---
title: "API GDAL"
version: 2.0
locale: id
source: https://docs.djangoproject.com/id/2.0/ref/contrib/gis/gdal/
canonical: https://djangodocs.dev/id/2.0/ref/contrib/gis/gdal/
---
# API GDAL

[GDAL](http://www.gdal.org/) stands for **Geospatial Data Abstraction Library**,
and is a veritable "Swiss army knife" of GIS data functionality.  A subset
of GDAL is the [OGR](http://www.gdal.org/ogr_arch.html) Simple Features Library, which specializes
in reading and writing vector geographic data in a variety of standard
formats.

GeoDjango provides a high-level Python interface for some of the
capabilities of OGR, including the reading and coordinate transformation
of vector spatial data and minimal support for GDAL's features with respect
to raster (image) data.

> **Note**
>
> Although the module is named `gdal`, GeoDjango only supports some of the
> capabilities of OGR and GDAL's raster features at this time.

## Ikhtisar

### Data Contoh

The GDAL/OGR tools described here are designed to help you read in
your geospatial data, in order for most of them to be useful you have
to have some data to work with.  If you're starting out and don't yet
have any data of your own to use, GeoDjango tests contain a number of
simple data sets that you can use for testing. You can download them here:

```
$ wget https://raw.githubusercontent.com/django/django/master/tests/gis_tests/data/cities/cities.{shp,prj,shx,dbf}
$ wget https://raw.githubusercontent.com/django/django/master/tests/gis_tests/data/rasters/raster.tif
```

## Vector Data Source Object

### `DataSource`

[`DataSource`](#django.contrib.gis.gdal.DataSource) adalah sebuah pembungkus untuk obyek sumber data OGR yang mendukung membaca data dari beragam dari bentuk berkas geospasial didukung-OGR dan sumber data menggunakan sederhana, konsisten antarmuka. Setiap sumber data diwakili oleh sebuah obyek [`DataSource`](#django.contrib.gis.gdal.DataSource) yang mengandung satu atau lebih lapisan data. Setiap lapisan, diwakili oleh [`Layer`](#django.contrib.gis.gdal.Layer) object, mengandung beberapa nomor dari fitur-fitur geografik ([`Feature`](#django.contrib.gis.gdal.Feature)), informasi tentang jenis dari fitur-fitur mengandung di lapisan itu (sebagai contoh titik, poligon, dll.), sama halnya nama-nama dan jenis-jenis dari bidang tambahan apapun ([`Field`](#django.contrib.gis.gdal.Field)) dari data yang mungkin terhubung dengan setiap fitur di lapisan itu.

#### `class DataSource(ds_input, encoding='utf-8')`

Pembangun untuk `DataSource` hanya membutuhkan satu parameter: jalur dari berkas anda ingin baca. Bagaimanapun, OGR juga mendukung beragam sumber data lebih rumit, termasuk basisdata, yang mungkin diakses dengan melewatkan string nama khusus daripada jalur. Untuk informasi lebih, lihat dokumentasi [OGR Vector Formats](http://www.gdal.org/ogr_formats.html). Sifat [`name`](#django.contrib.gis.gdal.DataSource.name) dari sebuah instance `DataSource` memberikan nama OGR dari sumber data pokok yang itu sedang gunakan.

Pilihan parameter `encoding` mengizinkan anda menentukan penyandian bukan-standar dari string di sumber. Ini khususnya berguna ketika anda mendapatkan pengecualian `DjangoUnicodeDecodeError` selagi membaca nilai bidang.

Sekali anda telah membuat `DataSource` anda, anda dapat menemukan seberapa banyak lapisan data itu kandung dengan mengakses sifat [`layer_count`](#django.contrib.gis.gdal.DataSource.layer_count), atau (setara) dengan menggunakan fungsi `len()`. Untuk informasi pada mengakses lapisan dari data mereka sendiri, lihat bagian lain:

```
>>> from django.contrib.gis.gdal import DataSource
>>> ds = DataSource('/path/to/your/cities.shp')
>>> ds.name
'/path/to/your/cities.shp'
>>> ds.layer_count                  # This file only contains one layer
1
```

#### `layer_count`

Mengembalikan sejumlah lapisan di sumber data.

#### `name`

Mengembalikan nama dari sumber data.

### `Lapisan`

#### `class Layer`

`Layer` adalah sebuah pembungkus untuk lapisan dari data di obyek `DataSource`. Anda tidak pernah membuat obyek `Layer` secara langsung. Sebagai gantinya, anda mengambil mereka dari obyek [`DataSource`](#django.contrib.gis.gdal.DataSource), yang pada dasarnya wadah standar Python dari obyek `Layer`. Sebagai contoh, anda dapat mengakses lapisan khusus dengan indeksnya (sebagai contoh `ds[0]` untuk mengakses lapisan pertama), atau anda dapat mengulang terhadap semua lapisan di wadah dalam perulangan `loop`. `Layer` itu sendiri bertindak sebagai sebuah wadah untuk fitur-fitur geometris.

Khususnya, semua fitur di lapisan yang diberikan mempunyai jenis geometri sama. Sifat [`geom_type`](#django.contrib.gis.gdal.Layer.geom_type) dari lapisan adalah sebuah [`OGRGeomType`](#django.contrib.gis.gdal.OGRGeomType) yang mencirikan jenis fitur. Kami dapat menggunakan itu untuk mencetak beberapa informasi dasar tentang setiap lapisan di [`DataSource`](#django.contrib.gis.gdal.DataSource):

```
>>> for layer in ds:
...     print('Layer "%s": %i %ss' % (layer.name, len(layer), layer.geom_type.name))
...
Layer "cities": 3 Points
```

Keluaran contoh adalah dari sumber data kota, dimuat diatas, yang ternyata mengandung satu lapisan, dipanggil `"cities"`, yang mengandung tida titik fitur. Untuk kemudahan, contoh-contoh diatas menganggap bahwa anda telah menyimpan lapisan itu di variabel `layer`:

```
>>> layer = ds[0]
```

#### `name`

Mengembalikan nama lapisan ini di sumber data.

```
>>> layer.name
'cities'
```

#### `num_feat`

Mengembalikan sejumlah fitur-fitur di lapisan. Sama seperti `len(layer)`:

```
>>> layer.num_feat
3
```

#### `geom_type`

Mengembalikan jenis geometri dari lapisan, sebagai sebuah obyek [`OGRGeomType`](#django.contrib.gis.gdal.OGRGeomType):

```
>>> layer.geom_type.name
'Point'
```

#### `num_fields`

Mengembalikan sejumlah bidang di lapisan, yaitu sejumlah bidang dari data terhubung dengan setiap fitur di lapisan:

```
>>> layer.num_fields
4
```

#### `fields`

Mengembalikan daftar nama dari setiap bidang di lapisan ini:

```
>>> layer.fields
['Name', 'Population', 'Density', 'Created']
```

Mengembalikan daftar dari jenis-jenis data dari setiap bidang di lapisan ini. Ini adalah subkelas dari `Field`, diobrolkan dibawah:

```
>>> [ft.__name__ for ft in layer.field_types]
['OFTString', 'OFTReal', 'OFTReal', 'OFTDate']
```

#### `field_widths`

Mengembalikan daftar dari bidang maksimal untuk setiap bidang dalam lapisan ini:

```
>>> layer.field_widths
[80, 11, 24, 10]
```

#### `field_precisions`

Mengembalikan daftar dari angka ketelitian untuk setiap dari bidang-bidang dalam lapisan ini. Ini tidak berarti (dan disetel ke nol) untuk bidang bukan-numerik:

```
>>> layer.field_precisions
[0, 0, 15, 0]
```

#### `extent`

Mengembalikan tingkatan spasial dari lapisan ini, sebagai sebuah obyek [`Envelope`](#django.contrib.gis.gdal.Envelope):

```
>>> layer.extent.tuple
(-104.609252, 29.763374, -95.23506, 38.971823)
```

#### `srs`

Sifat yang mengembalikan [`SpatialReference`](#django.contrib.gis.gdal.SpatialReference) terkait dengan lapisan ini:

```
>>> print(layer.srs)
GEOGCS["GCS_WGS_1984",
    DATUM["WGS_1984",
        SPHEROID["WGS_1984",6378137,298.257223563]],
    PRIMEM["Greenwich",0],
    UNIT["Degree",0.017453292519943295]]
```

Jika [`Layer`](#django.contrib.gis.gdal.Layer) tidak mempunyai informasi acuan spasial terkait dengan itu, \`\` None\`\` dikembalikan.

