I need to store Multipolygon data in Datastax Graph. They do support some of geo data types like point, line String and polygon . Do they support Multipolygon.
Could you please help with this
DSE Graph does not support explicit Multipolygon data types.
If you don't mind sharing, what types of issues/challenges does Multipolygon help you solve?
Related
I have four sets of data which have been created in dictionaries. After plotting them in one graph it is hard to clearly differentiate the point.
I put all of the data frames in one graph. My intention is to zoom in data points without changing x values that one can see the difference.
Please, help me in this regard. Thank you!
Graph Describes 4 sets of data
I've been learning how to use Cartopy and Matplotlib to plot map. But I have a question regarding the argument transform. According to the Cartopy document, transform specifies "what coordinate system your data are defined in". Suppose I am going to plot temperatures of an area, and the area has been split into several grid cells. Each grid cells has a corresponding coordinate defined in lat and lon (Geodetic Systems). Based on the Cartopy document, I need to use crs.PlateCarree() instead of crs.Geodetic(). I'm a bit confused about it. Because,I think the PlateCarree is a way of projection. In other words, coordinates defined in PlateCarree projections are projected data. But latitude and longitude should be unprojected data. Can anyone help me with it? Thanks!
I am using this query to extract the geometries of all countries using BigQuery public dataset, see question here
how to extract all countries geometry from Openstreet map dataset in BigQuery
I use R to draw the results
I tried Kepler.GL and gave me the same results
Something is wrong with Russia and the USA
I know little about R visualization, but what is probably happening is you getting WKT text from BigQuery, and feeding it to R, which has different assumptions.
Tthe issue is your R package probably treats WKT differently than BigQuery. WKT semantics depends on the spatial reference system (SRS) used, which could be geographic (non-projected, using sphere or ellipsoid) or projected (flat map). BigQuery uses geographic system, so edge between points A and B is the shortest geodesic path. Most visualization systems use projected coordinates, and assume flat map. Edge between A and B is shortest straight line on the flat map.
While this does not matter too much in many cases, it still does affect precision when you have long edges. But when an edge crosses anti-meridian (180 degree meridian) you get big problem. An edge between (-169, 66) (eastern edge of Russia) and say (176, 70) (a nearby point on Chukchi sea) is relatively short on the sphere, it crosses anti-meridian, and spans 15 degrees longitude. But the same edge on flat map span 145 degrees longitude and crosses most of the map! These are the long near-horizontal lines you see.
What should you do?
If R has a packet that supports geographic SRS (it is sometime an option to use geodesic edges), you could try it.
Or you can also let BigQuery convert geography from geographic SRS to flat map, that R would understand, using ST_AsGeoJson function. GeoJson is defined on flat map, so BigQuery ST_AsGeoJson converts the semantics from geographic SRS to flat map SRS. You then visualize GeoJson string instead of WKT string in R.
ST_AsGeoJson does a lot of work, to make result conformant to GeoJson spec and flat map. It splits parts of geography that lay east and west of anti-meridian, so you don't get edges that cross it. It also approximates geodesic edges with flat map edges. But it makes visualization system much easier.
I am trying to extract decimal degrees data from a shapefile using the QGIS software but no luck. I am using the field calculator method where i create a new double field then select Geometry then $x and $y but am still getting data in this format 247152.338941123. Have set the CRS layer to WGS84 but no luck. Please if you know what am doing wrong, help me. Thanks
From the values returned it seems that your layer is stored as a projected coordinate system. Try saving the layer as a geographic coordinate system (EPSG:4326) and it should work.
I have some data defined on a sphere (a sphere not the earth): is it possible with Python 2.6 and matplotlib to draw them on map (of the type of Mercator map) "automatically" or do I have to project the data?
Edit: All of my data are lat-long.
It really depends on what you have and what you want: x-y and/or lat-lon? It looks like your question is similar to a problem I had and more-or-less answered:
matplotlib and apect ratio of geographical-data plots
Consider using set_aspect(), using the reciprocal of the mean latitude of your data.
See matplotlib and apect ratio of geographical-data plots for a working example.