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Hi Viviane, please have a look at Eric's post below  he gives a brilliant explanation to this problem. A GA layer is basically more a continuous surface of a function that takes an (x,y) location and returns a value. It does not have a set grid resolution as a raster has and the contours you see for the GA layer are just drawn from a very course grid, with the symbology based on min/max of the input points. The visual difference between GA layer and output raster is simply down to the different contouring and symbology, but the values will be the same!! I at the end decided on a raster grid size, exported and classified the raster in a similar way as the GA layer (i.e. max min and class ranges)  it looks the same and the values are the same. Hope this somehow helps. Cheers, Astrid
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02162014
09:57 PM

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Thanks a lot for this brilliant reply Eric! It definitely helped me understanding whats going on with the kriging output and the conversion to rasters. Much appreciated! THANKS!
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02112013
08:28 AM

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Hi Eric, thanks for your prompt reply. I've seen this blog entry before and yes...I guess I'm a bit stupid here. So when converting a GA layer to a raster, an average value for each raster cell (which is different to the resolution of GA layer) is calculated. If I define only to take into account 1 point in x and y direction, this one will be placed in the centre of the cell. Whilst calculating the average of the cell a weighted distance value will be assigned to all neighbouring points within the cell. In case of the max value not being located in the centre of the cell, it will be weighted according to its distance from the centre of the cell and nearby points. Hence the max value does not show up as the final cell value. Is this right? If not, I guess a slightly more in detail explanation would be very much appreciated. Many thanks for your help, Astrid
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02092013
01:04 AM

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Hello, I have a question regarding the export of kriging results into a raster. I've seen a few threads related to this question, but unfortunately could not find the right answer. The problems: 1. The raster's min and max values differ from the min and max values of the input data. Max and min values (which are actually real measured max and min) change by nearly 10% when the kriging result is exported to a raster, which is not acceptable for my data and study purpose. I've seen that this problem is linked to the cell size. Is there anyway around it  recalculating the raster values in some way and trying to correct them manually? I really need the min and max values to not be changed in my dataset. 2. The isolines of classes as shown in kriging do not match with the ones in the raster. As far as I understand is the problem the conversion of the onthefly, hence fairly coarse, interpolated GA layer into a much finer raster. So I played around with the cell size and did notice that the result improved when increasing the cell size, but I didn't manage to match the output of the GA layer. I also read in a few threads that the coordinate system could be a problem, so I converted it from degrees to metre, but didn't notice any improvements. My sampling area is only 6m^2, so I guess this makes the degree problem neglectable. Any suggestions on how to improve the raster output if a fairly fine grid is required? I need a raster output (ideally a fine grid) as I would like to perform further analysis on these data. Any suggestions and tips on how to deal with this and hopefully improve the end result are highly appreciated! Best regards, Astrid
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02082013
01:52 AM

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Dear Jeffrey, I firstly used Kriging as part of the Spatial Analyst Tools, but soon figured out that the Geostatistical Analyst, as you said, provides a much wider range of adjustments and also a far better visualisation of the model fitting and number crunching related to the statistical output. Hence I'm going to continue using the Geostatistical Wizard. Thanks a lot for your help, advice and support of this final decision! It's very much appreciated. I found the thought of possibly using a wrong interpolation and hence creating data out of the blue, which would then also form a base for further work, pretty scary! But this definitely confirmed my decision of using Kriging for the interpolation. Many thanks, Astrid
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02062013
07:45 AM

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Dear Jeffrey, thanks for your prompt reply and sorry for the double posting of this thread! I tried the Spline function and adjusted weight and number of points, but am ending up with really odd output values. My data should be in a range of 0 to 4.5, but the Spline output ranges in some cases from 400 to +800. This occurs for the regularized as well as the tension spline type and I'm not entirely sure why it happens. The data work fine with Kriging and the model output looks good, with a mean error close to zero (0.001) and RMS standardized close to 1 (please correct if this interpretation is wrong). I do not have a theoretical basis which provides a good reason to replicate the method used in Matlab in ArcGIS. I only assumed that linear interpolation is required as everyone, who I know is handling current flow data, is using it  basically a fairly bad reason. I had a few discussions with oeanographers today, asking why linear interpolation is so commonly used with current flow data. The general reply was: because it is simple and easy. So no deeper theory behind it. Accodingly I decided now to use kriging. My sampling area is only 6 km^2, which means that the difference might not have a huge effect either. Additionally the stats behind it support the model prediction, thus it is acceptable. Would you agree with this? Best regards, Astrid
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02062013
05:52 AM

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Hello, I have a dataset of current flow data (x,y,z), collected by a vesselmounted ADCP over 11 transects, which were spaced by 300m. Normally I would use Matlab to postprocess and interpolate these data. In Matlab I would apply the griddata function, which creates a uniform meshgrid (dimensions defined by myself) and applies linear interpolation, which I smooth at the end. I would like to recreate the results in ArcGIS 10.0, but I am struggling a bit as I'm not entirely sure which interpolation to use. Initially I thought the creation of TINs would come closest to what I've done in Matlab, but I think my data are not scattered enough (being formed by straight transect lines) and I'm ending up with a very jagged appearance and bad edge effects. I then tried the natural neighbour interpolation and the result was closer to my Matlab results, but the surface was not very smooth. IDW gave ok results, but I would prefer the resulting surface to include the measured values. Hence I applied the Spline function, but it overestimated the values in some areas. Kriging at the end gave a reasonable good result. I was now wondering if anyone here worked with current flow data and could give some advice on how to best interpolate these in ArcGIS. As far as I understand (please apologize if I'm wrong and correct if required) is a linear interpolation fairly simple and straight forward calculating the value of a point between two known points and thus differs from available interpolation options in ArcGIS, which are all distance weighted. Accordingly I'm hesitating to apply a distance weighted interpolation as I'm not entirely sure what the effect on my data will be. Your help and advice will be highly appreciated! Best regards, Astrid
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02052013
07:25 AM

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Thank you very, very much Jeffrey! This solved my problem :)!
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12162012
11:44 PM

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Hello, I have a question regarding kmeans clustering in ArcGIS. I have a shapefile, which contains a number of polygons with different values for mean, standard deviation, skewness and quantiles. I would like to cluster them using kmeans clustering. I am aware that ArcGIS 10.1 just integrated a tool for this, but I am still working under ArcGIS 10.0. I also discovered a toolbox , which is using R in ArcGIS, but I'm having problems with the installation of the required Design package in R and hence can't get it to work. Accordingly I was wondering if you could suggest a different way on how to get kmeans clustering to work in ArcGIS 10.0. Can I do the clustering in R and then import the results somehow into ArcGIS? Tips and suggestions are highly appreciated! Many thanks for your help, Astrid
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12122012
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