The Create Space Time Cube By Aggregating Points, Create Space Time Cube From Defined Locations, and Create Space Time Cube From Multidimensional Raster Layer tools structure and summarize datasets into a netCDF data format by creating space-time bins that form a cube-like structure. Each bin in the cube contains a value, or count, of the number of events that occurred at the bin location for the time-step interval specified. Additionally, the cube may contain one or more summary fields or variables with statistics for the attribute fields specified in each bin.
There are a variety of analysis tools in the Space Time Pattern Mining toolbox that you can run against the cube after it is created. The Emerging Hot Spot Analysis tool takes the netCDF cube as input; runs a space-time hot spot analysis (Getis-Ord Gi* statistic); and identifies trends in the aggregated count data, summary fields, or variables, such as new, intensifying, diminishing, and sporadic hot and cold spots. The Local Outlier Analysis tool also takes the netCDF cube as input and runs an interpretation of the Local Moran's I statistic to identify statistically significant clusters and outliers in the context of both space and time. The Time Series Clustering tool identifies the locations in the space-time cube that are most similar and partitions them into distinct clusters in which members of each cluster have similar time series characteristics. There are a variety of forecast methods in the Time Series Forecasting toolset that allow you to forecast and estimate future values and identify temporal outliers as well as a tool to help you evaluate and compare the different forecast models created. The netCDF cube is updated with the results of these analyses in the form of several new variables.
The data and variables stored in the space-time netCDF cube can be visualized in either two or three dimensions using the Visualize Space Time Cube in 2D or Visualize Space Time Cube in 3D tools located in the Utilities toolset. The space-time cube can be visualized and explored in three dimensions in a 3D scene. Visualization of the cube is useful for several reasons:
- It can help you understand the structure of the space-time cube and how the process of aggregation into the cube works.
- It can also offer insights into the results of Emerging Hot Spot Analysis, Local Outlier Analysis, and the other Space Time Pattern Mining analysis tools, providing evidence that can help you understand the results.
- Additionally, visualizing the value of the summary fields, variables, or other display themes can help you understand how confident you can be in subsequent analyses by displaying the spatial pattern of empty bins that had to be estimated or temporal outliers in your analysis.
Visualize the space-time cube in 3D
To visualize the space-time cube in 3D, complete the following steps:
- Open ArcGIS Pro.
- Open a scene. To open a scene so the results of the tool can be rendered in 3D, click the Insert tab, click New Map, and choose a new global or local scene.
- Set the elevation surface to zero. Because time is used as the vertical axis in visualizing the space-time cube, it is important for accurate interpretation that all locations on the ground be at the same elevation so all time-step intervals start at the same base. To do this, turn off the default elevation surfaces by clicking off any Ground layers that appear in the Elevation Surfaces group in the Contents pane.
Note:
The next time a new scene is added, the default surfaces populate again. - Open the Visualize Space Time Cube in 3D tool.
- Choose a cube variable to explore. After Create Space Time Cube By Aggregating Points, Create Space Time Cube From Defined Locations, or Create Space Time Cube From Multidimensional Raster Layer is run, variables stored in the cube include count as well as any summary fields or variables that you chose to aggregate when creating the cube.
- Choose a Display Theme option for the selected cube variable. The Value option allows you to see the raw numbers associated with aggregation or creation of the cube. You also have many other options depending on the analysis tools you have run on the space-time cube. For instance, the option to visualize Hot and cold spot results is available if you have run Emerging Hot Spot Analysis, and the option to visualize Cluster and outlier results is available if you have run Local Outlier Analysis on that particular variable. Summary variables also give you the option to display the estimated bins, so you can see exactly which bins were filled in based on your decisions when you created the cube.
- Choose where to save the output features and click Run.
Note:
If the data is not drawing, you may need to clear the Visibility Range limits, which you can do by selecting the new layer in the Contents pane, clicking the Feature Layer tab, and clicking the Clear Limits button.
Note:
- See Navigation to learn more about navigating and exploring your 3D scene in ArcGIS Pro.
- See Visualize temporal data using the time slider to learn more about enabling time on your 3D space-time cube and exploring the temporal aspects of your data.
- See Get started with the range slider to learn about different ways to explore numeric data stored in the space-time cube.
Explore 3D results using the time slider
The 3D space-time cube can be further explored using the time slider. To use the time slider, complete the following steps:
- In the Contents pane, double-click the output of the Visualize Space Time Cube in 3D tool and choose Time.
- Set Layer Time to Each feature has start and end time fields. Start Time Field and End Time Field are automatically populated, and Time Extent is automatically calculated. Click OK.
- Click the Time tab and set Span to 0. Uncheck the Use Time Span check box and set Step Interval to the Time Step Interval value of the input space-time cube.
- Enable time by clicking the time button to the left of the time slider, and use the arrows or play button to explore the results in your space-time cube.
Tip:
The Space Time Cube Explorer Add-in helps you interact with and explore your space-time cubes by automatically setting up time and range sliders for you. The Space Time Cube Explorer also allows you to display your cubes quickly with many preset layer symbology options in the Display Gallery. The Space Time Cube Explorer Add-in is available at www.esriurl.com/SpaceTimeCubeExplorer. Your 3D visualization of the space-time cube can also be shared as a web scene and used in stories.
Visualize the space-time cube in 2D
To visualize the space-time cube in 2D, complete the following steps:
- Start ArcGIS Pro.
- Open the Visualize Space Time Cube in 2D tool.
- Choose a cube variable to explore. After the cube has been created, variables stored in the cube include count, as well as any summary fields or variables that you chose to aggregate when creating the cube.
- Choose a display theme to display the selected cube variable. Examples of some display themes are as follows:
- Locations with data—Allows you to see all of the locations that contain data for the selected variable, and the Trends option shows where values have been increasing or decreasing over time (the results of the Mann-Kendall statistic run on the selected cube variable for each location). The Locations with data option is not available space-time cubes using defined locations (or when aggregating points to defined locations).
- Hot and cold spot trends—Shows where hot and cold spot z-scores are increasing or decreasing over time (the results of the Mann-Kendall statistic run on the z-scores of the space-time hot spot analysis for the selected cube variable), and Emerging Hot Spot Analysis results re-creates the results you saw when you ran the Emerging Hot Spot Analysis tool. Both Hot and cold spot trends and Emerging Hot Spot Analysis results are only available when Emerging Hot Spot Analysis has been run on the selected cube variable.
- Local Outlier Results—Re-creates the results you saw when you ran the Local Outlier Analysis tool for the selected cube variable.
- Number of estimated bins—Shows how many bins were estimated at each unique location, allowing you to see if there is a spatial pattern of places with missing values. If entire sections of the map have high numbers of estimated bins, those areas may be best left out of the analysis. Locations excluded from analysis shows those places that had data but had empty bins that could not be filled because they did not meet the criteria for estimation. Both Number of estimated bins and Locations excluded from analysis are only available for summary fields.
- Choose where to save the output features and click Run.