The Space Time Pattern Mining toolbox contains statistical tools for analyzing data distributions and patterns in the context of both space and time. It includes a toolset for visualizing the data stored in the space-time netCDF cube in both 2D and 3D.
Create Space Time Cube takes point datasets and builds a multidimensional cube data structure (netCDF) for analysis. Emerging Hot Spot Analysis then takes the cube as input and identifies statistically significant hot and cold spot trends over time. You might use the Emerging Hot Spot Analysis tool to analyze crime or disease outbreak data in order to locate new, intensifying, persistent, or sporadic hot spot patterns at different time-step intervals. The Utilities toolset contains tools for visualizing the data stored in the space-time cube in two and three dimensions. These visualization tools can be used to understand the structure of the cube, how the cube aggregation process works, and also to visualize the patterns over time at specific locations of interest. See Visualizing the Space Time Cube for strategies to allow you to look at cube contents.
Summarizes a set of points into a netCDF data structure by aggregating them into space-time bins. Within each bin, the points are counted and specified attributes are aggregated. For all bin locations, the trend for counts and over time and summarized attributes are evaluated.
Identifies trends in the clustering of point counts or attributes in a netCDF space-time cube. Categories include new, consecutive, intensifying, persistent, diminishing, sporadic, oscillating and historical hot and cold spots.
This toolset contains tools for visualizing the variables stored in a netCDF cube.
www.esriurl.com/SpatialStats contains an up-to-date list of all of the resources available for using the Spatial Statistics tools, including the following:
- Free web seminars
- Books, articles, and white papers
- Sample scripts and case studies