Latest Contributions by EifLeffie

Hi, im having the same problem with extract multi value to points. I've done so many manipulations on my files already just so i can extract multiple values and append to my points but i kept getting a <null> values on the field in my table attributes. I had reprojected, resampled and converted the data to several formats but it would not work. I'm using ArcGIS  desktop 10.2 which I just purchased. I have read several times the conversation on this thread and did what you guys have done (except downloading the pack to fix the bug that ESRI mentioned). There was a mention that it has been fixed in this   new version  so I thought there is no need. Having said that, is there a pack available to fix the bug specifically for 10.2? In addition to that, my file is in a generic format and I wonder if there is a specific format compatibility requirement so this tool would work? Please kindly help, I've been working on this for two days now and I cant seem to crack it. I wonder if I'm missing a piece of vital step here. Thanks. Regards, Leffie ... View more

If your data is stationary, you expect to see randomness in the colors of the Voronoi polygons when they're symbolized by entropy or standard deviation.  The idea is that the local variation should be roughly constant across the surface; you should not have areas with much more erratic data than others. Looking at your two Voronoi maps, it looks like you have some nonstationarity, but it doesn't look very drastic.  The StDev symbolization seems more clustered, but the Entropy symbolization doesn't look too bad, and I prefer to use Entropy when looking for stationarity. Thanks much Eric. If you want, you can send your data to ekrause@esri.com, and I'll see if I can fit a good kriging model. I have sent you the file via email. I highly appreciate the help. Best regards, Eif ... View more

The Local Moran's I test in spatial statistics has the potential to detect nonstationarity, but it's really looking for local outliers.  If the data is stationary, you won't find local outliers; however, the lack of local outliers does not imply stationarity, so be careful. For investigating stationarity, I suggest using the Voronoi Map ESDA tool with Type set to Entropy or StDev.  One advantage of the Voronoi Map is that it works with quantiles, so it's nonparametric.  Local Moran's I comes with distributional assumptions. Thanks Eric. I am not familiar with how the Voronoi map works and this is sort of abstract to me. Is there a paper on how this works? I have attached the image of the voronoi for both entropy and stDev and I am confused on how to interpret it. Any help is highly appreciated. Thanks, Eif ... View more

Have you checked "stationarity" assumptions? It sounds like you may have some serious nonstationarity in your data. A polynomial trend removal will not account for second-order effects. Violation of even the most relaxed model of stationarity can have a negative effect on Kriging estimates. ArcGIS has the LISA model available, in the Spatial Statistics Toolbox, for testing stationarity. Thanks for the reply Jevans. I have not checked yet for the "stationarity" of the dataset. The dataset is actually annual growth of trees. Pardon me but I am not yet that well verse in GIS processing. What is LISA model? Thanks, Eif ... View more

Thanks Eric. That's a big help! Cheers, Eif ... View more

Eric, sorry about my former post.. ERRATA ....OR WE NEED TO DO SOME FURTHER MODIFICATIONS... Eif ... View more

Thanks Eric, but not really. I was wondering how the strength of the anisotropy can be detected. I have found an article regarding that clearly explained with the use of other software and I sorted it out already. I am also wondering if once the anisotropy is set to "TRUE", does the software automatically removes the effect of the directional influences or we need to do Pardon me for the many questions, but it's actually taking me months already before I can finalize the kriging procedure as I am doing also some readings and research about the geostat and variograms. I am new to this geostat and semivariogram stuff. I don't want to give up on these and am keen to learn how I could minimize the errors so I could end up with the very good kriging results. Cheers, Eif ... View more

Hi Eric, The datasets that I am working with has a trend and the plan is to remove it. The trend is a U shape which can be removed using the second order polynomial. However, I have confusion in identifying the directional influence in the datasets. For instance, in page 104 of the manual of geostat analyst (Which I just found and is very useful indeed), the image (attached here) shows a strong influence on the southeast to northwest. I wonder how the strength of directional influence was detected. X  axis is west-east (left-right) direction while Y-axis is the north-south (up-down) heading.  Directional info on the image says: Location - 30 degrees; Horizontal - 120 degrees; Vertical -  -27degrees. Please kindly elaborate on this. Thank you. Regards, Eif ... View more

Hi Eric, Thanks for the help Eric. I got a result showing a high root mean square (239) and average standard error (234.16), mean error is also high (-7). I wonder if there is a technique to reduce these. I have tried changing the model type like Hole effect and other types hoping to at least reduce the errors but they are all resulting to high error values. Would there be some other trick here to reduce the error? My apology as I am not familiar with this method. I would be glad if there is any procedure on how to reduce errors in this type of processing. I would highly appreciate any help on this. Thanks. Best regards, Eif ... View more

Hi Steve, Thanks a lot for the reply. What I did was to copy all the parameters in the prediction error of each model and encode in excel. The process is a bit tedious but I can be sure of which model I could choose (eg. model with lowest mean, Root Mean Sqr and Ave. Std. Error is a bit large but gap is small, etc.). It would be easier if only one parameter (e.g. mean) is to be compared, however, in choosing the best model, we have to consider the RMS and ASE values, gaps, etc.). This I guess cannot be done in ArcGIS as this needs manual analysis and would be based from the best jugdment of the user. Thanks a lot and have a great weekends! Cheers, Eif ... View more

Thanks Steve for the reply. I have not used this utility yet as I am not that familiar with programming but I think it's worth a try. Best regards, Eif ... View more

Thanks much Lauren for the help!..so helpful indeed. Cheers, Eif ... View more