SELECT ST_Force_2D(the_geom) FROM...
Update your existing table
ALTER TABLE your_geo_table ADD geom2d geometry;
UPDATE your_geo_table SET geom2d = ST_Force_2D(the_geom);
See also http://postgis.net/docs/
You should be able to do this with ST_Force2D
This is the example from the manual:
SELECT ST_AsEWKT(ST_Force2D('POLYGON((0 0 2,0 5 2,5 0 2,0 0 2),(1 1 2,3 1 2,1 3 2,1 1 2))'));
POLYGON((0 0,0 5,5 0,0 0),(1 1,3 1,1 3,1 1))
It might be possible to use a CAST operator as well (...
If you don't want to add a new column you can also do the following:
ALTER TABLE your_geo_table
ALTER COLUMN geom TYPE geometry(YOUR_GEOM_TYPE, YOUR_EPSG)
ALTER TABLE your_geo_table
ALTER COLUMN geom TYPE geometry(MULTILINESTRING, 4326)
If you examine the answer of afalciano in Converting projected coordinates to lat/lon using Python?
1) you define the two projections
# original projection
p = pyproj.Proj("+proj=stere +lat_0=90 +lat_ts=60 +lon_0=-105 +k=90 +x_0=0 +y_0=0 +a=6371200 +b=6371200 +units=m +no_defs")
# resulting projection, WGS84, long, lat
You can use projectRaster() to resample to a new resolution (also extent and CRS):
r2resampled <- projectRaster(r2,r1,method = 'ngb')
r3resampled <- projectRaster(r3,r1,method = 'bilinear')
The first one is categorical, so it's necessary to use nearest neighbor as method (ngb). The second one is numeric, so you can use bilinear (bilinear) or nearest ...
dimension(): refers to the topological dimension (i.e. point/line/area)
coordinateDimension(): returns the dimension of the tuple as given (as statet in the OP)
spatialDimension(): returns the dimension of the tuple without the measurement part (with "M" being the measurement in a linear reference system)
As it's pretty obvious for a 2D or "4D" literal, you ...
For unifying dimensions and resolutions of rasters, resample() function from Raster package works well for me:
r1 <- raster("Animal.tif")
r2 <- raster("LandTrans.tif")
r3 <- raster("TempJan.tif")
r1 <- resample(r1,r3)
r2 <- resample(r2,r3,method='ngb')
rs <- stack(r1,r2,r3)
basically use TIME=value& at the end of the WMS request. For a range of values you need to use TIME=start/end&. If you look in the GetCapabilities response you will see the values of time that will work.
See this tutorial for a brief explanation.
You need to use a projection that supports a meter unit such as WGS 84 UTM Zone ## N/S (depending on the site location in which country, you need to specify the zone number and in which hemisphere N OR S). Then do the following steps:
Select Advanced Digitizing Panel by right-click anywhere on the tools menu bar to enable the panel:
Click on Add Polygon ...
Specifically, the QGIS 3 tool is called Drop m/z values. It's in the Processing Toolbox, under Vector Geometry. The documentation is here:
By definition, a line is a single segment connected by two points. It has one dimension - length.
A linestring is made by joining several lines. Each of the lines have a single dimension, however, because the joined lines can change direction, they now have a second dimension - length and width, much like a polygon.
If you think of a simple curve, such ...
If you want to create 6x6 square buffers around your points you need to give an option of width = 3 in gBuffer. Because the width is the distance radio r from the center.
Try the reproducible example below:
# Load packages
# Define projection
epsg.32721 <- "+proj=utm +zone=21 +south +datum=WGS84 +units=...
Thanks for the comments. However, I figured out that the problem was related to a missed call of meshgrid. By doing this I was able to run my code and generate the right lon/lat arrays.
xv, yv = np.meshgrid(x, y)
p = pyproj.Proj("+proj=stere +lat_0=90 +lat_ts=60 +lon_0=-105 +k=90
Of the three opinions expressed so far, yours, Benjamin, makes the most sense to me:
X, Y and Z are spatial dimensions and M is some other coordinate/dimension.
