Module 5 - Spatial Statistics

This week we took a bit of a break from cartography, and completed an ESRI virtual training course on spatial statistics, called "Exploring Spatial Patterns in Your Data Using ArcGIS". Unlike "traditional statistics", (what most of us learned in high school or college), "spatial statistics" incorporates space, proximity, area, and connectivity to analyze distributions, patterns, processes, and relationships from a spatial perspective.

One of the most important lessons I took from this lecture was that we must first explore our data using spatial statistics so that we can properly choose the correct analysis tools to maximize our efforts in providing quality outputs for important decision-makings at the hands of stakeholders.

The way we figure out which analysis tools to use is by first determining whether our data fits the characteristics of a normally distributed dataset. Some of these characteristics include the mean and median having similar values, skewness with a value equal to zero, data density distributed along a bell-shaped curve, and more. For our lab assignment, we learned how to look for these characteristics by running a few tools: the Mean Center Tool, the Median Center Tool, and the Directional Distribution (Standard Deviational Ellipse) Tool all found under ArcToolbox > Spatial Statistics > Measuring Geographic Distributions in ArcGIS Desktop. Our task was to determine which areas in western and central Europe should issue a freeze advisory based on the current readings provided by weather monitoring stations across the region. The results are seen below in my final map product.