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2

Try the dissolve tool. This will merge polylines where their ends touch. Logically a contour from one lake would not be touching any other lake so there is no need to checking if they are the same name and elevation.


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I'm assuming that what you are looking for is an overlay of the isopolygons, with resultant polygons attributed with the sum of the parent polygons. If so, the usual technique is to union/node the linework, polygonize it, and then use a point-in-polygon query for each resultant to find it's parents. This is a good blog post describing this technique. There ...


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Are you using the -n parameter? If not, nodata values will be included in your mosaic. GDAL will ignore nodata values if you specify this and will mosaic data without overlapping nodata areas included. Note (update from OP): np.nan may not work as a nodata value For example: gdal_merge.py -n 0 -o output.tif input1.tif input2.tif You will need to know the ...


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Solution 1: r.patch solved the problem if DSM and DEM files are inputted correctly into the algorithm. Unfortunately, changing the order of the files in the UI is not clear. You need to drag them in order in the selection window before clicking OK. Solution 2: As @MrXsquared described in a comment in the initial post, this problem occurs when "nodata ...


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I think that as @MrXsquared tells you, you must first solve the problem of non data or null. This is very common, it depends on the type of data and how the raster was generated. You can search on this website to find out how to solve it. If your null value is recognized by QGis, for example -9999 (used by SAGA). You could perform the procedure with the ...


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The both coordinate systems are essentially the same despite the name and the code. The software you are using obviously selects the first coordinate system that matches the proj string and shows that. projinfo -o proj epsg:8687 PROJ.4 string: +proj=utm +zone=33 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs +type=crs projinfo -o proj epsg:25833 PROJ....


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I figured this out. First you need to create a new field merged_ID in the lot layer, giving a unique ID to each group of polygons to be merged. The attribute table would look like this: Then type the following query in the virtual layer creation window: select st_union(geometry), l.* from "lot" as l group by l."merged_ID"


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For polygons in polygons I would suggest using either within or have their center in. Within will only select precincts that are within the county. Have their center in works well if you have messy polygon edges that overlap a lot, however, if you have extremely irregular polygons whos centroid may fall outside the polygon boundaries. Just something to ...


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Im using QGIS 3.14. I found the GDAL Dissolve tool to be more feature rich than that standard QGIS Dissolve tool. It allowed me to choose the Dissolve Field, choose the geometry name but also, 'Produce one feature for each geometry....' which essentially performed a SinglePart to MultiPart function.


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So the big issue is what "algorithm" to use. I'm doing pretty much the same as @Fezter with an overlay and checking overlaps. I take anything with an overlaps=1 and keep it as a final result. I take one feature at random with the highest number of overlaps, and drop it from the translation. So: Do Overlay Data If Overlaps = 1 then ...


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so I just wanted to add the solution i ended up going with, a hybrid of a few different ones. It's frustrating the the esri documentation for Merge_Management() doesn't actually say how it keeps/deletes fields but it will. relevant code sample below. pointfieldmappings = arcpy.FieldMappings() point_keep_fields = ['RequestID','Prioritization_Bucket','...


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I think I understand your question now, and I have a potential solution. I have created a simple workspace which buffers some points by 100m and then passes the points and buffers into a PointOnAreaOverlayer. Then, I test for how many overlaps there are. The workspace looks like this: The points and buffers look like this: Tester Parameters: Resulting ...


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This is potentially less performant than Emil's answer, but much more concise: just merge everything indiscriminately, create 2 sets with the original field names, then delete the symmetric difference of those field names (belonging to either fc_a or fc_b, but not both). merged = arcpy.Merge_management([fc_a, fc_b], 'merged') fields_a = {field.name for ...


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Creating layers with hidden fields is the way to go here, using field info objects. I have a function I regularly use for this. Then it's a matter of creating your two layers and using them as inputs in your merge. Try: import arcpy fc1 = r"your\first\featureclass" fc2 = r"your\second\featureclass" mergeFc = r"your\output\merge\...


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