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I tried keeping the file at simple locations like D:/ArcGIS or C:/ArcGIS and extracting to similar simple locations as you suggested. But the error persists. I have used the same file earlier to install it and it was running good. Do I need to install something else on my system since I did a fresh install of windows after which I am attempting to install ArcGISPro2.6.
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08-14-2020
02:35 AM
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Error arises on clicking the .exe file. The dialog box says "An unexpected error while unpacking files. Error code: -2147467259 ". File name is "ArcGISPro_26_175036.exe"
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08-14-2020
01:57 AM
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Hello Mr. Krause, The tool works as expected! One thing very interesting about the new GA Layer was that the cross-validated (CV) statistics remain the same, since I was expecting that the added extent would have lowered the quality of the overall results. BUT, the statistics remained the same. In my opinion, this is because no measurement changed for the CV statistics calculation. So, even if I perform validation by sub-setting the points, no result report is going to change since the number of points, their measured values and their predicted values, all remain the same. Only new predictions in the added region are added in the new GA layer. Please correct me if my understanding of this concept is not correct.
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05-01-2020
10:40 PM
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So, I believe I should use a smaller neighbourhood to speed up the process, particularly if I am getting no difference in the results. Please correct the statement if required. Thank you for the great response.
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05-01-2020
09:17 PM
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Problem: My study area is a simple rectangular polygon in which the sampled points are spread inside. The extent of this polygon is obviously greater than the extent of the bounding box of input points. Now, the Geostatistical Wizard does not honor the (extent) environment settings. Also, Kriging is not given as an independent tool in the GA toolbox which can be supplied with the extent environment settings. As much as I know, only the wizard can do together (a) data transformations, (b) semivariogram modelling, and (c) neighbourhood parameterization, but it won't produce the result in the entire extent of the polygon! Alternative adopted: Added four points at the four corners of the study area polygon. I updated their z-values with the mean of the sampled points. This causes the wizard to produce output in the exact extent of the study area polygon. The interpolation in the new 'extra region' would have used data from the sampled points and these 4 extra points. Discussion: Is the above method a good alternative to the environment settings problem? I believe that a lot of users would come across this problem because a lot of times the output extent would be bigger than the sampling extent. Regarding the use of spatial analyst kriging tool, there's the only the option of simple and ordinary kriging and the tool is less flexible than the GA one. Is there a workflow of tools available to perform the above kriging job? Please enrich my knowledge.
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05-01-2020
08:40 AM
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Thank you for the insights Mr. Krause. So, the labor done in modelling the semivariogram is not lost if the neighbourhood parameters are not adopted in the next step. How the semivariogram properties are still transferred to the neighbourhood search process while even using a different radii, are implicit in your comment. I believe the explanation might be lengthy or beyond the scope of this discussion. So, I set the 'copy parameters' to 'FALSE' and checked the cross-validation stats with a much smaller radii. The stats were similar to the ones I was getting with this huge sized radii, from which I conclude that the big radius is doing no harm. As a curiosity, are such big radii used in the general interpolation jobs? Thank you.
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05-01-2020
07:59 AM
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As I have read about some threads in Geostatistical Analyst that there are no definitive rules about choosing the right neighborhood size but the bad ones are like choosing the radius more than half of the range of semivariogram. So, I have decided the parameters of first part i.e. Semivariogram modelling: Lag size = SET (using 'Avg Neighbourhood Distance' tool from Spatial Analyst, and following the rule that lag size * no. of lags = 0.5 * (max distance between input points)) Lag no. = SET (as in point 1) Anisotropy = ON (as I can see that the sill is approached rapidly in one direction than the others) Model = 'Stable' (subject to change) Nugget = 'OFF' (due to poor cross-validation stats with Nugget = 'ON') So, now in the second part i.e. Prediction, I have set some parameters with confidence but have confusion in some: Number of neighbors belongs to range [10, 32] The problem: If I set the 'copy parameters from semivariogram' to 'TRUE', the ellipse almost encompasses the study region extent which I believe is a bit weird. But, if I set its flag to 'FALSE' and set the major and minor axis myself, would that nullify the effect of semivariogram modelling? If yes or not, please provide me some recommendations about the neighborhood size as also seen in the images below. Eric Krause Image 1 - Semivariogram modelling parameters, Image 2 - the big search radius.
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05-01-2020
03:20 AM
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Thank you. You have nice insights and vast experience of geostatistics. The thirds option is interesting. Although, there is a bit of double-dipping in this method too over the repeated usage of training set of data. I will try to perform it and include in my writeup if I can theoretically defend its usage. I am closing the thread here. Its answered and thank you.
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05-01-2020
02:48 AM
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Hello. Since its a 2011 copy, do we have an updated version of this book too?
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04-28-2020
10:57 PM
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