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You could check out if http://www.naturalearthdata.com/downloads/10m-cultural-vectors/ or http://www.weogeo.com/ has the data you want.


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I have a processing model for that: https://github.com/falu/qgis-split-lines-by-polygons. It works only with qgis 2.4


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It is not really documented in http://www.gdal.org/gdal_polygonize.html that gdal_polygonize is using only one band of the source image. Better wording would be: creates vector polygons for all connected regions of pixels in the raster sharing a common pixel value on the selected band From the script itself you can see that by default band 1 is ...


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To do this in turf, you would do the following: // assume neigborhood is a geojson polygon feature // assume pt is a geojson point feature var turf = require('turf') // < require turf if you are using it from node.js var buffered = turf.buffer(neighborhood, 10, 'miles') var isInside = turf.inside(pt, buffered) console.log(isInside) If you want to do ...


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Efficiency might not be my strong suit, but here is the process I came up with: In the code below, I first create a point feature class from the vertices of my input shapefile. From here I iterate through each feature in the input shapefile. I select each vertex in the point feature class associated with that feature, and then perform a distance selection. ...


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Based on your comment I am assuming you can identify which polygons were affected (be it a few or all), they were only shifted (no rotation or scaling), and are currently in an edit session. Ensure Point and Vertex snapping are enabled. Select all affected polygons and locate the selection anchor (small x near center of all selected elements). While ...


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There's no zipcodes table publicly accessible. You need to create a table with the zipcodes you need (one per row!) and then geocode this table by using the Postal Codes option, selecting in the second selector 'United States'. If I understood well, your regions are composed by several zipcodes that you want to group in order to form them, right? You can, ...


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With recent release by Google of Open Location Code, there was a good questioning about Geohash. Infortunately, I didn't see something about polygons Geohash. As you are looking for various implementations for Geohash like solutions, look at Google comparison of various algorithms and solutions at ...


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Add the spatial adjustment toolbar. Then open an edit session, create some links from the vertices of 4 of the polygons to the points, select affine transform and run the adjustment.


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There are a number of assumptions in your question which need to be addressed before you get to the implementation question. The example you provide is a biodiversity analysis that is based on a sample of varieties of a given plant species. I looked at the manual for the software that was used to generate this raster, and there is no indication that this is ...


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This really depends on a number of factors. Are you talking about a large number of features? Do you have 100 neighborhoods and 1000 point locations, or a thousand times that number? Is your precision requirement high enough that you'll need to take Great Circle calculations into account? At less than 10 miles the error will be around 10-30 meters, ...


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Worked it out, I just drew a polygon around the catchment, added a field called HEIGHT, and then used the field calculator to give me the height I wanted (872m). I then generated a tin from that polygon and then used the surface difference function with the reference surface being the tin I created from the contours to find out where the new tin was above, ...


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One way to speed up your code is to use a dictionary. Iterating the dictionary is faster than the cursor even when you include loading the data into the dictionary from the search cursor. I did a test run on a single polygon to be cut by a single line and the difference in time was 0.74 seconds for cursor vs 0.39 seconds for the dictionary. def ...


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Offhand I don't know of a QGIS tool that does it, but I have a couple of ideas on how to tackle the problem. One possible workflow, though not automatic, would be to dissolve all municipal to a temp polygon, then clip the climate data using that. This would eliminate the exterior overlaps and leave only the interior gaps, which would be fewer problems to ...


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I'd really give SpatiaLite a go for getting this done! Most conveniently you could use the QSpatiaLite plugin in QGIS. Just set up a polygon grid with a sensible size for gridcells. Then intersect the grid with the ethnic group's polygon and calculate area of each intersection. With the resulting table you can calculate your indices by using the ...


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In QGIS, you could generate a point grid on top of your polygons. You'll find this function under Vector -> Research tools (I think it's called that in English, my QGIS version is in another language.) You'll have to find some reasonable granularity when it comes to the point grid spacing. Then under the Vector menu, you do a Join attributes by location ...


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You don't have one polygon, you have many. It looks like the xy coords from all polygons are just dumped into one large list to make a single polygon. Hence the polygon boundary is jumping around creating bad topology. As the above commenters say, your question is poor. But, taking a guess: if you only want one polygon merge your data together prior to ...


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I would make a new layer by buffering your polygons by x-meters and checking the 'dissolve' option. Make sure your new layer is singlepart geometry and then give each of your buffered polygons a unique ID. Next perform a spatial join of your buffers on your original polygons to attribute the originals with the ids from your buffers. Finally dissolve your ...


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In your case the last polygon has a reversed order in the vertices so that's why mapnik (the library we use for rendering) the geometry is removed. If you reserse the order for the latest polygon (with st_reverse for example) it's rendered as you expect. I don't actally know if that's expected and it's a mapnik bug, I'd recommend you to file a ticket in its ...


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You can open Esri file geodatabase in QGIS. I am not real familiar with how to run the analysis in QGIS, but I am pretty sure it can be done.


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When specific shapes exhibit strange behavior as a result of a geoprocessing tool or editing operation, one of the first things to check is whether they have valid geometries. Geometry errors can result in null results or other errors. QGIS has a Check Geometry Validity tool, and another option would be to load it into GRASS and run v.clean. There are ...


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With SQL: import SHAPE1 and Soil layer to spatiaLite (plugin: QspatiaLite), then run a query and load as table in QGIS. the SQL: SELECT SHAPE1.plgnID As ID, Soils.soiltype As soiltype, MAX(AREA(INTERSECTION(SHAPE1.geometry,Soils.geometry))) FROM SHAPE1, Soils GROUP BY ID ..assuming we have a field with polygon IDs plgnID in layer SHAPE1 and a ...


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Update: Have achieved this the long way by creating rasters at spacing of 25 cm over the area, and then using the zonal statistics tool to extract the number of cells at a certain height inside a given polygon. Combined with the LIDAR info. the areas are then easy to calculate.


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You need to create a spatial join. The MMQGIS plugin does this quite easily - MMQGIS -> Combine -> Spatial Join. A tutorial is available here.


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Selections with multiple polygons are kind of tricky in OpenLayers 2. You have to check for every markers if they're within every selected polygon. With more markers, this can slow down the application drastically. There might be an easier way to do this, however this is my solution for your problem: function updateFeatureTable(featureList) { var wkt = ...


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If I understood your question right, what you are trying to do is an aggregate union of a Django GeoQuerySet. There are functions for this that are easier to use and probably more efficient than the loop from you question. You have two options: there is the collect command, which creates one multipolygon collection without dissolving the boundaries, and the ...


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If you reproject the polygon data to Asia Lambert Conic (not just On-the-fly, but really reprojecting all vertex coordinates into a new file), you can dissolve the polygons by a common attribute. This should remove the common border line. If it does not work in first run, have a closer look at the border line. There may be a small gap after the ...


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In ArcGIS. Start Editing the polygon layer. Select the two polygons only, one each side of the international dateline. In the dropdown Editor menu will be a merge option, click it. A window will appear select the portion of the polygon you want the other part to become a part of (usually the bigger one), they flash as you select them. You now have one ...



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