#### `spatial_filter`

Property that may be used to retrieve or set a spatial filter for this
layer. A spatial filter can only be set with an [`OGRGeometry`](#django.contrib.gis.gdal.OGRGeometry)
instance, a 4-tuple extent, or `None`. When set with something other than
`None`, only features that intersect the filter will be returned when
iterating over the layer:

```
>>> print(layer.spatial_filter)
None
>>> print(len(layer))
3
>>> [feat.get('Name') for feat in layer]
['Pueblo', 'Lawrence', 'Houston']
>>> ks_extent = (-102.051, 36.99, -94.59, 40.00) # Extent for state of Kansas
>>> layer.spatial_filter = ks_extent
>>> len(layer)
1
>>> [feat.get('Name') for feat in layer]
['Lawrence']
>>> layer.spatial_filter = None
>>> len(layer)
3
```

#### `get_fields()`

Sebuah metode yang mengembalikan sebuah daftar dari nilai-nilai dari bidang yang diberikan untuk setiap fitur dalam lapisan:

```
>>> layer.get_fields('Name')
['Pueblo', 'Lawrence', 'Houston']
```

#### `get_geoms(geos=False)`

A method that returns a list containing the geometry of each feature in the
layer. If the optional argument `geos` is set to `True` then the
geometries are converted to [`GEOSGeometry`](/id/2.0/ref/contrib/gis/geos/#django.contrib.gis.geos.GEOSGeometry)
objects. Otherwise, they are returned as [`OGRGeometry`](#django.contrib.gis.gdal.OGRGeometry) objects:

```
>>> [pt.tuple for pt in layer.get_geoms()]
[(-104.609252, 38.255001), (-95.23506, 38.971823), (-95.363151, 29.763374)]
```

#### `test_capability(capability)`

Returns a boolean indicating whether this layer supports the given
capability (a string).  Examples of valid capability strings include:
`'RandomRead'`, `'SequentialWrite'`, `'RandomWrite'`,
`'FastSpatialFilter'`, `'FastFeatureCount'`, `'FastGetExtent'`,
`'CreateField'`, `'Transactions'`, `'DeleteFeature'`, and
`'FastSetNextByIndex'`.

### `Feature`

#### `class Feature`

`Feature` membungkus fitur OGR. Anda tidak pernah membuat obyek `Feature` secara langsung. Sebagai gantinya, anda mengambil mereka dari obyek [`Layer`](#django.contrib.gis.gdal.Layer). Setiap fitur terdiri dari sebuah geometri dan sekumpulan bidang mengandung sifat-sifat tambahan. Geometri dari sebuah bidang adalah dapat diakses melalui sifat `geom` nya, yang mengembalikan sebuah obyek [`OGRGeometry`](#django.contrib.gis.gdal.OGRGeometry). Sebuah `Feature` berperilaku seperti wadah Python standar untuk bidangnya, yang itu dikembalikan sebagai obyek [`Field`](#django.contrib.gis.gdal.Field): anda dapat mengakses sebuah bidang secara langsung berdasarkan indeks atau namanya, atau dapat berulang terhadap bidang-bidang fitur, sebagai contoh di sebuah perulangan `for`.

#### `geom`

Mengembalikan geometri untuk fotur ini, sebagai sebuah obyek `OGRGeometry`:

```
>>> city.geom.tuple
(-104.609252, 38.255001)
```

#### `get`

Sebuah metode yang mengembalikan nilai dari bidang yang diberikan (ditentukan oleh nama) untuk fitur ini, **bukan** sebuah obyek pembungkus `Field`:

```
>>> city.get('Population')
102121
```

#### `geom_type`

Returns the type of geometry for this feature, as an [`OGRGeomType`](#django.contrib.gis.gdal.OGRGeomType)
object. This will be the same for all features in a given layer and is
equivalent to the [`Layer.geom_type`](#django.contrib.gis.gdal.Layer.geom_type) property of the [`Layer`](#django.contrib.gis.gdal.Layer)
object the feature came from.

#### `num_fields`

Returns the number of fields of data associated with the feature. This will
be the same for all features in a given layer and is equivalent to the
[`Layer.num_fields`](#django.contrib.gis.gdal.Layer.num_fields) property of the [`Layer`](#django.contrib.gis.gdal.Layer) object the feature
came from.

#### `fields`

Returns a list of the names of the fields of data associated with the
feature. This will be the same for all features in a given layer and is
equivalent to the [`Layer.fields`](#django.contrib.gis.gdal.Layer.fields) property of the [`Layer`](#django.contrib.gis.gdal.Layer)
object the feature came from.

#### `fid`

Mengembalikan penciri fitur dalam lapisan:

```
>>> city.fid
0
```

#### `layer_name`

Mengembalikan nama dari [`Layer`](#django.contrib.gis.gdal.Layer) yang berasal fitur. Ini akan menjadi sama untuk semua fitur dalam lapisan yang diberikan:

```
>>> city.layer_name
'cities'
```

#### `index`

Sebuah metode yang mengembalikan indeks dari nama bidang yang diberikan. Ini akan sama untuk semua fitur-fitur dalam lapisan yang diberikan:

```
>>> city.index('Population')
1
```

### `Field`

#### `class Field`

#### `name`

Mengembalikan nama dari bidang ini:

```
>>> city['Name'].name
'Name'
```

#### `type`

Mengembalikan jenis OGR dari bidang ini, sebagai sebuah integer. Dictionary `FIELD_CLASSES` memetakan nilai-nilai ini kedalam subkelas dari `Field`:

```
>>> city['Density'].type
2
```

#### `type_name`

Mengembalikan string dengan nama dari jenis data dari bidang ini:

```
>>> city['Name'].type_name
'String'
```

#### `value`

Mengembalikan nilai dari bidang ini. Kelas `Field` itu sendiri mengembalikan nilai sebagai sebuah string, tetapi setiap subkelas mengembalikan nilai dalam bentuk paling sesuai:

```
>>> city['Population'].value
102121
```

#### `width`

Mengembalikan lebar bidang ini:

```
>>> city['Name'].width
80
```

#### `precision`

Mengembalikan ketelitian numerik dari bidang ini. Ini tidak berarti (dan disetel ke nol) untuk bidang-bidang bukan-numerik:

```
>>> city['Density'].precision
15
```

#### `as_double()`

Mengembalikan nilai dari bidang sebagai double (float):

```
>>> city['Density'].as_double()
874.7
```

#### `as_int()`

Mengembalikan nilai dari bidang sebagai integer:

```
>>> city['Population'].as_int()
102121
```

#### `as_string()`

Mengembalikan nilai dari bidang sebagai deretan kalimat:

```
>>> city['Name'].as_string()
'Pueblo'
```

#### `as_datetime()`

Mengembalikan nilai dari bidang sebagai tuple dari komponen tanggal dan waktu:

```
>>> city['Created'].as_datetime()
(c_long(1999), c_long(5), c_long(23), c_long(0), c_long(0), c_long(0), c_long(0))
```

### `Driver`

#### `class Driver(dr_input)`

Kelas `Driver` digunakan secara mendalam untuk membungkus sebuah driver [`DataSource`](#django.contrib.gis.gdal.DataSource) OGR.

#### `driver_count`

Mengembalikan sejumlah driver vektor OGR saat ini terdaftar.

