You need to match the lenghts of your fields. To achieve that, go to Processing -> Refactor Fields
Select you layer with the too short field as input, map it to your "longer" layer and run it. The resulting layer should be mergeable with your original "long" layer.
If these are lines in the 2D Layers group, and are "screen sized" (e.g. size in pixels) then it appears what you are seeing is a lower-resolution rendering of the same line, in the next rasterized tile.
Can you send this in as a BUG to Esri Support, along with a map package (mpkx) (from share->Map package) so that we can troubleshoot and ...
It seems you are using point layers, are your geometries exactly coincident for the points you expect to join? For point geometries with several decimal figures, especially after reprojecting, it may be that they do not intersect. You could try Join by nearest and then filter out any joins that are above an acceptable distance threshold.
As was mentioned by @Matt there is corresponding algorithm for that i.e. "Basic statistics for fields", that can be launched from Python Console using PyQGIS.
Let's assume there are two layers 'groupe_layers' and 'groupe_layers_copy' with corresponding attribute tables, see image below.
My target field is the "AREA_HA" for which the ...
Create a virtual field that checks if start- and endpoint are on a line segment. Then you have two options:
Set "hard" restraints - adding an unconnected line is not possible. Only lines connected at start- and endpoint will be added.
No restraints for adding lines, but unconnected lines will be highlighted visually until you connect ...
The question asks to solve a number of steps in a bigger problem, which is to produce the Fresnel ellipsoid given the latitudes, longitudes and altitudes of the two end points. This answer considers the original problem as a whole. The following R function fresnelellipsoid_kml creates a kml file of the Fresnel ellipsoid between the two endpoints. The ...
First create 50 squares with Geometry by expression. Then split the layer, based on the area of the squares to get individual layers for each size.
To create 50 squares with side lenghts 10, 20, 30, ... 500, centered at the points of a point layer, you can use QGIS expressions with Geometry by expression (see here for details). ...
Ok so first a disclaimer, I don't know R. But the solution I provide is not code related. Moreover, I think your question is (not a bad one but) a "nested" one : answering it completely implies to ask and answer other sub-questions and write a lot of sub-functions to come up with a template, so I will try to give you the major steps I ...
The model simply takes an input (point) layer and the Create wedge buffers algorithm. There, set Input layer to Using model Input and set it to the input created.
For Azimuth (and Wedge width, if you like), use the default Value setting from the drop down menu, at the end of the line click on Data driven override / Edit... and type the name of the field you ...
Somehow, using tools like Wedge_buffer or Buffer, setting parameters (like distance, azimuth or width) based on attribute fields does not seem to work.
For this reason, a very simple way is to use Geometry by expression to create geometries using QGIS expressions. The model is extremely simple as you can see on the screenshot. Use this expression to create ...
You can do this if you create the buffers either with Virtual layer or Geometry generator.
Virtual layer: does create actual geometries. Use this query:
select st_buffer (p.geometry, b.size)
from point as p, buffersize as b
where p.id = b.id
Replace point with the name of the layer containing the geometries that you want to buffer.
Replace buffersize with ...
Finally I found the solution and I want to share it with you if anyone has the same problem.
You should use this option: iterate over this layer to split by each polygon in vector layer like this caption
There are tools Raster pixels to points and Raster pixels to polygons in the QGIS Processing toolbox. With these tools you can can convert your raster data into vector data and then you can add your attributes to the features.
Another approach is to add a new band to the raster image and categorize the values of the extra band to correspond with the IDs of ...