SNAP Nutritional Food Allocation (2)
How patterns detection and spatio-temporal Data Analysis can help crime incidents analysis that change location over time? Or county tax rates analysis that are fixed locations with attributes which also change over time? Space-time pattern mining tools have applications in various domains, including transportation planning, urban studies, public health, environmental monitoring, crime analysis, and natural disaster management.
To find out how Supplemental Nutrition Assistance Program (SNAP) participation rates have changed over time and visualize them in 2D and 3D, I explored SNAP data patterns example from ESRI MOOC, using space-time pattern mining.
Space-time pattern mining tools in GIS refer to the methods and techniques used to analyze and discover patterns that involve both spatial and temporal dimensions. These tools allow for the exploration and identification of patterns that emerge over space and evolve over time.
This information can help in the allocation of SNAP resources to areas of higher food insecurities. The result can drive the decision to distribute resource in a more efficient and equitable way
In this example, by leveraging space-time pattern mining tools, we can better understand the spatio-temporal dynamics of various oscillating hot spots low SNAP participation rates (southeastern areas) but in recent years, have had high participation rates.
The North central areas of the United States have mostly diminished cold spots, which means that the areas have significant clustering of low SNAP participation rates, but the intensity of that clustering has been decreasing.
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