## Geometri OGR

### `OGRGeometry`

Obyek-obyek [`OGRGeometry`](#django.contrib.gis.gdal.OGRGeometry) berbagi fungsi mirip dengan obyek [`GEOSGeometry`](/id/2.0/ref/contrib/gis/geos/#django.contrib.gis.geos.GEOSGeometry) dan pembungkus tipis disekitar perwakilan geometri internal OGR. Dengan demikian, mereka mengizinkan untuk lebih efektid mengakses ke data ketika menggunakan [`DataSource`](#django.contrib.gis.gdal.DataSource). Tidak seprti pasangan GEOS nya, [`OGRGeometry`](#django.contrib.gis.gdal.OGRGeometry) mendukung sistem acuan spasial dan perubahan kordinat:

```
>>> from django.contrib.gis.gdal import OGRGeometry
>>> polygon = OGRGeometry('POLYGON((0 0, 5 0, 5 5, 0 5))')
```

#### `class OGRGeometry(geom_input, srs=None)`

Obyek ini adalah sebuah pembungkus untuk kelas [OGR Geometry](http://www.gdal.org/classOGRGeometry.html). Obyek-obyek ini diinstasiasikan secara langsung dari parameter `geom_input` yang diberikan, yang mungkin berupa string mengandung WKT, HEX, GeoJSON, sebuah `buffer` mengandung data WKB, atau sebuah obyek [`OGRGeomType`](#django.contrib.gis.gdal.OGRGeomType). Obyek-obyek ini juga dikembalikan dari atribut [`Feature.geom`](#django.contrib.gis.gdal.Feature.geom), ketika membaca data vektor dari [`Layer`](#django.contrib.gis.gdal.Layer) (yaitu pada giliran bagian dari sebuah [`DataSource`](#django.contrib.gis.gdal.DataSource)).

#### `classmethod from_gml(gml_string)`

> **New in Django 1.11**

Membangun sebuah [`OGRGeometry`](#django.contrib.gis.gdal.OGRGeometry) dari string GML yang diberikan.

#### `classmethod from_bbox(bbox)`

Membangun sebuah [`Polygon`](#django.contrib.gis.gdal.Polygon) dari kotak-terikat diberikan (4-tuple).

#### `__len__()`

Mengembalikan sejumlah titik dalam sebuah [`LineString`](#django.contrib.gis.gdal.LineString), sejumlah geometri dalam sebuah  [`GeometryCollection`](#django.contrib.gis.gdal.GeometryCollection). Tidak diberlakukan ke jenis geometri lain.

#### `__iter__()`

Iterates over the points in a [`LineString`](#django.contrib.gis.gdal.LineString), the rings in a
[`Polygon`](#django.contrib.gis.gdal.Polygon), or the geometries in a [`GeometryCollection`](#django.contrib.gis.gdal.GeometryCollection).
Not applicable to other geometry types.

#### `__getitem__()`

Returns the point at the specified index for a [`LineString`](#django.contrib.gis.gdal.LineString), the
interior ring at the specified index for a [`Polygon`](#django.contrib.gis.gdal.Polygon), or the geometry
at the specified index in a [`GeometryCollection`](#django.contrib.gis.gdal.GeometryCollection). Not applicable to
other geometry types.

#### `dimension`

Mengembalikan sejumlah dimensi kordinat dari geometri, yaitu 0 untuk titik, 1 untuk baris, dan sebagainya:

```
>> polygon.dimension
2
```

#### `coord_dim`

Returns or sets the coordinate dimension of this geometry. For example, the
value would be 2 for two-dimensional geometries.

#### `geom_count`

Mengembalikan sejumlah unsur dalam geometri ini:

```
>>> polygon.geom_count
1
```

#### `point_count`

Mengembalikan sejumlah titik digunakan untuk menggambarkan geometri ini:

```
>>> polygon.point_count
4
```

#### `num_points`

Nama lain untuk [`point_count`](#django.contrib.gis.gdal.OGRGeometry.point_count).

#### `num_coords`

Nama lain untuk [`point_count`](#django.contrib.gis.gdal.OGRGeometry.point_count).

#### `geom_type`

Mengembalikan jenis dari geometri ini, sebagai sebuah obyek [`OGRGeomType`](#django.contrib.gis.gdal.OGRGeomType).

#### `geom_name`

Mengembalikan nama dari jenis dari geometri ini:

```
>>> polygon.geom_name
'POLYGON'
```

#### `area`

Mengembalikan kawasan dari geometri ini, atau 0 untuk geometri yang tidak mengandung sebuah kawasan:

```
>>> polygon.area
25.0
```

#### `envelope`

Mengembalikan sampul dari geometri ini, sebagai sebuah obyek [`Envelope`](#django.contrib.gis.gdal.Envelope).

#### `extent`

Returns the envelope of this geometry as a 4-tuple, instead of as an
[`Envelope`](#django.contrib.gis.gdal.Envelope) object:

```
>>> point.extent
(0.0, 0.0, 5.0, 5.0)
```

#### `srs`

Sifat ini mengendalikan acuan spasial untuk geometri ini, atau `None` jika tidak ada sisterm acuan spasia telah diberikan ke itu. Jika diberikan, mengakses sifat ini mengembalikan sebuah obyek [`SpatialReference`](#django.contrib.gis.gdal.SpatialReference). Itu mungkin disetel dengan obyek [`SpatialReference`](#django.contrib.gis.gdal.SpatialReference) lain, atau masukan apapun yang [`SpatialReference`](#django.contrib.gis.gdal.SpatialReference) terima. Contoh:

```
>>> city.geom.srs.name
'GCS_WGS_1984'
```

#### `srid`

Returns or sets the spatial reference identifier corresponding to
[`SpatialReference`](#django.contrib.gis.gdal.SpatialReference) of this geometry.  Returns `None` if
there is no spatial reference information associated with this
geometry, or if an SRID cannot be determined.

#### `geos`

Mengebalikan obyek [`GEOSGeometry`](/id/2.0/ref/contrib/gis/geos/#django.contrib.gis.geos.GEOSGeometry) sesuai pada geometri ini.

#### `gml`

Mengembalikan sebuah string perwakilan dari geometri ini dalam bentuk GML:

```
>>> OGRGeometry('POINT(1 2)').gml
'<gml:Point><gml:coordinates>1,2</gml:coordinates></gml:Point>'
```

#### `hex`

Mengembalikan perwakilan string dari geometri ini dalam bentuk HEX WKB:

```
>>> OGRGeometry('POINT(1 2)').hex
'0101000000000000000000F03F0000000000000040'
```

#### `json`

Mengembalikan string perwakilan dari geometri ini dalam bentuk JSON:

```
>>> OGRGeometry('POINT(1 2)').json
'{ "type": "Point", "coordinates": [ 1.000000, 2.000000 ] }'
```

#### `kml`

Mengembalikan perwakilan string dari geometri ini dalam bentuk KML.

#### `wkb_size`

Mengembalikan ukuran dari penyangga WKB untuk menahan perwakilan WKB dari geometri ini:

```
>>> OGRGeometry('POINT(1 2)').wkb_size
21
```

#### `wkb`

Mengembalikan sebuah `buffer` mengandung perwakilan WKB dari geometri ini.

#### `wkt`

Mengembalikan perwakilan string dari geometri ini dalam bentuk WKT.

#### `ewkt`

Mengembalikan perwakilan EWKT dari geometri ini.

#### `clone()`

Mengembalikan klon baru [`OGRGeometry`](#django.contrib.gis.gdal.OGRGeometry) dari obyek geometri ini.

#### `close_rings()`

Jika ada lingkaran apapun dalam geometri ini yang belum ditutup, rutin ini akan melakukannya dengan menambahkan titik awalan ke akhiran:

```
>>> triangle = OGRGeometry('LINEARRING (0 0,0 1,1 0)')
>>> triangle.close_rings()
>>> triangle.wkt
'LINEARRING (0 0,0 1,1 0,0 0)'
```

#### `transform(coord_trans, clone=False)`

Transforms this geometry to a different spatial reference system. May take
a [`CoordTransform`](#django.contrib.gis.gdal.CoordTransform) object, a [`SpatialReference`](#django.contrib.gis.gdal.SpatialReference) object, or
any other input accepted by [`SpatialReference`](#django.contrib.gis.gdal.SpatialReference) (including spatial
reference WKT and PROJ.4 strings, or an integer SRID).

By default nothing is returned and the geometry is transformed in-place.
However, if the `clone` keyword is set to `True` then a transformed
clone of this geometry is returned instead.

#### `intersects(other)`

Mengembalikan `True` jika geometri ini memotong ke lain, sebaliknya mengembalikan `False`.

#### `equals(other)`

Mengembalikan `True` jika geometri ini setara dengan lain, sebaliknya mengembalikan `True`.

