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I need to create a map based on what I have available in a CAD document. I have minimal past experience with CAD files or the CAD program, and so I am trying to convert a CAD file to ArcMap so I can more easily manipulate the data and build on it there. I've added a coordinate system to the CAD file, but when I add it to ArcMap or try to convert to geodatabase, the CAD feature classes are empty. I've tried adding the CAD data by just clicking the add data button and adding the CAD file, and also by using the geoprocessing tools for converting from CAD to geodatabase. Either way I've tried, the CAD feature classes appear empty, with no data in them so nothing is displayed and attribute tables are empty. Perhaps I am missing a simple step... But any suggestions on how to successfully import a CAD file into ArcMap would be greatly appreciated.
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02-18-2016
11:44 AM
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Thank you, I double checked save location and got the SetNull function to work properly with the second expression you mentioned above. However I'm still receiving an error message when I use the Con function. The error message I receive with this is that the "'Raster' object is not callable". I'm using the expression: ((Con("Results" < -4, -4, "Results")) (Con("Results" > 1, 1, "Results"))) I've tried several variations of the expression to get the calculator to accept the syntax.
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04-10-2013
02:49 PM
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I'm still having some trouble getting this to work for me. I'm getting a couple of error messages when I try to run the raster calculator with SetNull. When I use both limiting values (-4 and 1), with this calculation SetNull("results" <-4 >1, "results"), I get this error message: ERROR 000539: Error running expression: rcexec() <type 'exceptions.ValueError'>: The truth value of a raster is ambiguous. I thought maybe it would only take one limiting value at a time rather than the range I was trying to specify... so I limited the calculation to only limit to < -4 with this calculation SetNull("results" <-4, "results") and got this error message: 000539: Error running expression: rcexec() <type 'exceptions.RuntimeError'>: ERROR 010240: Could not save raster dataset to <Save Location> with output format IMAGINE Image Perhaps I am inputting the values incorrectly?
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04-10-2013
10:51 AM
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Thanks very much, problem solved! I have one other question, regarding the raster calculator. I'm using the raster calculator to input a regression equation that I've created from my data, using the output I created with the euclidean distance calculator as the x value for the equation. However it predicts unrealistic values outside the range of what I know is possible for the variable I'm measuring. I'm wondering if there's a way that I can limit the output of the output from the raster calculator to only predict within values I know are possible? For instance limit the prediction to within -4 to 1, rather than allowing the calculator to predict values of up to -16, etc.
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04-03-2013
09:17 PM
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Thanks very much, problem solved! I have one other question, regarding the raster calculator. I'm using the raster calculator to input a regression equation that I've created from my data, using the output I created with the euclidean distance calculator as the x value for the equation. However it predicts unrealistic values outside the range of what I know is possible for the variable I'm measuring. I'm wondering if there's a way that I can limit the output of the output from the raster calculator to only predict within values I know are possible? For instance limit the prediction to within -4 to 1, rather than allowing the calculator to predict values of up to -16, etc.
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04-03-2013
09:17 PM
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I'm attempting to use the Euclidean distance tool in spatial analyst tools to calculate the distance from a polygon feature class. The problem I'm having is that even when I specify a maximum distance for the tool to calculate distance until, it still only creates output for the default maximum distance (to the extent of the input feature class layer), which in this case is around 5m or so. However, I want it to calculate distance much further out than that. Is there some simple step I'm missing to make the software recognize the maximum distance that I input and specify? Any suggestions would be greatly appreciated.
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04-01-2013
04:04 PM
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If you only have 10 points for each day, we do not recommend kriging. No interperpolator is going to be very effective with so few points, but if I had to choose one, I would go with Kernel Interpolation with Barriers. Just don't supply a barrier. Thank you for the response. I've been working on trying Kernel Interpolation with Barriers with my data set. I have a question regarding this method though, perhaps you or someone can answer. I would appreciate any suggestions. I do actually have a barrier: the channels around which the plants that have been measured are located. However, the barrier limitation in the kernel method sounds like it would limit the information provided by values on opposite sides of the channel. For instance, plants on opposite sides of the channel won't be analyzed together. I.e., if there are no samples, say, within 1m on one side, we won't have a good estimate at that distance on that particular side. Does this method still use all the distances regardless of side, but then place the barrier after interpolation? Since my sample size is low, if the barrier is placed and each side is analyzed individually, this would reduce the sample size further and perhaps not be an ideal method.
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02-24-2013
12:57 PM
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Hello all, I'm new to geostatistical analyst and am trying to use the method of kriging for an academic project. I was wondering if anyone might be able to guide me on how to use the geostatistical analyst for the data that I have. I have water potential and stomatal conductance data from 10 plants at 3 different sites in the Mojave. This data was taken on 5 different days over the course of two months following the addition of a pulse of water. I would like to take this data and spatially interpolate the water potential values and stomatal conductance values for each sample day to get a series of predictive and progressive surfaces. I know the sample size is pretty small and the prediction is going to be made over a very small scale as well. I've made some preliminary attempts at analyzing this data already. I found the kriging to be rather complicated in terms of determining all the proper settings, and the model was not coming out as I expected that it should (perhaps due to small sample size?). I also tried local polynomial interpolation (LPI) and the deterministic method of spline with barriers. The LPI method seems to go along more with what I might expect to see from my data, but I'm not sure what the best method is to use. Any help or suggestions would be greatly appreciated!
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02-10-2013
04:25 PM
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