I am having trouble understanding the documentation on geodjango. First of all using the zipcode example:
class Zipcode(models.Model):
code = models.CharField(max_length=5)
poly = models.PolygonField()
objects = models.GeoManager()
Is PolygonField where I would store the actual long/lattitude coordinates of the zipcode? The other question is how would I actually translate the zipcode into those coordinates? That is the one step I cannot figure out how to do.
I assume I'm going to need to convert the zipcode into coordinates and then compare those against other coordinates to determine 'nearest zipcodes to location x', which is what I'm trying to do.
On a side note, I found https://github.com/coderholic/django-cities, which seems like I would be able to accomplish this WITHOUT converting zipcodes into coordinates, but there isn't really any documentation, so I have no idea.
GeoDjango does not handle converting zip codes into locations: that's simply not what it's for. You'll need a geocoding library, a Google search should reveal plenty.
The project you link to simply uses an existing set of geocoded data for cities and zip codes, and even tells you where to get it - see the relevant management command.
Related
I am running a django application and I am using the PostGis extension for my db. I am trying to understand better what happens under the hood when I send coordinates, especially because I am working with different coordinate systems which translate to different SRIDs. My question is threefold:
Is django/postgis handling the transformation when creating a Point or Polygon in the DB.
Can I query it back using a different SRID
Is it advisable to use the default SRID=4326
Let's say I have a model like this (note I am setting the standard SRID=4326):
class MyModel(models.Model):
name = models.CharField(
max_length=120,
)
point = models.PointField(
srid=4326,
)
polygon = models.PolygonField(
srid=4326,
)
Now I am sending different coordinates and polygons with different SRIDS.
I am reading here in the django docs that:
Moreover, if the GEOSGeometry is in a different coordinate system (has a different SRID value) than that of the field, then it will be implicitly transformed into the SRID of the model’s field, using the spatial database’s transform procedure
So if I understand this correctly, this mean that when I am sending an API request like this:
data = {
"name": "name"
"point": "SRID=2345;POLYGON ((12.223242267 280.123144553))"
"polygon": "SRID=5432;POLYGON ((133.2345662 214.1429138285, 123.324244572 173.755820912250072))"
}
response = requests.request("post", url=url, data=data)
Both - the polygon and the point - will correctly be transformed into SRID=4326??
EDIT:
When I send a point with SRID=25832;POINT (11.061859 49.460983) I get 'SRID=4326;POINT (11.061859 49.460983)' from the DB. When I send a polygon with 'SRID=25832;POLYGON ((123.2796155732267 284.1831980485285, ' '127.9249715130572 273.7782091450072, 142.2351651215613 ' '280.3825718937042, 137.558146278483 290.279508688337, ' '123.2796155732267 284.1831980485285))' I get a polygon 'SRID=4326;POLYGON ((4.512360573651161 0.002563158966576373, ' '4.512402191765552 0.002469312460126783, 4.512530396754145 ' '0.002528880231016955, 4.512488494972807 0.00261814442892858, ' '4.512360573651161 0.002563158966576373))' from the DB
Can I query it back using a different SRID
Unfortunately I haven't found a way to query the same points back to their original SRID. Is this even possible?
And lastly I am working mostly with coordinates in Europe but I also might have to include sporadically coordinates from all over the world too. Is SRID=4326 a good standard to use?
Thanks a lot for all the help in advance. Really appreciated.
Transforming SRS of geometries is much more than just changing their SRID. So, if for some reason after a transformation the coordinates return with exactly the same values, there was most probably no transformation at all.
This example uses ST_Transform to transform a geometry from 25832 to 4326. See the results yourself:
WITH j (geom) AS (
VALUES('SRID=25832;POINT (11.061 49.463)'::geometry))
SELECT ST_AsEWKT(geom),ST_AsEWKT(ST_Transform(geom,4326)) FROM j;
st_asewkt | st_asewkt
---------------------------------+------------------------------------------------------
SRID=25832;POINT(11.061 49.463) | SRID=4326;POINT(4.511355210946569 0.000446125446657)
(1 Zeile)
The Polygon transformation in your question is btw correct.
Make sure that django is really storing the values you mentioned. Send a 25832 geometry and directly check the SRS in the database. If you're only checking using django, it might be that it is transforming the coordinates back again in the requests, which might explain you not seeing any difference.
To your question:
Is SRID=4326 a good standard to use?
WGS84 is the most used SRS worldwide, so I'd tend to say yes, but it all depends on your use case. If you're uncertain of which SRS to use, it might indicate that your use case does not impose any constraint to it. So, stick to WGS84 but keep in mind that you don't mix different SRS in your application. Btw: if you try to store geometries in multiple SRS in the same table, PostgreSQL will raise an exception ;)
Further reading: ST_AsEWKT, WGS84
First of all, I'm not big expert at GIS (I have created just a few small things in Django and GIS), but...