#### `disjoint(other)`

Returns `True` if this geometry is spatially disjoint to (i.e. does
not intersect) the other, otherwise returns `False`.

#### `touches(other)`

Mengembalikan `True` jika geometri ini menyentuh lainnya, sebaliknya mengembalikan `False`.

#### `crosses(other)`

Mengembalikan `True` jika geometri ini bersilangan ke lainnya, sebaliknya mengembalikan `False`.

#### `within(other)`

Returns `True` if this geometry is contained within the other, otherwise
returns `False`.

#### `contains(other)`

Returns `True` if this geometry contains the other, otherwise returns
`False`.

#### `overlaps(other)`

Returns `True` if this geometry overlaps the other, otherwise returns
`False`.

#### `boundary()`

The boundary of this geometry, as a new [`OGRGeometry`](#django.contrib.gis.gdal.OGRGeometry) object.

#### `convex_hull`

The smallest convex polygon that contains this geometry, as a new
[`OGRGeometry`](#django.contrib.gis.gdal.OGRGeometry) object.

#### `difference()`

Returns the region consisting of the difference of this geometry and
the other, as a new [`OGRGeometry`](#django.contrib.gis.gdal.OGRGeometry) object.

#### `intersection()`

Returns the region consisting of the intersection of this geometry and
the other, as a new [`OGRGeometry`](#django.contrib.gis.gdal.OGRGeometry) object.

#### `sym_difference()`

Returns the region consisting of the symmetric difference of this
geometry and the other, as a new [`OGRGeometry`](#django.contrib.gis.gdal.OGRGeometry) object.

#### `union()`

Returns the region consisting of the union of this geometry and
the other, as a new [`OGRGeometry`](#django.contrib.gis.gdal.OGRGeometry) object.

#### `tuple`

Mengembalikan kordinat-kordinat dari titik geometri sebagai sebuah tuple, kordinat-kordinat dari baris geometri sebagai sebuah tuple dari tuple, dan sebagainya:

```
>>> OGRGeometry('POINT (1 2)').tuple
(1.0, 2.0)
>>> OGRGeometry('LINESTRING (1 2,3 4)').tuple
((1.0, 2.0), (3.0, 4.0))
```

#### `coords`

Sebuah nama lain untuk [`tuple`](#django.contrib.gis.gdal.OGRGeometry.tuple).

#### `class Point`

#### `x`

Mengembalikan kordinat X dari titik ini:

```
>>> OGRGeometry('POINT (1 2)').x
1.0
```

#### `y`

Mengembalikan kordinat Y dari titik ini:

```
>>> OGRGeometry('POINT (1 2)').y
2.0
```

#### `z`

Returns the Z coordinate of this point, or `None` if the point does not
have a Z coordinate:

```
>>> OGRGeometry('POINT (1 2 3)').z
3.0
```

#### `class LineString`

#### `x`

Mengembalikan sebuah daftar dari kordinat X dalam baris ini:

```
>>> OGRGeometry('LINESTRING (1 2,3 4)').x
[1.0, 3.0]
```

#### `y`

Mengembalikan sebuah daftar dari kordinat Y dalam baris ini:

```
>>> OGRGeometry('LINESTRING (1 2,3 4)').y
[2.0, 4.0]
```

#### `z`

Returns a list of Z coordinates in this line, or `None` if the line does
not have Z coordinates:

```
>>> OGRGeometry('LINESTRING (1 2 3,4 5 6)').z
[3.0, 6.0]
```

#### `class Polygon`

#### `shell`

Returns the shell or exterior ring of this polygon, as a `LinearRing`
geometry.

#### `exterior_ring`

Sebuah nama lain untuk [`shell`](#django.contrib.gis.gdal.Polygon.shell).

#### `centroid`

Returns a [`Point`](#django.contrib.gis.gdal.Point) representing the centroid of this polygon.

#### `class GeometryCollection`

#### `add(geom)`

Adds a geometry to this geometry collection. Not applicable to other
geometry types.

### `OGRGeomType`

#### `class OGRGeomType(type_input)`

Kelas ini mengizinkan untuk gambaran dari jenis geometri OGR dalam beberapa cara:

```
>>> from django.contrib.gis.gdal import OGRGeomType
>>> gt1 = OGRGeomType(3)             # Using an integer for the type
>>> gt2 = OGRGeomType('Polygon')     # Using a string
>>> gt3 = OGRGeomType('POLYGON')     # It's case-insensitive
>>> print(gt1 == 3, gt1 == 'Polygon') # Equivalence works w/non-OGRGeomType objects
True True
```

#### `name`

Returns a short-hand string form of the OGR Geometry type:

```
>>> gt1.name
'Polygon'
```

#### `num`

Mengembalikan sejumlah kaitan pada jenis geometri OGR:

```
>>> gt1.num
3
```

#### `django`

Returns the Django field type (a subclass of GeometryField) to use for
storing this OGR type, or `None` if there is no appropriate Django type:

```
>>> gt1.django
'PolygonField'
```

### `Envelope`

#### `class Envelope(*args)`

Represents an OGR Envelope structure that contains the minimum and maximum
X, Y coordinates for a rectangle bounding box. The naming of the variables
is compatible with the OGR Envelope C structure.

#### `min_x`

Nilai minimal kordinat X

#### `min_y`

Nilai maksimal kordinat X.

#### `max_x`

Nilai minimal kordinat Y.

#### `max_y`

Nilai maksimal kordinat Y.

#### `ur`

Kordinat atas-kanan, sebagai sebuah tuple.

#### `ll`

Kordinat kiri-bawah, sebagai sebuah tuple.

#### `tuple`

A tuple representing the envelope.

#### `wkt`

A string representing this envelope as a polygon in WKT format.

#### `expand_to_include(*args)`

## Coordinate System Object

### `SpatialReference`

#### `class SpatialReference(srs_input)`

Spatial reference objects are initialized on the given `srs_input`,
which may be one of the following:

- OGC Well Known Text (WKT) (sebuah string)
- Kode EPSG(integer atau string)
- String PROJ.4
- A shorthand string for well-known standards (`'WGS84'`, `'WGS72'`,
  `'NAD27'`, `'NAD83'`)

Contoh:

```
>>> wgs84 = SpatialReference('WGS84') # shorthand string
>>> wgs84 = SpatialReference(4326) # EPSG code
>>> wgs84 = SpatialReference('EPSG:4326') # EPSG string
>>> proj4 = '+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs '
>>> wgs84 = SpatialReference(proj4) # PROJ.4 string
>>> wgs84 = SpatialReference("""GEOGCS["WGS 84",
DATUM["WGS_1984",
     SPHEROID["WGS 84",6378137,298.257223563,
         AUTHORITY["EPSG","7030"]],
     AUTHORITY["EPSG","6326"]],
 PRIMEM["Greenwich",0,
     AUTHORITY["EPSG","8901"]],
 UNIT["degree",0.01745329251994328,
     AUTHORITY["EPSG","9122"]],
 AUTHORITY["EPSG","4326"]]""") # OGC WKT
```

#### `__getitem__(target)`

Returns the value of the given string attribute node, `None` if the node
doesn't exist. Can also take a tuple as a parameter, (target, child), where
child is the index of the attribute in the WKT. For example:

```
>>> wkt = 'GEOGCS["WGS 84", DATUM["WGS_1984, ... AUTHORITY["EPSG","4326"]]')
>>> srs = SpatialReference(wkt) # could also use 'WGS84', or 4326
>>> print(srs['GEOGCS'])
WGS 84
>>> print(srs['DATUM'])
WGS_1984
>>> print(srs['AUTHORITY'])
EPSG
>>> print(srs['AUTHORITY', 1]) # The authority value
4326
>>> print(srs['TOWGS84', 4]) # the fourth value in this wkt
0
>>> print(srs['UNIT|AUTHORITY']) # For the units authority, have to use the pipe symbol.
EPSG
>>> print(srs['UNIT|AUTHORITY', 1]) # The authority value for the units
9122
```

#### `attr_value(target, index=0)`

The attribute value for the given target node (e.g. `'PROJCS'`).
The index keyword specifies an index of the child node to return.

#### `auth_name(target)`

Returns the authority name for the given string target node.

#### `auth_code(target)`

Returns the authority code for the given string target node.

