It can be used to input raster data into your application. In most cases there is one RasterLayer for each raster file. Raster files can be uploaded through the admin interface and are stored in the RasterLayer model. Like for any other model, raster layers can also be created using the Django shell.
Each raster file corresponds to one RasterLayer object. When adding a new raster file, the following properties are required :. The datatype tells django-raster how to interpret the pixel values.
By default, django-raster extracts all other raster metadata from the input file. The optional input parameters are the following. The srid, the nodata value and the maximum zoom value are all determined automatically from the raster properties if left blank.
The max zoom value specifies the highest z-x-y zoom level to create tiles for see below. The legend attribute is a foreign key to a raster Legend object.
If the raster legend is specified, it is used as default style when rendering tiles from that raster. How raster tiles are rendered is described in detail in the Rendering tiles section. There are also three boolean flags that allow finer grained control over the raster layer parse process. This is enabled by default and is recommended in most cases as the tile renderer will expect those tiles to be present. During parsing, the raster is reprojected to the web mercator projection.
This operation is costly and is only done once by default. Django-raster stores a reprojected version in a separate model. Note that this will result in less use of storage, but an overhead when parsing, especially for asynchronous parsing where the file will be reprojected by each worker.
The raster file can be uploaded directly using the raster file field, or passed as a url either to a public http s address, or a url like string, pointing directly to an s3 bucket. The http s urls are regular web urls. For the s3 links, the boto3 library is used to directly access an s3 bucket and download it from there. In this way, private or requester-pays buckets can be used as source. The credentials for accessing the buckets need to be configured so that boto3 can see them.
Note that for requester pays bucket this might incur charges even if the requester is not the owner of the bucket. Upon uploading a file, django-raster automatically parses the raster file. The parser extracts metadata from the raster and its bands, and creates tiles. The progress or possible errors in parsing is written to a parse log object, which is exposed on the RasterLayer admin interface. The parser automatically creates a tile pyramid in the z-x-y scheme of a TMS.
It only takes a minute to sign up. GeoDjango does not currently support raster files. Even if your database supports raster data, there are no Python hooks into that functionality provided by GeoDjango. However, you can still work with raster data in a Python framework that includes GeoDjango. You'll just need another tool for working with raster data, such as rasterioraster2pgsqlor by using the Python bindings for GDAL.
If you wish to store raster data in a database, be aware that few databases will allow you to store raster data as anything other than a BLOB.
Again, as GeoDjango doesn't recognize raster manipulation functionality in the database, you'll need to perform raw SQL queries with Django. The code example above just delivers the raster as a file attachment. For displaying rasters on the front-end browser-side of your web application, you'll need a way to display raster data, but that is another discussion e.
I started working on developing some raster functionality within Django. There are two packages that I am working on, one that allows loading raster data into Django, and another one that allows serving raster through a Tile Map Service or a Web Map Service. Here is a page that uses these packages for raster rendering through Leaflet as xyz tile layers.
Please take all of this with a grain of salt. The python packages are in early stage development, so please take that into consideration if you want to try them out. Any feedback would be appreciated of course. And apologies for the self-advertising, but I figured this might be interesting for some of you. As of version 1. Sign up to join this community. The best answers are voted up and rise to the top.
You will need something to tile the raster and then serve these as tiles to Leaflet as if it was a background map. You probably want to use Geoserver or something similar to do this. Sign up to join this community. The best answers are voted up and rise to the top. Home Questions Tags Users Unanswered. GeoDjango raster field display on Leaflet Ask Question.
Asked 1 year, 8 months ago. Active 3 months ago. Viewed times. RasterField all works fine without error. How do I display this raster in some web map like Leaflet? Vince Mar Mar 3 3 silver badges 11 11 bronze badges. Active Oldest Votes. Alexander Alexander 8 8 silver badges 13 13 bronze badges.
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Community and Moderator guidelines for escalating issues via new response…. Feedback on Q2 Community Roadmap.Spatial fields consist of a series of geometry field types and one raster field type. There is no such standard for raster data.
In addition to the regular Field options available for Django model fields, spatial fields have the following additional options. All are optional. Defaults to also known as WGS84units are in degrees of longitude and latitude. Choosing an appropriate SRID for your model is an important decision that the developer 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.
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.
However, latitude and longitude are angles, not distances. In other words, while the shortest path between two points on a flat surface is a straight line, the shortest path between two points on a curved surface such as the earth is an arc of a great circle. Using a geographic coordinate system may introduce complications for the developer later on.
For example, SpatiaLite does not have the capability to perform distance calculations between geometries using geographic coordinate systems, e.
Projected coordinate systems are especially convenient for region-specific applications, e. Moreover, projected coordinate systems are defined in Cartesian units such as meters or feeteasing distance calculations. Defaults to True.
Creates a spatial index for the given geometry field. Specifically, spatial indexes are typically created using a variant of the R-Tree, while regular database indexes typically use B-Trees. There are additional options available for Geometry fields. All the following options are optional. This option may be used for customizing the coordinate dimension of the geometry field.