In this documentaion about GeoDjango: https://docs.djangoproject.com/en/3.1/ref/contrib/gis/tutorial/#automatic-spatial-transformations . According to it:
When doing spatial queries, GeoDjango automatically transforms geometries if they’re in a different coordinate system. ...
Try in console (./manage.py shell):
from <yourapp>.models import MyModel
obj1 = MyModel.objects.all().first()
print(obj1)
print(obj1.point)
print(dir(obj1.point))
print(obj1.point.srid)
--edit--
You can manually test converting between SRID similary to this page: https://gis.stackexchange.com/questions/94640/geodjango-transform-not-working
obj1.point.transform(<new-srid>)
I am trying to plot a simplified map for pedestrians in my university campus using Osmnx library with python 2.7.
So far, I have this Image of the plot and as you can see, it is plotting sidewalks on both sides of the street. I was planning on removing one side of the sidewalks from this.
However I'm confused what logic to approach this with?
So far, I have created a custom filter to plot only footways
custom_walk = ('["area"!~"yes"]["highway"="footway"]["foot"!~"no"]["service"!~"private"]{}').format(ox.settings.default_access)
G = ox.graph_from_bbox(top, bottom,right, left, custom_filter= custom_walk)
ox.plot_graph(G_projected,save = True,filename = "maps", show = False,node_size=5,node_color='#FFFFFF',node_edgecolor='#FFFFFF',edge_color='#cccccc',bgcolor = "#000000",node_zorder=3,dpi=300, edge_linewidth=5,use_geom=True)
ox.simplify.clean_intersections(G,tolerance=100)
What I am trying to understand is does Osmnx have relations for footways in a way that will tell me their relative position to the nearest street (if they are on the east or the north side of the street (that way I can keep a standard on what sidewalks are visible)? Or if there is a simpler logic at this?
Thanks!
What I am trying to understand is does Osmnx have relations for footways in a way that will tell me their relative position to the nearest street (if they are on the east or the north side of the street (that way I can keep a standard on what sidewalks are visible)? Or if there is a simpler logic at this?
The answer is no, OSMnx doesn't know where the sidewalk is in relation to the nearest street. One option might be to just identify the sidewalk edges you don't want, make a list of their OSM IDs, then remove them from the graph.
I have tried to find a lot over the Internet but I am unable to get a perfect utility/API for my requirement.
I am interested in getting the latitude, longitude values of all areas in a city.
Currently i am using this google maps api
https://developers.google.com/maps/documentation/geocoding/start
But, when i enter a city name, it is giving only one lat-long pair for that city. Is there any way that if i give a city name, i can get all the areas and their corresponding latitude, longitude values?
Thanks.
There's a nice documentation for this at: Places API
I used this to get the latitude / longitude for one of my own projects and I also have an example of this.
If you look at the example, you can just type a location and it will immediately get the lat / long of the location and zoom in, you can also do this for more locations at the same time. Remember there is a limit for the maps api so it can only process so many data at the same time. Hope this may help you out! :)
I want to build a website with a map based on openstreetmap that colors buildings based on a their potential average annual yield of solar power. I have the energy data for individual houses.
My question is now, can I assign each house (identified by street name and number) a value and the house can then be colored based on this value in the browser?
I have little to no experience with openstreetmap and would be happy about hints into the right direction.
So you need a OSM dataset and filter it for building=* ways to get the building outlines (e.g. with osmosis). Then you do create a second run to filter for addr:= tags of nodes and merge them with the building outlines from step 1. Be aware of conflicts and that one building can have multiple addresses. So now you have a dataset with normalized addresses and need to create a lookup structure like hashmap to get a mapping for your solar data: addr:street x addr:housenumber -> building id
(very raw idea on how to do it)
IMHO the mixing of external datasources to the copyleft open database license makes that you need to relicense your dataset also under ODbL.
Also keep in mind that not every address is currently at OSM and the existing ones can be wrong!
How can I implement yelp like search?
There are 2 types of searches on yelp.
Simple search using the zip code, city and state in U.S.
I'm using PostgreSQL and wonder if there is good dataset that I can use that has city, state and zip code. I was hoping to find a good geo shape file and use geoDjango where I can just use, say Store.objects.filter(coordinates__in=cityNameORZipCode).
There seem to be some zip code database that I can use, but I really don't know where I can find a good city, state. The last option is to create my own cityname and state table and link to Stores, but not sure if this is smart thing to do.....hm.
Yelp has map search.
If you zoom in or out the google map, it searches local businesses according to the map area you are viewing. Think this is amazing. How can I do this?
It's looking dark right now. Please shed me some light.
You're asking a very broad and unanswerable question, but a good place to start for data in the U.S. is at the Census Bureau. For example:
State and State Equivalent Areas
County and County Equivalent Areas
The full list:
http://www.census.gov/geo/www/cob/bdy_files.html