#### `clone()`

Returns a clone of this spatial reference object.

#### `identify_epsg()`

Metode ini memeriksa WKT dari `SpatialReference` ini dan akan menambahkan node-node wewenang EPSG dimana sebuah penciri EPSG dapat diterapkan.

#### `from_esri()`

Morphs this SpatialReference from ESRI's format to EPSG

#### `to_esri()`

Morphs this SpatialReference to ESRI's format.

#### `validate()`

Memeriksa untuk melihat jika acuan spasial diberikan adalah sah, jika tidak sebuah pengecualian akan dimunculkan.

#### `import_epsg(epsg)`

Import spatial reference from EPSG code.

#### `import_proj(proj)`

Import spatial reference from PROJ.4 string.

#### `import_user_input(user_input)`

#### `import_wkt(wkt)`

Import spatial reference from WKT.

#### `import_xml(xml)`

Import spatial reference from XML.

#### `name`

Returns the name of this Spatial Reference.

#### `srid`

Returns the SRID of top-level authority, or `None` if undefined.

#### `linear_name`

Mengambalikan nama dari satuan linear.

#### `linear_units`

Mengembalikan nilai dari satuan linear.

#### `angular_name`

Mengembalikan nama dari satuan sudut."

#### `angular_units`

Mengembalikan nilai dari satuan sudut.

#### `units`

Returns a 2-tuple of the units value and the units name and will
automatically determines whether to return the linear or angular units.

#### `ellipsoid`

Returns a tuple of the ellipsoid parameters for this spatial reference:
(semimajor axis, semiminor axis, and inverse flattening).

#### `semi_major`

Returns the semi major axis of the ellipsoid for this spatial reference.

#### `semi_minor`

Returns the semi minor axis of the ellipsoid for this spatial reference.

#### `inverse_flattening`

Returns the inverse flattening of the ellipsoid for this spatial reference.

#### `geographic`

Returns `True` if this spatial reference is geographic (root node is
`GEOGCS`).

#### `local`

Returns `True` if this spatial reference is local (root node is
`LOCAL_CS`).

#### `projected`

Returns `True` if this spatial reference is a projected coordinate system
(root node is `PROJCS`).

#### `wkt`

Returns the WKT representation of this spatial reference.

#### `pretty_wkt`

Returns the 'pretty' representation of the WKT.

#### `proj`

Returns the PROJ.4 representation for this spatial reference.

#### `proj4`

Nama lain untuk [`SpatialReference.proj`](#django.contrib.gis.gdal.SpatialReference.proj).

#### `xml`

Returns the XML representation of this spatial reference.

### `CoordTransform`

#### `class CoordTransform(source, target)`

Represents a coordinate system transform. It is initialized with two
[`SpatialReference`](#django.contrib.gis.gdal.SpatialReference), representing the source and target coordinate
systems, respectively. These objects should be used when performing the same
coordinate transformation repeatedly on different geometries:

```
>>> ct = CoordTransform(SpatialReference('WGS84'), SpatialReference('NAD83'))
>>> for feat in layer:
...     geom = feat.geom # getting clone of feature geometry
...     geom.transform(ct) # transforming
```

## Obyek Data Raster

### `GDALRaster`

[`GDALRaster`](#django.contrib.gis.gdal.GDALRaster) is a wrapper for the GDAL raster source object that
supports reading data from a variety of GDAL-supported geospatial file
formats and data sources using a simple, consistent interface.  Each
data source is represented by a [`GDALRaster`](#django.contrib.gis.gdal.GDALRaster) object which contains
one or more layers of data named bands.  Each band, represented by a
[`GDALBand`](#django.contrib.gis.gdal.GDALBand) object, contains georeferenced image data. For example, an RGB
image is represented as three bands: one for red, one for green, and one for
blue.

> **Note**
>
> For raster data there is no difference between a raster instance and its
> data source. Unlike for the Geometry objects, [`GDALRaster`](#django.contrib.gis.gdal.GDALRaster) objects are
> always a data source. Temporary rasters can be instantiated in memory
> using the corresponding driver, but they will be of the same class as file-based
> raster sources.

#### `class GDALRaster(ds_input, write=False)`

The constructor for `GDALRaster` accepts two parameters. The first
parameter defines the raster source, and the second parameter defines if a
raster should be opened in write mode. For newly-created rasters, the second
parameter is ignored and the new raster is always created in write mode.

The first parameter can take three forms: a string representing a file
path, a dictionary with values defining a new raster, or a bytes object
representing a raster file.

If the input is a file path, the raster is opened from there. If the input
is raw data in a dictionary, the parameters `width`, `height`, and
`srid` are required. If the input is a bytes object, it will be opened
using a GDAL virtual filesystem.

For a detailed description of how to create rasters using dictionary input,
see [Membuat raster dari data](#gdal-raster-ds-input). For a detailed description of how to
create rasters in the virtual filesystem, see [Using GDAL's Virtual Filesystem](#gdal-raster-vsimem).

The following example shows how rasters can be created from different input
sources (using the sample data from the GeoDjango tests; see also the
[Data Contoh](#gdal-sample-data) section).

```
>>> from django.contrib.gis.gdal import GDALRaster
>>> rst = GDALRaster('/path/to/your/raster.tif', write=False)
>>> rst.name
'/path/to/your/raster.tif'
>>> rst.width, rst.height  # This file has 163 x 174 pixels
(163, 174)
>>> rst = GDALRaster({  # Creates an in-memory raster
...     'srid': 4326,
...     'width': 4,
...     'height': 4,
...     'datatype': 1,
...     'bands': [{
...         'data': (2, 3),
...         'offset': (1, 1),
...         'size': (2, 2),
...         'shape': (2, 1),
...         'nodata_value': 5,
...     }]
... })
>>> rst.srs.srid
4326
>>> rst.width, rst.height
(4, 4)
>>> rst.bands[0].data()
array([[5, 5, 5, 5],
       [5, 2, 3, 5],
       [5, 2, 3, 5],
       [5, 5, 5, 5]], dtype=uint8)
>>> rst_file = open('/path/to/your/raster.tif', 'rb')
>>> rst_bytes = rst_file.read()
>>> rst = GDALRaster(rst_bytes)
>>> rst.is_vsi_based
True
>>> rst.name  # Stored in a random path in the vsimem filesystem.
'/vsimem/da300bdb-129d-49a8-b336-e410a9428dad'
```

> **Changed in Django 1.11**
>
> Added the ability to pass the `size`, `shape`, and `offset`
> parameters when creating [`GDALRaster`](#django.contrib.gis.gdal.GDALRaster) objects. The parameters
> can be passed through the `ds_input` dictionary. This allows to
> finely control initial pixel values. The functionality is similar to
> the [`GDALBand.data()`](#django.contrib.gis.gdal.GDALBand.data)
> method.

> **Changed in Django 2.0**
>
> Added the ability to read and write rasters in GDAL's memory-based
> virtual filesystem. `GDALRaster` objects can now be converted to and
> from binary data in-memory.

#### `name`

The name of the source which is equivalent to the input file path or the name
provided upon instantiation.

```
>>> GDALRaster({'width': 10, 'height': 10, 'name': 'myraster', 'srid': 4326}).name
'myraster'
```

#### `driver`

The name of the GDAL driver used to handle the input file. For `GDALRaster`s created
from a file, the driver type is detected automatically. The creation of rasters from
scratch is a in-memory raster by default (`'MEM'`), but can be altered as
needed. For instance, use `GTiff` for a `GeoTiff` file. For a list of file types,
see also the [GDAL Raster Formats](http://www.gdal.org/formats_list.html) list.