Disclaimer: I've never heard of those function names (coordinateDimension and spatialDimension) before so I'm no authority. And I'm not sure I could claim any bounty if ever I'm proved correct!
I know that PostGIS have a multipoint object, but all example that I have seen on the web are limited to 4D. Is it possible to use this structure to store multiple concentrations in addition of space and time. If so, is there a simple way to get rid of extra dimensions such as concentrations and time, when we are just working on space? If I want to post ...
As you have experienced, Raster -> Projections -> Warp (Reproject)... is the right way to reproject with good results.
Save As ... is useful for vector data, or just saving to the same raster format under a different name or folder.
Your use of the term "dimensions" makes me think you're used to engineering design programs like AutoCAD, where you can add measurements like this:
QGIS doesn't have quite the same feature. It also doesn't use the term "dimensions." So if you tried to search for how to do this, you probably had very little success. Here are some ways you can add dimensional ...
You will need to install Crayfish plugin, which will add some Mesh algorithms in the QGIS Processing Toolbox.
(1) Load the NetCDF file as a mesh layer, by Menu > Layer > Add Layer > Add Mesh Layer and select your NetCDF file (.nc).
(2) Please follow steps in a picture below:
Prepare a point shapefile at your intended research location.
As @user2856 said, I was getting the number of dims the tuple unpacking code was expecting.
In order to get the right amount of dims, I ran
The output was
(<class 'netCDF4._netCDF4.Dimension'>: name = 'time', size = 94750, <class 'netCDF4._netCDF4.Dimension'>: name = 'expver', size = 2, <class 'netCDF4._netCDF4.Dimension'...
The issue may lie in the fact of the format of your input:
Input coordinates can be given as python arrays, lists/tuples, scalars or numpy/Numeric/numarray arrays. Optimized for objects that support the Python buffer protocol (regular python and numpy array objects).
Python interface to PROJ.4 library
Performs cartographic transformations and geodetic ...
The problem seems to be that GeoTools thinks that your packages coordinate system is infinitely wide and high which throws off some of the later calculations and leads to a bounding box which is NaN by NaN and hence the error.
I suspect that this is a bug so if you could file one including this test case and the geopackage, some one will look at it.
There was a bug in placing the tileorigin into bottom-left while it should be in top-left that was originally reported by GDAL developer
and next faulty noticed by GeoServer developer as a GDAL bug
which finally lead to fixes in both ...
Here is how i convert a QgsGeometry (geom) of type PolygonZ to a Polygon in the console:
new_geom = QgsGeometry().fromPolygonXY(geom.asPolygon())
It is some kind of workaround since there is no dedicated method for that. So i dont know if there are better ways to do it. Using the processing tool as recommended in the other answers would be the correct way ...
First within the CARTO Editor, go to the infowindow (iw) tab and click on </>. This HTML panel would allow you to customize in detail your in. And the CSS style parameter that allows you to change the iw height is max-height. Add and set this parameter to the style attribute to your needs. Your iw should look similar to this one:
I can't test this, but as a educated guess:
from django.contrib.gis.gdal import OGRGeometry
ds = DataSource(options['filename'])
for layer in ds:
for i in layer:
ogrgeom = OGRGeometry(i.geom) # Make an OGRGeom object from the string representation
ogrgeom.z = None # This is now a 2 dimensional geometry object with no Z ...
I believe that the the preview tool is meant to be a way to quickly look at the data and styling for the admin, it's not intended for customization as far I as know.
The documentation on the layer preview page provided on the geoserver website doesn't provide any methods on how to change the layer preview page width and height values as far as I could find....
In GIS, there is a concept for POINT, LINE and POLYGON (in a vector sense). There's no concept of LINE MADE OF POINTS, or SEQUENTIAL MULTI-POINT.
A multi-point dataset is simply many points grouped together with one set of attribute for the group.
For what you want to do, I think you just want to have something like:
id, station_id, datetime, geometry, ...