5)))
Backend  SQL Equivalent 

PostGIS  ST_DWithin(poly, geom, 5) 
Oracle  SDO_WITHIN_DISTANCE(poly, geom, 5) 
SpatiaLite  PtDistWithin(poly, geom, 5) 
Aggregate Functions¶
Django provides some GISspecific aggregate functions. For details on how to use these aggregate functions, see the topic guide on aggregation.
Keyword Argument  Description 

tolerance 
This keyword is for Oracle only. It is for the
tolerance value used by the SDOAGGRTYPE
procedure; the Oracle documentation has more
details. 
Example:
>>> from django.contrib.gis.db.models import Extent, Union
>>> WorldBorder.objects.aggregate(Extent('mpoly'), Union('mpoly'))
Collect
¶

class
Collect
(geo_field)¶
Availability: PostGIS, SpatiaLite
Returns a GEOMETRYCOLLECTION
or a MULTI
geometry object from the geometry
column. This is analogous to a simplified version of the Union
aggregate, except it can be several orders of magnitude faster than performing
a union because it simply rolls up geometries into a collection or multi object,
not caring about dissolving boundaries.
Extent
¶

class
Extent
(geo_field)¶
Availability: PostGIS, Oracle, SpatiaLite
Returns the extent of all geo_field
in the QuerySet
as a fourtuple,
comprising the lower left coordinate and the upper right coordinate.
Example:
>>> qs = City.objects.filter(name__in=('Houston', 'Dallas')).aggregate(Extent('poly'))
>>> print(qs['poly__extent'])
(96.8016128540039, 29.7633724212646, 95.3631439208984, 32.782058715820)
Extent3D
¶

class
Extent3D
(geo_field)¶
Availability: PostGIS
Returns the 3D extent of all geo_field
in the QuerySet
as a sixtuple,
comprising the lower left coordinate and upper right coordinate (each with x, y,
and z coordinates).
Example:
>>> qs = City.objects.filter(name__in=('Houston', 'Dallas')).aggregate(Extent3D('poly'))
>>> print(qs['poly__extent3d'])
(96.8016128540039, 29.7633724212646, 0, 95.3631439208984, 32.782058715820, 0)
MakeLine
¶

class
MakeLine
(geo_field)¶
Availability: PostGIS, SpatiaLite
Returns a LineString
constructed from the point field geometries in the
QuerySet
. Currently, ordering the queryset has no effect.
Example:
>>> qs = City.objects.filter(name__in=('Houston', 'Dallas')).aggregate(MakeLine('poly'))
>>> print(qs['poly__makeline'])
LINESTRING (95.3631510000000020 29.7633739999999989, 96.8016109999999941 32.7820570000000018)
Union
¶

class
Union
(geo_field)¶
Availability: PostGIS, Oracle, SpatiaLite
This method returns a GEOSGeometry
object
comprising the union of every geometry in the queryset. Please note that use of
Union
is processor intensive and may take a significant amount of time on
large querysets.
Note
If the computation time for using this method is too expensive, consider
using Collect
instead.
Example:
>>> u = Zipcode.objects.aggregate(Union(poly)) # This may take a long time.
>>> u = Zipcode.objects.filter(poly__within=bbox).aggregate(Union(poly)) # A more sensible approach.
Footnotes
[1]  See OpenGIS Simple Feature Specification For SQL, at Ch. 2.1.13.2, p. 213 (The Dimensionally Extended NineIntersection Model). 
[2]  See SDO_RELATE documentation, from the Oracle Spatial and Graph Developer’s Guide. 
[3]  (1, 2) For an explanation of this routine, read Quirks of the “Contains” Spatial Predicate by Martin Davis (a PostGIS developer). 