An in-memory raster is created through the following example:

```
>>> GDALRaster({'width': 10, 'height': 10, 'srid': 4326}).driver.name
'MEM'
```

A file based GeoTiff raster is created through the following example:

```
>>> import tempfile
>>> rstfile = tempfile.NamedTemporaryFile(suffix='.tif')
>>> rst = GDALRaster({'driver': 'GTiff', 'name': rstfile.name, 'srid': 4326,
...                   'width': 255, 'height': 255, 'nr_of_bands': 1})
>>> rst.name
'/tmp/tmp7x9H4J.tif'           # The exact filename will be different on your computer
>>> rst.driver.name
'GTiff'
```

#### `width`

The width of the source in pixels (X-axis).

```
>>> GDALRaster({'width': 10, 'height': 20, 'srid': 4326}).width
10
```

#### `height`

The height of the source in pixels (Y-axis).

```
>>> GDALRaster({'width': 10, 'height': 20, 'srid': 4326}).height
20
```

#### `srs`

The spatial reference system of the raster, as a
[`SpatialReference`](#django.contrib.gis.gdal.SpatialReference) instance. The SRS can be changed by
setting it to an other [`SpatialReference`](#django.contrib.gis.gdal.SpatialReference) or providing any input
that is accepted by the [`SpatialReference`](#django.contrib.gis.gdal.SpatialReference) constructor.

```
>>> rst = GDALRaster({'width': 10, 'height': 20, 'srid': 4326})
>>> rst.srs.srid
4326
>>> rst.srs = 3086
>>> rst.srs.srid
3086
```

#### `srid`

The Spatial Reference System Identifier (SRID) of the raster. This
property is a shortcut to getting or setting the SRID through the
[`srs`](#django.contrib.gis.gdal.GDALRaster.srs) attribute.

```
>>> rst = GDALRaster({'width': 10, 'height': 20, 'srid': 4326})
>>> rst.srid
4326
>>> rst.srid = 3086
>>> rst.srid
3086
>>> rst.srs.srid  # This is equivalent
3086
```

#### `geotransform`

The affine transformation matrix used to georeference the source, as a
tuple of six coefficients which map pixel/line coordinates into
georeferenced space using the following relationship:

```
Xgeo = GT(0) + Xpixel*GT(1) + Yline*GT(2)
Ygeo = GT(3) + Xpixel*GT(4) + Yline*GT(5)
```

The same values can be retrieved by accessing the [`origin`](#django.contrib.gis.gdal.GDALRaster.origin)
(indices 0 and 3), [`scale`](#django.contrib.gis.gdal.GDALRaster.scale) (indices 1 and 5) and [`skew`](#django.contrib.gis.gdal.GDALRaster.skew)
(indices 2 and 4) properties.

Awalnya adalah `[0.0, 1.0, 0.0, 0.0, 0.0, -1.0]`.

```
>>> rst = GDALRaster({'width': 10, 'height': 20, 'srid': 4326})
>>> rst.geotransform
[0.0, 1.0, 0.0, 0.0, 0.0, -1.0]
```

#### `origin`

Coordinates of the top left origin of the raster in the spatial
reference system of the source, as a point object with `x` and `y`
members.

```
>>> rst = GDALRaster({'width': 10, 'height': 20, 'srid': 4326})
>>> rst.origin
[0.0, 0.0]
>>> rst.origin.x = 1
>>> rst.origin
[1.0, 0.0]
```

#### `scale`

Pixel width and height used for georeferencing the raster, as a as a
point object with `x` and `y`  members. See [`geotransform`](#django.contrib.gis.gdal.GDALRaster.geotransform)
for more information.

```
>>> rst = GDALRaster({'width': 10, 'height': 20, 'srid': 4326})
>>> rst.scale
[1.0, -1.0]
>>> rst.scale.x = 2
>>> rst.scale
[2.0, -1.0]
```

#### `skew`

Skew coefficients used to georeference the raster, as a point object
with `x` and `y`  members. In case of north up images, these
coefficients are both `0`.

```
>>> rst = GDALRaster({'width': 10, 'height': 20, 'srid': 4326})
>>> rst.skew
[0.0, 0.0]
>>> rst.skew.x = 3
>>> rst.skew
[3.0, 0.0]
```

#### `extent`

Extent (boundary values) of the raster source, as a 4-tuple
`(xmin, ymin, xmax, ymax)` in the spatial reference system of the
source.

```
>>> rst = GDALRaster({'width': 10, 'height': 20, 'srid': 4326})
>>> rst.extent
(0.0, -20.0, 10.0, 0.0)
>>> rst.origin.x = 100
>>> rst.extent
(100.0, -20.0, 110.0, 0.0)
```

#### `bands`

List of all bands of the source, as [`GDALBand`](#django.contrib.gis.gdal.GDALBand) instances.

```
>>> rst = GDALRaster({"width": 1, "height": 2, 'srid': 4326,
...                   "bands": [{"data": [0, 1]}, {"data": [2, 3]}]})
>>> len(rst.bands)
2
>>> rst.bands[1].data()
array([[ 2.,  3.]], dtype=float32)
```

#### `warp(ds_input, resampling='NearestNeighbour', max_error=0.0)`

Returns a warped version of this raster.

The warping parameters can be specified through the `ds_input`
argument. The use of `ds_input` is analogous to the corresponding
argument of the class constructor. It is a dictionary with the
characteristics of the target raster. Allowed dictionary key values are
width, height, SRID, origin, scale, skew, datatype, driver, and name
(filename).

By default, the warp functions keeps most parameters equal to the
values of the original source raster, so only parameters that should be
changed need to be specified. Note that this includes the driver, so
for file-based rasters the warp function will create a new raster on
disk.

The only parameter that is set differently from the source raster is the
name. The default value of the the raster name is the name of the source
raster appended with `'_copy' + source_driver_name`. For file-based
rasters it is recommended to provide the file path of the target raster.

The resampling algorithm used for warping can be specified with the
`resampling` argument. The default is `NearestNeighbor`, and the
other allowed values are `Bilinear`, `Cubic`, `CubicSpline`,
`Lanczos`, `Average`, and `Mode`.

The `max_error` argument can be used to specify the maximum error
measured in input pixels that is allowed in approximating the
transformation. The default is 0.0 for exact calculations.

Untuk pengguna akrab dengan `GDAL`, fungsi ini mempunyai fungsionalitas mirip pada kegunaan baris-perintah `gdalwarp`.

For example, the warp function can be used for aggregating a raster to
the double of its original pixel scale:

```
>>> rst = GDALRaster({
...     "width": 6, "height": 6, "srid": 3086,
...     "origin": [500000, 400000],
...     "scale": [100, -100],
...     "bands": [{"data": range(36), "nodata_value": 99}]
... })
>>> target = rst.warp({"scale": [200, -200], "width": 3, "height": 3})
>>> target.bands[0].data()
array([[  7.,   9.,  11.],
       [ 19.,  21.,  23.],
       [ 31.,  33.,  35.]], dtype=float32)
```

#### `transform(srid, driver=None, name=None, resampling='NearestNeighbour', max_error=0.0)`

Returns a transformed version of this raster with the specified SRID.

This function transforms the current raster into a new spatial reference
system that can be specified with an `srid`. It calculates the bounds
and scale of the current raster in the new spatial reference system and
warps the raster using the [`warp`](#django.contrib.gis.gdal.GDALRaster.warp) function.

By default, the driver of the source raster is used and the name of the
raster is the original name appended with
`'_copy' + source_driver_name`. A different driver or name can be
specified with the `driver` and `name` arguments.

The default resampling algorithm is `NearestNeighbour` but can be
changed using the `resampling` argument. The default maximum allowed
error for resampling is 0.0 and can be changed using the `max_error`
argument. Consult the [`warp`](#django.contrib.gis.gdal.GDALRaster.warp) documentation for detail
on those arguments.

```
>>> rst = GDALRaster({
...     "width": 6, "height": 6, "srid": 3086,
...     "origin": [500000, 400000],
...     "scale": [100, -100],
...     "bands": [{"data": range(36), "nodata_value": 99}]
... })
>>> target = rst.transform(4326)
>>> target.origin
[-82.98492744885776, 27.601924753080144]
```

#### `info`

> **New in Django 2.0**

Returns a string with a summary of the raster. This is equivalent to
the [gdalinfo](http://www.gdal.org/gdalinfo.html) command line utility.

#### `metadata`

> **New in Django 2.0**

The metadata of this raster, represented as a nested dictionary. The
first-level key is the metadata domain. The second-level contains the
metadata item names and values from each domain.

To set or update a metadata item, pass the corresponding metadata item
to the method using the nested structure described above. Only keys
that are in the specified dictionary are updated; the rest of the
metadata remains unchanged.

