Latest Contributions by LaurenRosenshein

Hi Thomas, You can definitely use the Spatial Statistics tools to evaluate how clustered or dispersed the distribution of your data is, or the distribution of values associated with your data, whether it's points, lines, or polygons.  There are quite a few different tools you can use to do that type of analysis, all depending on the question that you are asking or the problem that you're trying to solve.  Some tools that you might want to look into are the Average Nearest Neighbor tool, the Ripley's K Function tool, or the Spatial Autocorrelation tool, to name a few.  You might also want to see the general descriptions of all of the tools for measuring global clustering (Analyzing Patterns) and local clustering (Mapping Clusters).  Hopefully these resources will help you get started.  You can also check out some additional tutorials, videos, and web seminars about the Spatial Statistics tools here:  http://esriurl.com/spatialstats. Also, just so you know, several of the tools in the Spatial Statistics toolbox do optionally take a Spatial Weights Matrix as an input.  The Spatial Weights Matrix helps you define, ahead of time, how features are related in space. ... View more

Hi Terry, You are absolutely right, the Hot Spot Analysis tool should be working on your selection set.  In order to figure out exactly what the problem is, I'm hoping you can try a few things and answer a few questions to narrow it down. 1. When you use "Select by attributes" on the dataset, do the correct features appear selected in the map?  If you open the attribute table with the selection do you see those features are selected?  --If the answers to these questions aren't "yes" (ie the selection isn't working) it sounds like it is a problem with the selection, potentially with your query.  Try the same thing with your definition query, too. 2. With the data selected, can you please try running another tool?  Something simple, like maybe copy features or buffer.  We want to make sure that your selection is being honored by other tools that are supposed to honor selections.  If it isn't, then we may have an issue with selections and/or your dataset.  If the selection is being honored, then would it be possible for you to share your data with us so that we can try to reproduce the issue and figure out what's going on? So sorry you're having trouble, and hopefully we can get it figured out quickly! Lauren Rosenshein Geoprocessing Product Engineer ... View more

Hi Chris, This is a good question, and my initial reaction is that this does not sound like a bug (although I do understand your concern).  The first part of your question involves clipping a dataset that was originally created using the Generate Random Points tool.  Once you clip those random points, depending on the polygon that you're using to clip the points you may be imposing a structure on what were once randomly distributed points, which could lead to a clustered distribution. In terms of the new dataset that you created using the Australia boundary, what does that constraining dataset look like?  Is it one polygon representing Australia, or does it have multiple polygons?  If it has multiple polygons (regions, counties, etc.), then Generate Random Points actually generates a user-specified random number of points in each one of those polygons.  What that means is that if you have smaller polygons and larger polygons within that constraining dataset, then there will be 100 points (for example) in each one of the smaller polygons and 100 points in each one of the larger polygons.  What that means is that within each individual polygon the features will be "random", but for the entire study area you will have imposed some definite clustering in those smaller polygons.  So that's one thing to think about. The other thing to think about, which is touched in a little bit on the documentation for Average Nearest Neighbor, is how sensitive the Average Nearest Neighbor (ANN) tool is to the study area or extent of your analysis.  Essentially what ANN does is look at the average distance between each feature and its closest feature in relation to the area of the analysis and compare that to the distances between random features in a circle of the same area.  So, for instance, the same exact distribution of points could be considered random or clustered depending on the extent/bounding geometry used for the analysis.  For this reason, one of the ways that we recommend using ANN is actually for making comparisons between multiple distributions within the same study area.  For instance, if you had points represnting the locations of various types of trees in Australia, you could use ANN to compare those distributions because the point locations/distributions would be changing, but the bounding geometry would stay the same.  That isn't to say that you cannot use ANN for your purposes, it is just important to remember the impact that your bounding geometry has on your output. ... View more

Hi Vicki, In ArcGIS 10, there is a Geoprocessing drop-down menu along the top bar of your ArcMap window.  From the Geoprocessing drop-down there is the option to open Modelbuilder.  From there, most things should be pretty similar.  If you're having trouble finding the tools that you need, don't forget that you can Search For Tools, which is also an option available from the Geoprocessing drop-down menu. ... View more

