For this module we were to take an ESRI online course on spatial statistics. We had temperature data and a basemap of western Europe provided from the National Climatic Data Center. Our objective was to use spatial statistics using the ESRI learning course to determine where freeze warnings should be issued. During the course of the exercise, we examined our data using various spatial statistical techniques, including mean center, median center, and directional distribution. Mean center identifies the average X and Y value of all our data values, where the median center is the point at which the Euclidean distance between all points is at a minimum. When these two points are at the same location, the data is said to be normally distributed. We also looked at directional distribution in this exercise. This tool creates standard deviational ellipses that show the spatial characteristics of features, such as central tendency, dispersion, and directional trends (ArcMap).
This map shows an analysis of spatial statistics of western Europe weather monitoring stations and focuses on temperature data. The median center is the red triangle and the mean center is the blue square. They are geographically near each other, so the data is relatively normal in distribution. The directional distribution shows a generally west to east trend (WSW to ENE). I then added essential map elements to this map and the final result is seen above.
After this section, we also learned about histograms, normal QQ plots, Vernoi charts, semivariograms, and trend analysis.
I think this was a very good exercise to not only learn about spatial statistics in general, but also in how we can use these tools within ArcMap to gain valuable information about our data.
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