I want to invite you to join the Salisbury University Geography students as they present their final GIS programming projects, Monday December 18, at 4:30PM in Henson 153. Snacks will be provided*.
Last year we had a really successful presentation of student programming assignments as part of our GIS Programming class. For this year, we decided to do something different. Rather than students selecting their own projects, I identified four topics that I thought were under served as traditional GIS tools. That is, the tools simply don’t exist as far as I know. And, because the tools aren’t readily available, they aren’t applied within our discipline – hence the name, Salisbury Gives Back.
So, our students created four separate ArcGIS Script tools that will run right in ArcGIS:
Join Count Analysis Tool – This tool focuses on the spatial autocorrelation method of join count analysis that evaluates area features with binary variables to determine if the data is random, dispersed or clustered. An example would be to determine the spatial autocorrelation of voting patterns for the US Presidential Elections (i.e. red vs. blue states). The tool calculates the expected and observed dissimilar joins, the Z score, and associated p-value.
Sadly, this useful method is rarely used because a tool does not currently exist to perform join count analysis. However, with this tool, geographers can now evaluate spatial autocorrelation with binary variables. In fact, with this tool’s ease-of-use, I expect to see Political Geographers make use of the analysis capabilities to evaluate elections all throughout the US and beyond.
Quadrat Analysis Tool – This tool focuses on the spatial autocorrelation of point patterns across a landscape. Using points and a grid of quadrats, this tool measures whether a point pattern is random, dispersed, or clustered and is frequently used in hazard analysis for things like wildfire distribution, tornado touchdowns, or dispersion of crime. The tool calculates the variance to mean ratio, Chi-square value, and associated p-value. In addition, the tool thematically shades the quadrats based on their counts.
Similar to the Join Count Analysis, there does not appear to be a tool that exists to accomplish the task, and therefore the approach is rarely used in our discipline.
Stratified Sampling Tool – This is not a spatial tool, but rather a tool that takes stratified samples and generates point and interval estimates from the stratums. Generating estimates from stratified sampling is a very powerful statistical technique, and provides significant improvements over simple random sampling. A good example is to estimate yearly household utility usage in a community by sampling homes from three different stratums: large, medium, and small. The tool allows the user to enter the data for each stratum, along with the level of confidence (i.e. 90%, 95%), and provides the point estimate and confidence interval.
Stratified sampling is rarely used because there isn’t a tool that can perform the task. However, with this tool, geographers can now easily determine confidence intervals for estimation of averages, totals, and proportions when considering different stratums.
ArcGIS and Google Route Optimization Tool – Currently, network analysis in ArcGIS requires Network Analyst. Network Analyst requires a significant effort to not only create a network, but also maintain it. Further, most organizations don’t have up-to-date speed limits or real time traffic observations. This tool integrates ArcGIS with the Google Maps API so that users can route the ArcGIS features over a Google network, using the Google Routing Engine. Users can input their own geodatabase feature classes, and the tool returns the Google routes as a geodatabase feature class, along with driving directions. In addition, the user can select different route types (i.e. driving, walking, mass transit). If you ever wanted to route your ArcGIS data over a Google network, you want to stick around for this presentation!
We hope that you can join us for the presentations and code walk-through. If you know of other people who might be interested in these tools, please do not hesitate to pass this email along.
* we plan to record all four sessions, and I will post them here next week, along with the associated toolbox (assuming I don’t mess up the recording!).