To remove a metadata item, use `None` as the metadata value.

```
>>> rst = GDALRaster({'width': 10, 'height': 20, 'srid': 4326})
>>> rst.metadata
{}
>>> rst.metadata = {'DEFAULT': {'OWNER': 'Django', 'VERSION': '1.0'}}
>>> rst.metadata
{'DEFAULT': {'OWNER': 'Django', 'VERSION': '1.0'}}
>>> rst.metadata = {'DEFAULT': {'OWNER': None, 'VERSION': '2.0'}}
>>> rst.metadata
{'DEFAULT': {'VERSION': '2.0'}}
```

#### `vsi_buffer`

> **New in Django 2.0**
>
> A `bytes` representation of this raster. Returns `None` for rasters
> that are not stored in GDAL's virtual filesystem.

#### `is_vsi_based`

> **New in Django 2.0**
>
> A boolean indicating if this raster is stored in GDAL's virtual
> filesystem.

### `GDALBand`

#### `class GDALBand`

`GDALBand` instances are not created explicitly, but rather obtained
from a [`GDALRaster`](#django.contrib.gis.gdal.GDALRaster) object, through its [`bands`](#django.contrib.gis.gdal.GDALRaster.bands)
attribute. The GDALBands contain the actual pixel values of the raster.

#### `description`

Nama dari gambaran dari pita, jika ada.

#### `width`

The width of the band in pixels (X-axis).

#### `height`

The height of the band in pixels (Y-axis).

#### `pixel_count`

The total number of pixels in this band. Is equal to `width * height`.

#### `statistics(refresh=False, approximate=False)`

Compute statistics on the pixel values of this band. The return value
is a tuple with the following structure:
`(minimum, maximum, mean, standard deviation)`.

If the `approximate` argument is set to `True`, the statistics may
be computed based on overviews or a subset of image tiles.

If the `refresh` argument is set to `True`, the statistics will be
computed from the data directly, and the cache will be updated with the
result.

If a persistent cache value is found, that value is returned. For
raster formats using Persistent Auxiliary Metadata (PAM) services, the
statistics might be cached in an auxiliary file. In some cases this
metadata might be out of sync with the pixel values or cause values
from a previous call to be returned which don't reflect the value of
the `approximate` argument. In such cases, use the `refresh`
argument to get updated values and store them in the cache.

For empty bands (where all pixel values are "no data"), all statistics
are returned as `None`.

The statistics can also be retrieved directly by accessing the
[`min`](#django.contrib.gis.gdal.GDALBand.min), [`max`](#django.contrib.gis.gdal.GDALBand.max), [`mean`](#django.contrib.gis.gdal.GDALBand.mean), and [`std`](#django.contrib.gis.gdal.GDALBand.std) properties.

#### `min`

The minimum pixel value of the band (excluding the "no data" value).

#### `max`

The maximum pixel value of the band (excluding the "no data" value).

#### `mean`

The mean of all pixel values of the band (excluding the "no data"
value).

#### `std`

The standard deviation of all pixel values of the band (excluding the
"no data" value).

#### `nodata_value`

The "no data" value for a band is generally a special marker value used
to mark pixels that are not valid data. Such pixels should generally not
be displayed, nor contribute to analysis operations.

To delete an existing "no data" value, set this property to `None`
(requires GDAL ≥ 2.1).

#### `datatype(as_string=False)`

The data type contained in the band, as an integer constant between 0
(Unknown) and 11. If `as_string` is `True`, the data type is
returned as a string with the following possible values:
`GDT_Unknown`, `GDT_Byte`, `GDT_UInt16`, `GDT_Int16`,
`GDT_UInt32`, `GDT_Int32`, `GDT_Float32`, `GDT_Float64`,
`GDT_CInt16`, `GDT_CInt32`, `GDT_CFloat32`, and `GDT_CFloat64`.

#### `color_interp(as_string=False)`

> **New in Django 2.0**

The color interpretation for the band, as an integer between 0and 16.
If `as_string` is `True`, the data type is returned as a string
with the following possible values:
`GCI_Undefined`, `GCI_GrayIndex`, `GCI_PaletteIndex`,
`GCI_RedBand`, `GCI_GreenBand`, `GCI_BlueBand`, `GCI_AlphaBand`,
`GCI_HueBand`, `GCI_SaturationBand`, `GCI_LightnessBand`,
`GCI_CyanBand`, `GCI_MagentaBand`, `GCI_YellowBand`,
`GCI_BlackBand`, `GCI_YCbCr_YBand`, `GCI_YCbCr_CbBand`, and
`GCI_YCbCr_CrBand`. `GCI_YCbCr_CrBand` also represents `GCI_Max`
because both correspond to the integer 16, but only `GCI_YCbCr_CrBand`
is returned as a string.

#### `data(data=None, offset=None, size=None, shape=None)`

The accessor to the pixel values of the `GDALBand`. Returns the complete
data array if no parameters are provided. A subset of the pixel array can
be requested by specifying an offset and block size as tuples.

If NumPy is available, the data is returned as NumPy array. For performance
reasons, it is highly recommended to use NumPy.

Data is written to the `GDALBand` if the `data` parameter is provided.
The input can be of one of the following types - packed string, buffer, list,
array, and NumPy array. The number of items in the input should normally
correspond to the total number of pixels in the band, or to the number
of pixels for a specific block of pixel values if the `offset` and
`size` parameters are provided.

If the number of items in the input is different from the target pixel
block, the `shape` parameter must be specified. The shape is a tuple
that specifies the width and height of the input data in pixels. The
data is then replicated to update the pixel values of the selected
block. This is useful to fill an entire band with a single value, for
instance.

Sebagai contoh:

```
>>> rst = GDALRaster({'width': 4, 'height': 4, 'srid': 4326, 'datatype': 1, 'nr_of_bands': 1})
>>> bnd = rst.bands[0]
>>> bnd.data(range(16))
>>> bnd.data()
array([[ 0,  1,  2,  3],
       [ 4,  5,  6,  7],
       [ 8,  9, 10, 11],
       [12, 13, 14, 15]], dtype=int8)
>>> bnd.data(offset=(1, 1), size=(2, 2))
array([[ 5,  6],
       [ 9, 10]], dtype=int8)
>>> bnd.data(data=[-1, -2, -3, -4], offset=(1, 1), size=(2, 2))
>>> bnd.data()
array([[ 0,  1,  2,  3],
       [ 4, -1, -2,  7],
       [ 8, -3, -4, 11],
       [12, 13, 14, 15]], dtype=int8)
>>> bnd.data(data='\x9d\xa8\xb3\xbe', offset=(1, 1), size=(2, 2))
>>> bnd.data()
array([[  0,   1,   2,   3],
       [  4, -99, -88,   7],
       [  8, -77, -66,  11],
       [ 12,  13,  14,  15]], dtype=int8)
>>> bnd.data([1], shape=(1, 1))
>>> bnd.data()
array([[1, 1, 1, 1],
       [1, 1, 1, 1],
       [1, 1, 1, 1],
       [1, 1, 1, 1]], dtype=uint8)
>>> bnd.data(range(4), shape=(1, 4))
array([[0, 0, 0, 0],
       [1, 1, 1, 1],
       [2, 2, 2, 2],
       [3, 3, 3, 3]], dtype=uint8)
```

#### `metadata`

> **New in Django 2.0**

The metadata of this band. The functionality is identical to
[`GDALRaster.metadata`](#django.contrib.gis.gdal.GDALRaster.metadata).

### Membuat raster dari data

This section describes how to create rasters from scratch using the
`ds_input` parameter.

A new raster is created when a `dict` is passed to the [`GDALRaster`](#django.contrib.gis.gdal.GDALRaster)
constructor. The dictionary contains defining parameters of the new raster,
such as the origin, size, or spatial reference system. The dictionary can also
contain pixel data and information about the format of the new raster. The
resulting raster can therefore be file-based or memory-based, depending on the
driver specified.

There's no standard for describing raster data in a dictionary or JSON flavor.
The definition of the dictionary input to the [`GDALRaster`](#django.contrib.gis.gdal.GDALRaster) class is
therefore specific to Django. It's inspired by the [geojson](http://geojson.org) format, but the
`geojson` standard is currently limited to vector formats.

