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4

Using ArcGIS I would use the union tool. This will give you a layer that combines both the 'purple' and 'green' buffers into a single layer. From this output you can select just the 'green' areas which don't have cover 'purple' areas. You can either do this by looking in the attribute table and select the areas where the purple FID is -1. Alternatively ...


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UPDATE: Your problem seems to be with your data. Here is a snippet of your file: }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 585951.8, 181704.9 ], [ 576293.9, 181299.8 ], If I'm not mistaken, those ...


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The scale is not a constant on map projections. For local map it is not an issue because the change in scale is so small that it is below the precision of the drawing, but for World map there can be huge difference when you change latitude (obviously, in a Mercator projection, the same distance near the pole is not equivalent to the distance near the ...


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Jens Rasmussen, one of the inventors of Google Maps, a Danish computer programmer is credited with the creation of what is officially known as the map pin or pushpin. See this New York Times article which is referenced in his official wikipedia page


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Is it possible to use an annotation feature class for the 'DRAFT' text, manually editing the text, and setting the transparency for the layer at 50%? This allows you to see the features under the text, and it is not necessary to export the document for use in another program.


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Try Hec-ras, there is an extension to use in ArcGis.


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If you are going to be repeating this process or attempting to model/script it...then using a GP tool such as the Union tool as @MAJ742 suggests is certainly the best option and your best answer. If I understand your question correctly and this is a one time thing or you are just playing around with your data...you can try the Clip option on the editing ...


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Looking at the examples provided with the ?iconlabels function, the author uses the column landuse from the meuse dataset. That column is from class factor. So I tried to convert your column cluster from class integer to class factor and it worked. X = read.table(text="code,cluster,name,longt,latit 101,1,A,-89.6171,35.24992 ...



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