Lab 4: Hot Spot Analysis

Sheela Bhongir

Geog 406

Hand-in 1

Hand-in 2

Hand-in 3

Questions

1. What is hot spot analysis and why is it important?
1. Hot spot analysis is a spatial statistical tool used to determine whether an area with values displays a statistically significant clustering pattern. Such a pattern is considered to be statistically significant if the value is surrounded by other similar values. For example, if a high value is surrounded by other high values then the output of the hot spot analysis would indicate a high z-score value. In other words, the values show a significant clustering of points. This tool is important because it can help policy makers understand areas where they should focus their attention to. Hot spot analysis can help us better analyze crimes, voting patterns, economic geography and other phenomena in a spastically analytic fashion.

1. In the tutorial, you used ModelBuilder. Why? How was it helpful?
1. This analysis involved many steps and ModelBuilder helped us understand all the different geoprocessing components used to run the hotspot analysis. We used modelbuilder so all the geoprocessing elements could run at once upon final execution. If any changes had to be made, ModelBuilder made it easy to redo a step.

1. In the beginning of the exercise, you set some parameters in the “Environments” dialog box.  How was this helpful during the rest of the exercise?
1. The environments dialog helped us apply the same settings for all the components of the model. The environments set for a particular process will override all other settings.  This will help ensure the same projection, output value, and location where we save all the data.

1. Describe one new concept or tool you learned about during the exercise.
1. One new tool I learned was the Integrate tool. This tool snaps together nearby incident points based on a user defined threshold distance. I played around with this tool and set different threshold distances. I noticed that the higher the xy tolerance, we noticed more clustered. With lower xy tolerance I noticed less clustering.

1. Answer the following question from page 10 of the tutorial: What would your recommendations to the Portland area authorities be, based on the hot spot analysis exercise?
1. I would advise the Portland area authorizes to set up a emergency service station in the red colored clustered zone. This area receives the most number of calls. The areas in blue receive the lowest amount of calls and the areas in cream receive a medium amount of calls. If more resources are available then the red and cream colored zones statistically show enough demand to justify the creation of a new emergency service station.

1. What is the purpose of the Generate Spatial Weight Matrix tool?
1. This tool is used to create Spatial Weights file and is particularly helpful when using large datasets. It constructs a spatial weights matrix (.swm) file to represent the spatial relationships among features in a dataset.