Hi Michal, I'm really sorry that you're having trouble with GWR! In order to try to figure out what's going on, if you can provide the following information we can try to reproduce your problem and hopefully fix it! -What version of ArcGIS are you using? -What operating system are you using? -What kind of data are you using? Polygons, points, lines? How many features are there? Are they are in a personal geodatabase, a file geodatabase, shapefiles, or other? If possible, if you could provide the dataset that was giving you trouble that would be very helpful in trying to reproduce. If this is possible, it will also be helpful to get screenshots of the tool dialogs before you run them, so that we know exactly the parameter choices you're making. If not, the above information should at least get us on the right track. Again, I'm very sorry that you're having trouble, and we'll do our best to figure it out! Lauren Rosenshein Geoprocessing Product Engineer ... View more

Hi Winn, I'm really sorry that you're having trouble running OLS and GWR on your feature classes!  In order to try to figure out what's going on, if you can provide the following information we can try to reproduce your problem and hopefully fix it! -What version of ArcGIS are you using? -What operating system are you using? -What kind of feature classes are you using?  Polygons, points, lines?  How many features are there?  Are they are in a personal geodatabase, a file geodatabase, or other? -Does the problem seem data specific?  For instance, if you try to run OLS or GWR on a completely different feature class, does it work?  Or do all feature classes cause this failure? If possible, if you could provide the dataset that was giving you trouble that would be very helpful in trying to reproduce.  If this is possible, it will also be helpful to get screenshots of the tool dialogs before you run them, so that we know exactly the parameter choices you're making.  If not, the above information should at least get us on the right track. Again, I'm very sorry that you're having trouble, and we'll do our best to figure it out! Lauren Rosenshein Geoprocessing Product Engineer ... View more

Hi Mary, I'm sorry you're having trouble running Spatial Autocorrelation.  There are some possibilities for why you're seeing this error.  One possibility is that you may have a selection set?  If you have any features selected the tool will honor that selection, so make sure you clear any selection before you run the tool (unless, of course, you specifically want to analyze that selection set).  Another possibility is either null values or invalid geometry.  Both of these could also be causing trouble.  For the invalid geometry, you may want to try running the Repair Geometry tool and see if that helps.  If none of this helps, you can send over your data and we can see if we can reproduce the issue here. Your next question is about recognizing raster layers.  The best thing to do is to convert your rasters to points, at which point you can use the Spatial Autocorrelation tool.  To the best of my knowledge there is no tool in ArcGIS that calculates spatial autocorrelation statistics for rasters.  As far as your last question goes, I'm not 100% sure what you're trying to do, but it sounds like you may want to do a regression analysis, in which case you could use Ordinary Least Squares Regression (for which you will need point data and can do a raster to point conversion).  You can learn a lot more about regression analysis in ArcGIS, and the assumptions of OLS in general, from this one hour free training seminar called Regression Analysis Basics. ... View more

Hi Amber, I'm really sorry you're having trouble with the Incremental Spatial Autocorrelation sample script.  At 10.1 the Incremental Spatial Autocorrelation tool will be part of ArcGIS, and we're working really hard to deal with some of the issues that have come up since the release of the sample script.  For now, though, there are some things that you can do. The most likely reason that you're having issues with memory is that at the distances that you're using to test for spatial autocorrelation many of the features have tens of thousands of neighbors.  Ideally, you want to use distances that give your features no more than maybe a hundred, a couple hundred, maybe even 1000 neighbors...but no feature should ever have 100,000 neighbors.  A good way to see if this is your problem is to run the Generate Spatial Weights Matrix tool for some of your largest distance increments.  The tool will tell you the maximum number of neighbors that any feature has.  If you are seeing huge numbers there, then that is likely to be your problem with Incremental Spatial Autocorrelation.  The solution is to lower the distances that you're testing so that each feature has a more reasonable number of neighbors. One thing that you may be running into is that the distance at which each feature has at least one neighbor is large, maybe because of outliers (a couple of features that are really far away from all of the other features).  A good option is to create a selection set that does not include the outliers and use just those features to figure out a good beginning and increment distance...and ultimately you would run Incremental Spatial Autocorrelation on just the selection set (without the outliers).  After you find a peak and choose a threshold distance, you can then use the Generate Spatial Weights Matrix tool to create a weights matrix that uses a threshold distance that you choose, but then you can also choose a minimum number of neighbors.  What that will do is for the majority of the features it will use the distance band you created, but for the outliers it will use the minimum distance (since that distance band may be too small for them to have any neighbors).  That way you can use a threshold distance that makes sense for the majority of your features, but still include the outliers in your analysis. ... View more