Examples of using the different keys when creating rasters can be found in the
documentation of the corresponding attributes and methods of the
[`GDALRaster`](#django.contrib.gis.gdal.GDALRaster) and [`GDALBand`](#django.contrib.gis.gdal.GDALBand) classes.

#### Kamus `ds_input`

Only a few keys are required in the `ds_input` dictionary to create a raster:
`width`, `height`, and `srid`. All other parameters have default values
(see the table below). The list of keys that can be passed in the `ds_input`
dictionary is closely related but not identical to the [`GDALRaster`](#django.contrib.gis.gdal.GDALRaster)
properties. Many of the parameters are mapped directly to those properties;
the others are described below.

The following table describes all keys that can be set in the `ds_input`
dictionary.

| Kunci | Awalan | Penggunaan |
| --- | --- | --- |
| `srid` | diwajibkan | Dipetakan ke atribut [`srid`](#django.contrib.gis.gdal.GDALRaster.srid) |
| `width` | diwajibkan | Dipetakan ke atribut [`width`](#django.contrib.gis.gdal.GDALRaster.width) |
| `height` | diwajibkan | Dipetakan ke atribut [`height`](#django.contrib.gis.gdal.GDALRaster.height) |
| `driver` | `MEM` | Dipetakan ke atribut [`driver`](#django.contrib.gis.gdal.GDALRaster.driver) |
| `name` | `''` | Lihat dibawah |
| `origin` | `0` | Dipetakan ke atribut [`origin`](#django.contrib.gis.gdal.GDALRaster.origin) |
| `scale` | `0` | Dipetakan ke atribut [`scale`](#django.contrib.gis.gdal.GDALRaster.scale) |
| `skew` | `0` | Dipetakan ke atribut [`width`](#django.contrib.gis.gdal.GDALRaster.width) |
| `bands` | `[]` | Lihat dibawah |
| `nr_of_bands` | `0` | Lihat dibawah |
| `datatype` | `6` | Lihat dibawah |
| `papsz_options` | `{}` | Lihat dibawah |

#### `name`

String representing the name of the raster. When creating a file-based
raster, this parameter must be the file path for the new raster. If the
name starts with `/vsimem/`, the raster is created in GDAL's virtual
filesystem.

#### `datatype`

Integer representing the data type for all the bands. Defaults to `6`
(Float32). All bands of a new raster are required to have the same datatype.
The value mapping is:

| Nilai | Jenis Piksel GDAL | Deskripsi |
| --- | --- | --- |
| 1 | GDT\_Byte | Delapan bit integer tidak bertanda |
| 2 | GDT\_UInt16 | Enam belas bit integer tidak bertanda |
| 3 | GDT\_Int16 | Enam belas bit integer bertanda |
| 4 | GDT\_UInt32 | Tiga-puluh-dua bit integer tidak bertanda |
| 5 | GDT\_Int32 | Tiga-puluh-dua bit integer bertanda |
| 6 | GDT\_Float32 | Thirty-two bit floating point |
| 7 | GDT\_Float64 | Sixty-four bit floating point |

#### `nr_of_bands`

Integer representing the number of bands of the raster. A raster can be
created without passing band data upon creation. If the number of bands
isn't specified, it's automatically calculated from the length of the
`bands` input. The number of bands can't be changed after creation.

#### `bands`

A list of `band_input` dictionaries with band input data. The resulting
band indices are the same as in the list provided. The definition of the
band input dictionary is given below. If band data isn't provided, the
raster bands values are instantiated as an array of zeros and the "no
data" value is set to `None`.

#### `papsz_options`

> **New in Django 2.0**

A dictionary with raster creation options. The key-value pairs of the
input dictionary are passed to the driver on creation of the raster.

The available options are driver-specific and are described in the
documentation of each driver.

The values in the dictionary are not case-sensitive and are automatically
converted to the correct string format upon creation.

The following example uses some of the options available for the
[GTiff driver](http://www.gdal.org/frmt_gtiff.html). The result is a compressed signed byte raster with an
internal tiling scheme. The internal tiles have a block size of 23 by 23:

```
>>> GDALRaster({
...    'driver': 'GTiff',
...    'name': '/path/to/new/file.tif',
...    'srid': 4326,
...    'width': 255,
...    'height': 255,
...    'nr_of_bands': 1,
...    'papsz_options': {
...        'compress': 'packbits',
...        'pixeltype': 'signedbyte',
...        'tiled': 'yes',
...        'blockxsize': 23,
...        'blockysize': 23,
...    }
... })
```

#### Kamus `band_input`

The `bands` key in the `ds_input` dictionary is a list of `band_input`
dictionaries. Each `band_input` dictionary can contain pixel values and the
"no data" value to be set on the bands of the new raster. The data array can
have the full size of the new raster or be smaller. For arrays that are smaller
than the full raster, the `size`, `shape`, and `offset` keys  control the
pixel values. The corresponding keys are passed to the [`data()`](#django.contrib.gis.gdal.GDALBand.data)
method. Their functionality is the same as setting the band data with that
method. The following table describes the keys that can be used.

| Kunci | Awalan | Penggunaan |
| --- | --- | --- |
| `nodata_value` | `None` | Dipetakan ke atribut `nodata_value` |
| `data` | Sama seperti `nodata_value` atau `0` | Dilewatkan ke metode [`data()`](#django.contrib.gis.gdal.GDALBand.data) |
| `size` | `(with, height)` dari raster | Dilewatkan ke metode [`data()`](#django.contrib.gis.gdal.GDALBand.data) |
| `shape` | Sama seperti ukuran | Dilewatkan ke metode [`data()`](#django.contrib.gis.gdal.GDALBand.data) |
| `offset` | `(0, 0)` | Dilewatkan ke metode [`data()`](#django.contrib.gis.gdal.GDALBand.data) |

### Using GDAL's Virtual Filesystem

GDAL has an internal memory-based filesystem, which allows treating blocks of
memory as files. It can be used to read and write [`GDALRaster`](#django.contrib.gis.gdal.GDALRaster) objects
to and from binary file buffers.

This is useful in web contexts where rasters might be obtained as a buffer
from a remote storage or returned from a view without being written to disk.

[`GDALRaster`](#django.contrib.gis.gdal.GDALRaster) objects are created in the virtual filesystem when a
`bytes` object is provided as input, or when the file path starts with
`/vsimem/`.

Input provided as `bytes` has to be a full binary representation of a file.
For instance:

```
# Read a raster as a file object from a remote source.
>>> from urllib.request import urlopen
>>> dat = urlopen('http://example.com/raster.tif').read()
# Instantiate a raster from the bytes object.
>>> rst = GDALRaster(dat)
# The name starts with /vsimem/, indicating that the raster lives in the
# virtual filesystem.
>>> rst.name
'/vsimem/da300bdb-129d-49a8-b336-e410a9428dad'
```

To create a new virtual file-based raster from scratch, use the `ds_input`
dictionary representation and provide a `name` argument that starts with
`/vsimem/` (for detail of the dictionary representation, see
[Membuat raster dari data](#gdal-raster-ds-input)). For virtual file-based rasters, the
[`vsi_buffer`](#django.contrib.gis.gdal.GDALRaster.vsi_buffer) attribute returns the `bytes` representation
of the raster.

Here's how to create a raster and return it as a file in an
[`HttpResponse`](/id/2.0/ref/request-response/#django.http.HttpResponse):

```
>>> from django.http import HttpResponse
>>> rst = GDALRaster({
...     'name': '/vsimem/temporarymemfile',
...     'driver': 'tif',
...     'width': 6, 'height': 6, 'srid': 3086,
...     'origin': [500000, 400000],
...     'scale': [100, -100],
...     'bands': [{'data': range(36), 'nodata_value': 99}]
... })
>>> HttpResponse(rast.vsi_buffer, 'image/tiff')
```

## Pengaturan

### `GDAL_LIBRARY_PATH`

A string specifying the location of the GDAL library.  Typically,
this setting is only used if the GDAL library is in a non-standard
location (e.g., `/home/john/lib/libgdal.so`).

## Pengecualian

#### `exception GDALException`

The base GDAL exception, indicating a GDAL-related error.

#### `exception SRSException`

An exception raised when an error occurs when constructing or using a
spatial reference system object.