To get a measure of intensity of feature clustering, this tool uses a space time implementation that considers the value for each bin within the context of the values for neighbouring bins. The Emerging Hot Spot Analysis tool will identify trends in the clustering of earthquakes, setting my Analysis Variable parameter as Count. Let’s now take a look another tool, consuming the space time cube that I already created as the input. However, prior to this I need to ensure I have inserted a scene into my Project.Įxploring my space time bins, I can see that there appears to be a slightly higher count of earthquakes that occurred to the south of the Ikara-Flinders Ranges National Park between 19. To do this, I will need to run the Visualize Space Time Cube in 3D. The next step I will now want to complete is to visualise my space time cube in 3D. Right clicking on the Message entry in the Results window and selecting View will display the results in a message box. Try to find a balance between making your distance interval too large and loosing the underlying patterns or too small so you end up with heaps of cubes filled with zero.Īfter running the Create Space Time Cube tool, it is important to check the results of the tool. You will want to select a Distance Interval that makes sense for your analysis. If the data spans a year, you may want to look at trends in terms of monthly or weekly. If you are looking at crime events across Adelaide for example, you may want to decide to aggregate points into 400 meter bins because that is about a city block. As my data covers a large area and earthquakes don’t exactly occur right at the same location I need to consider adjusting my bin dimensions to be relatively large. In most cases you will not know how to define the cube, the strong recommendation is to think about what is the appropriate dimensions should be for the particular question you are trying to answer. The distance interval is basically how large the space time bins should be. The final optional parameter I need to consider is the Distance Interval. I am going to specify mine to be End Time. Another important parameter to think about is the Time Step Alignment when aggregating your data, because it determines where the aggregation will begin and end. As my data spans 58 years, I may want to consider aggregating the bin time slice to be 4 years. The first optional parameter – Time Step Interval, will often need to be considered and specified. The hardest part is deciding what or if you need to specify anything for the optional parameters that can alter the cube dimensions. The default parameters for the tool are fairly self-explanatory and are explained here. Graphic depicting how a space time cube is created Which I then subsequently created a feature class. The quake data was sourced online from Geoscience Australia as a csv, recording the last 58 years of earthquakes across the State. So, let’s explore how we can utilise some these tools to analyse earthquakes that have occurred across South Australia. Several tools, including Create Space Time Cubes, Cluster and Outlier Analysis, Emerging Hot Sport Analysis and Grouping Analysis assist with answering these difficult questions. Where your decisions or resource allocations effective?.With the evolution of ArcGIS Pro we now have the opportunity to not only successfully analyse patterns of time and space, but also immerse in a deep 3D visual experience.ĪrcGIS allows you to exploit the space and time aspects of your data, allowing you to answer questions like: Space time analysis seeks to understand when and where (and sometimes why) things occur. Everything happens at a place and occurs at some point in time.
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