By default, it is set to 2, for representing two-dimensional geometries. For spatial backends that support it, it may be set to 3 for three-dimensional support. If set to Truethis option will create a database column of type geography, rather than geometry.
Please refer to the geography type section below for more details. The geography type provides native support for spatial features represented with geographic coordinates e. Distance and measurement operations performed on a geography column automatically employ great circle arc calculations and return linear units.
Because geography calculations involve more mathematics, only a subset of the PostGIS spatial lookups are available for the geography type. Practically, this means that in addition to the distance lookups only the following additional spatial lookups are available for geography columns:.Opened 5 years ago. Closed 5 years ago. Last modified 3 years ago. Raster integrations is becoming stronger for database back-ends such as PostGIS, so an integration of raster data into Django would open new possibilities for online mapping.
Handling raster data in online environments is currently hard to accomplish and integration into a web framework would make this easier in many cases. Adding a RasterField makes sense as a first step to handling raster data input and output.
Spatial querying and other operations could then be built on top of that. Now I was thinking of moving the module to master and starting to write the documentation for it. But I am not sure if it would be better to integrate it directly into the contrib. In the gdal. I think that we could aim for more integration with main gdal module. For example, when I compare driver.
Maybe the other files could be left in a raster module. These are just quick thoughts, without deep looking in the code. In 4df3a3e0e9bfcd64a3e2eb85e0dd7b8f4f6e :.
Refs In 00fad7d2dbdaea9fe09f36bff77c7 :. Based on Daniel Wiesmann's work. I branched off master and started integrating the raster files into the structure with the new driver. I followed your suggestions above. The new branch is this one:. Both are related to lazy-instanciation of field target instances Rasters or Geometries. I've prepared a new small step, with the following patch.
I've deliberately chosen some different paths from your branch. It's not to contradict you by pleasure :-I may totally be wrong or naive with certain choices, but I'm trying to create the most Pythonesque API as possible. Feel free to criticize and contradict me in return! Just had a quick look, this is awsome, its very clean like this.
I can't resist to add a quote of a movie I saw the other day:. It's your limitations that make you the wonderful disaster that you most probably are. For me that is where collaboration comes in.
It only takes a minute to sign up. This structure can be used directly in online mapping software such as OpenLayers or Leaflet. In your code example you create your own raster model. That is not compatible with the functionality of the django-raster package. The goal of django-raster is to avoid having to create and manage raster models. Then the raster files itself should be stored using the RasterLayer model that comes with the django-raster package.
The easiest way to add your image is to use the django admin site.
Simply create a new RasterLayer in the admin and upload your file using the rasterfile field. So to display your raster data you don't need to write much code, just configure django-raster in your Django project and start using its functionality such as ingesting and displaying raster data. Sign up to join this community.
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Asked 1 year, 9 months ago. Active 7 months ago. Viewed times. TextField add raster using console : from django. Massimiliano Moraca 1 1 silver badge 11 11 bronze badges. Mar Mar 3 3 silver badges 11 11 bronze badges. Active Oldest Votes. Sign up or log in Sign up using Google. Sign up using Facebook. Sign up using Email and Password. Post as a guest Name. Email Required, but never shown. The Overflow Blog. The Overflow How many jobs can be done at home? Featured on Meta. Community and Moderator guidelines for escalating issues via new response….
I found Geodjango read raster files from 3 years ago, as well as some sparse documentation for django-rasterbut no real examples or tutorials of how to use the module.
The code I have:. How to use rasters in Django depends on your use case of course. In the simplest case, if your rasters are relatively small and do not need tiling, you can simply declare a model with a raster field and assign rasters to it. Loading a raster into postgis is as simple as that. Note that like that every time you will get one instance of the RasterWithName model, it will load the entire raster. This works fine for smaller rasters, but for large ones this might be clunky, depending on how you want to use it.
Saving one model instance does load the data into postgres, its not more complicated than that. However, you still do not have views or url endpoints to render the raster on the web. You can use external software to serve the rasters such as mapserver for instance. If you want to stay within the Django universe, I would use the django-raster package. It has a tiling engine, which splits your rasters into tiles instead of loading them as one object.
It also has a views and url endpoints that are useful to display the rasters in a web map through a z-x-y tile scheme. The main limitation of the django-raster package at the moment is that it always stores the raster in the Web Mercator projection srid To use django-raster, install the package and then create a RasterLayer object through the admin interface. When creating a raster layer you can upload your raster file in the rasterfile field.
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The parsing of the raster layer can be a long process if the file is large. For larger rasters, the parsing during web request might time out. You can configure your application to use celery for asynchronous parsing see this section of the installation. Alternatively, you can create your raster layers in the django shell instead of using the admin interface.
Well the GeoDjango tutorial has all the useful information about how to use it. From version 1.