Hello,
This post comes out of a series of discussions around the general topic of “What I’d really like to know about each Spatial Statistic tool?”. The current help section contains a wealth of information, but there are still some lingering questions:
1) In layman terms, what does each tool do?
– There’s a great post in the help section on sample applications. But they’re grouped by spatial question, and then a tool is listed. It’d be wonderful if a similar set of examples of simple-to-understand terms was listed by tool. So, for example, I could look at the incremental spatial correlation explanation and read that it answers questions about “At which distances is spatial clustering most pronounced?
2) What type of data sets are appropriate for use with a given tool and why?
– Each of the tools is based on a mathematical statistic of some kind. You have thoughtfully included a Best Practices section along with most of the tools. But there’s no mention of the reason for each suggestion. I realize this is a big ask, but if there was some explanation of the mathematical theory behind what will go wrong when best practices aren’t followed, it would really help gain a deeper understanding of tool results. For example, for Hot Spot analysis there’s a suggestion to use 30 input features. But why? Is this because the tool is built off the principle of the Central Limit Theorem?
3) A tool-picking flowchart. There are so many great tools out there. What the above questions really deal with come down to a question of “How do I pick a tool?”. I’d love to be able to load up a flowchart that tried to assess my spatial question. Am I concerned with just spatial patterns in and of themselves, or do I want to learn about spatial distribution of values associated with features? Once I find several tools of interest, I’d like to read about what their potential weaknesses are? Will the tool vary greatly if I change sample extent? Will strongly spatially clustered data skew results? Is zero inflation a problem? A lot this is the responsibility of the user to figure out, but it’s these types of questions we’re asking a lot in our class, which often works with non-ideal data sets.Thanks,
3) A tool-picking flowchart. There are so many great tools out there. What the above questions really deal with come down to a question of “How do I pick a tool?”. I’d love to be able to load up a flowchart that tried to assess my spatial question. Am I concerned with just spatial patterns in and of themselves, or do I want to learn about spatial distribution of values associated with features? Once I find several tools of interest, I’d like to read about what their potential weaknesses are? Will the tool vary greatly if I change sample extent? Will strongly spatially clustered data skew results? Is zero inflation a problem? A lot this is the responsibility of the user to figure out, but it’s these types of questions we’re asking a lot in our class, which often works with non-ideal data sets.Thanks,
– Max Taylor