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Most of the tools for creating contours assume you have an elevation dataset, like a raster or a TIN, which the contour lines can be derived from. It is possible to interpolate between the existing contours you have, but fairly tricky to do. The approach Mark mentions above is probably your best bet. Right now, you have contours which are at different heights, so each line contains the height (or depth) of the values along it. If you convert those lines into points, you can interpolate a surface, and make a "fake" DEM which includes the data that you do have (from the contours). Then, you can use that new raster DEM to create contours at the resolution of your choosing. Note that these will be interpolated, and may not be accurate. So, taking your contours, this would look something like: Data Management Tools > Features > Feature Vertices to Points Spatial Analyst Tools > Interpolation > IDW (there are many other approaches to interpolation, IDW is perhaps the simplest). Spatial Analyst Tools > Surface > Contour cheers, Shaun
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03-28-2014
09:24 AM
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Have you tried the Surface Volume tool in 3D analyst?
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03-28-2014
09:02 AM
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Hello Joe, Yes, you can perform a Viewshed analysis which should do what you're looking for. cheers, Shaun
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03-28-2014
08:51 AM
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I don't believe that Hawthorne has yet released a version of GME compatible with ArcGIS 10.2 -- the site shows 10.1 as the latest version supported. Jake Wall has a package explcitly for movement ecology, ArcMET, and it does support MCP, but I'm not sure if it's yet available for 10.2 either -- you might want to check with him. Generally, the third party extensions from the scientific community aren't lock-step with the latest releases, as it can take a while to have enough new users on the platform to justify the time required to build a release for that version. cheers, Shaun
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03-28-2014
08:36 AM
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James, Assuming 32bit values, you're still only looking at something like 268MB (236*552*540*4 bytes) of data, which should fit into memory without a problem. Doing that for both your rasters and points would be a good place to start as Curtis mentions, as your sampling has to iterate over all points and rasters which isn't particularly fast. Another option that would take more work is to stack the rasters using multidimensional arrays, such as with NumPy or NetCDF. Then, you can pull out the values of all 540 rasters by sampling a single vector (all rasters at one point) which should greatly improve performance. cheers, Shaun
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03-06-2014
10:09 AM
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Rosita, In my own toolboxes, I have these lines: local_path = os.path.abspath(os.path.dirname(__file__))
sys.path.insert(0, local_path) That will get the path of the current file (in this case, the .pyt) and prepend it to Python's system path. cheers, Shaun
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03-05-2014
08:14 AM
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