Hi Berk, That's a great question!  For line and polygon features, feature centroids are used in distance computations. For multipoints, polylines, or polygons with multiple parts, the centroid is computed using the weighted mean center of all feature parts. The weighting for point features is 1, for line features is length, and for polygon features is area. ... View more

Hi Eleanor, I'm not sure I understand what you mean by "pooling the residuals" from the local models, but I'll try to clarify.  Basically, both OLS and GWR ultimately calculate a prediction for each feature in the dataset.  For OLS that prediction is based on a global model.  For GWR that prediction is based on a local model that was calibrated using nearby features.  Either way, each feature ends up with a predicted value.  The residuals, whether you are talking about OLS or GWR, are just the difference between that predicted value and the observed value. Once you have those residuals, calculating the R2 value is exactly the same for both methods.  The only difference is whether the predicted value was calculated using a global model (OLS) or a local model (GWR). ... View more

Hi Karen, The kind of dummy variables you're talking about are fine along with some more normal variables in OLS.  They are also alright in GWR if they are not spatial regime variables.  The potential problem is that there is a much higher probability of getting large areas of the same value with only two choices, ie with dummy variables, which then leads to issues with local multicollinearity when using GWR.  Try it with GWR (once you've found a properly specified model using OLS).  If it is a problem: 1) GWR will not solve and will report Severe Model Design 2) If GWR does solve, be sure to check the condition number ... > 30 indicates problems with local multicollinearity (i.e., the regression models for those features are unstable because of variable redundancy and you cannot trust the results). As for a logit version, at this time there is no logistic regression in ArcGIS.  One option is to use R to do a logistic regression.  We've got a sample of of integrating R and ArcGIS which you can find here. ... View more

Hi Ed, Actually, what you want to do to get a value field for running the Getis-Ord Gi* statistic is aggregate your data so that you can use a count field as the input field for analysis.  The Hot Spot Analysis tool will then calculate a z-score and p-value for each feature based on the statistical significance.  You can learn more about Hot Spot Analysis and aggregating your data here.  You may also want to run through the Hot Spot Analysis Tutorial.  To get more information about all of the Spatial Statistics tools you can also go to http://esriurl.com/spatialstats. ... View more

Hi Tim, That's a great question!  Actually, almost all of the spatial statistics tools are python scripts, which means that you have access to the underlying code!  If you right click on the Generate Spatial Weights Matrix tool and choose to "Edit" it, it will open in your script editor of choice.  From there you can go ahead and make any changes that you want!  My suggestion would be to save the original script files before you start making changes, just to make sure you can always revert back if need be.  🙂 ... View more

Hi Eif, It looks like you are using the right Log function in ArcGIS.  The "Log" function using VB is the same as the "Ln" function in Excel...both use the Natural Log.  The "Log" function in excel actually defaults to a log with a base of 10, so that is where the difference you're seeing is coming from.  Sorry for the confusion there! As for the precision issue that you're having, it looks like the field that you are using to calculate the log is an integer field (either short integer or long integer).  You will need to create new fields and use either Double or Float, which will then give you the precision that you're looking for. ... View more

Hi Wolfram, The default threshold distance for the Getis-Ord Gi* statistic is calculated as the distance at which every feature in the dataset has at least one neighbor.  You can also learn more about Hot Spot Analysis here, and you can find a ton of resources about all of the tools in the Spatial Statistics toolbox at http://esriurl.com/spatialstats. ... View more