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Found that I could use the TileLayer plugin https://github.com/minorua/TileLayerPlugin instead of openlayers. After creating a .tsv file for Google image layers, I am able to load a google layer base map which zooms fine and has no problem with buffering. Unfortunately, if visible, it does slow down the buffering process considerably. I just turn it off when ...


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It looks like the answer was easier than I thought. All that needed to be done was take out mapUnitsPerPixel and and then find the correct distance (.00015) pntBuf = pntGeom.buffer(.00015,0) This works great without being affected by scale.


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Accordingly to Spatialite coockbook you must register your VIEW into the views_geometry_columns, so to make it become a real Spatial View, i.e.: INSERT INTO views_geometry_columns (view_name, view_geometry, view_rowid, f_table_name, f_geometry_column) VALUES ('buffer500m', 'geometry', 'ROWID', 'point', 'geom');


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If you have a Spatial Analyst license and using rasters an option, you could use the Focal Statistics tool with the Wedge neighborhood. It's probably more appropriate than vectors in your case anyway (overlap of several layers for a suitability analysis).


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Your 'var CountPt' part of the code (which does the counting of points) needs to be moved to within the updateBuffer function so that it constantly reruns. function updateBuffer() { var pointMarker = marker.toGeoJSON(); buffered = turf.buffer(pointMarker, 1, 'miles'); buff = L.geoJson(buffered); buff.addTo(map); ...


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Here is the solution, found myself, and not obvious at all in the documentation: add a OUTLINECOLOR to the LABEL tags! CLASS NAME "myLayer" EXPRESSION ([code] = 1) STYLE SYMBOL "STD_circle" COLOR 0 255 0 END LABEL FONT "vera" TYPE TRUETYPE SIZE 3 COLOR 0 0 0 ...


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Have you tried to write the different distances in a python list : [356.8,792] as describe in the ressources : http://resources.arcgis.com/en/help/main/10.1/index.html#//00080000001p000000


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Suggesting a workflow: Starting point is after the creation of Buffer B. For Buffer A use the multiple ring buffer creating two buffers. The original one and another one which is 1.5 times the distance. E.g 12 meters and 8 meters. For buffer B open a new field (float, named "expand"), and feed it with [BUFF_Distance]/2 Use intersect to create an ...


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I by mistake gave that answer to an old thread. So copied it here. Trying to find the thread I found this ESRI code for field calculator that iterate to find the right buffer for each polygon. Code attached in the end, and there is a link to the page. Note that this answer is un-related to the code below (but I worked to hard to make it, so I leave it here ...


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I can only suggest a simple method that will give an approximate on average; yet if you are looking for the exact percentage reduction of area this would not work - but might guide your thoughts towards a coding solution. This method is based, like others have suggested, on negative input to the buffer tool. However it also involves adjustment to the the ...


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You could try setting the output workspace with arcpy.env.workspace to be a folder not a file GDB. Make sure you specify a folder without spaces in the path as ArcGIS will use its default GRID format for temporary rasters which can't have spaces in the path.


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One method would be to split your point file (via a select and export or some other method) into to new files - points within buffers and points that are not. From there you can use a Spatial Join (which doesn't require an Advanced License if you don't have one) to join the points outside the buffers to those inside. With the settings of that tool you can ...


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Try using the Near (analysis) tool. The resulting table will show which point is closest by whatever OBJECTID you specify. Then perform a join and field calculate the values into your previous points.


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If you have the spatial analyst extension you can use the Euclidean Distance tool. 1. Convert the buffer to a raster with the "To Raster" tool (under conversion tools). 2. Then run the Euclidean Distance Tool which will create a raster with values representing distance from the cells that comprised the input raster. 3. Then if necessary, you can extract ...


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you will NOT have the same results, but both results have their own interest. In the first case, the buffers will not overlap. So the total area under the multiple ring buffer will be equal to the area of one large buffer. This is usefull if you want categories of distances (e.g. how many inhabitants are between 1 and 2 km away from an hazard). Note that, ...


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Here's a blog post by Paul Ramsey about doing this in PostGIS, perhaps a worthy venture: http://boundlessgeo.com/2014/10/postgis-training-creating-overlays/ Summed up with this note: Now we have a single coverage of the area, where each polygon knows how much overlap contributed to it. Ironically, when visualized using the coverage count as a ...


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You could use the Intersect tool (Vector > Geoprocessing Tools > Intersect) on the buffers and then to find the number of intersections it would simply be the total number of attributes - the number of points.


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As indicated in the comments, you have a few issues. The first one I see is your enumerating through fcs. What do you expect to enter at the prompt? Your code will enumerate through each letter, which I expect is not what you want. For example, if you enter "fred, bob", the list will be: [f,r,e,d, , b,o,b]. Try: arcpy.env.workspace = r'c:\data' ...



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