ArcGIS Pro

What’s new for Spatial Statistics in ArcGIS Pro 2.8? Data Engineering and more!

The latest release of ArcGIS Pro 2.8 focuses on performance and productivity. The Spatial Statistics team is excited to share some of the new capabilities in ArcGIS Pro 2.8. These include streamlined data preparation, new conversion tools for SAS® datasets, a new tool for smoothing time series data, updates to clustering methods, new and improved geoprocessing messages, and performance improvements.
Let’s look at some of these in more detail.

1) Data Engineering

We have introduced a dedicated view in ArcGIS Pro 2.8 to streamline your data preparation tasks. This view is called Data engineering. It will help you explore, visualize, clean, and prepare your data quickly and confidently. In addition, the Data Engineering view and its associated ribbon help you better understand your data and prepare it for spatial analysis and mapping workflows.

In the Data Engineering view, you can do the following:

2) SAS®-ArcGIS Bridge

New at ArcGIS Pro 2.8, the SAS-ArcGIS Bridge consists of two new geoprocessing tools for converting between SAS datasets and Esri tables, as well as the SWAT and SASPY Python packages, which allow you to use SAS procedures and custom SAS code in notebooks. Additionally, SAS is now an alliance in the Esri Partner Network.

New tools:

3) Time Series Smoothing

Time series are often messy, and noise can hide important patterns.  Time Series Smoothing removes the noise in time series and often makes the underlying signal clearer.

The Time Series Smoothing tool smooths a numeric variable of one or more time series using centered, forward, and backward moving averages, as well as an adaptive method based on local linear regression. After smoothing short-term fluctuations, longer-term trends or cycles often become apparent. This tool is available in the Spatial Statistics toolbox (Utilities toolset).

 

An illustration showing time series smoothing
An illustration showing time series smoothing.

4) Density-Based Clustering with Time Enhancement

Density-based clustering tool finds clusters of point features within surrounding noise based on their spatial distribution. In ArcGIS Pro 2.8, the two algorithms, Defined distance (DBSCAN) and Multi-scale (OPTICS) have been enhanced to find spatio-temporal clusters.

The new Time Field and Search Time Interval parameters identify clusters of points in space and time. In addition, new 3D options and charts have been added to better understand the patterns.

 

A screenshot from the Density Based Clustering tool output showing clusters in space and time.
A screenshot from the Density Based Clustering tool output showing clusters in space and time.

5) Other performance and productivity improvements

The incremental spatial autocorrelation tool has been improved to work with larger datasets with better speed and performance.

Various tools now use HTML formatting for their geoprocessing messages.

 

A screenshot of Forest based classification and regression tool's new and improved HTML formatted message.
A screenshot of Forest based classification and regression tool's new and improved HTML formatted message.

For a complete list of all the new capabilities in ArcGIS Pro 2.8, see What’s new in ArcGIS Pro 2.8.

About the author

Ankita Bakshi is a Technical Product Engineer on Spatial Statistics Team at Esri. With a background in environmental engineering and computer science, she is passionate about solving social, economic and environmental problems with Spatial Analysis and Data Science. In her role, Ankita enjoys researching, finding solutions to build software and also loves creating video and written content to make the software tools more approachable and applicable to real world challenges. Outside of work Ankita enjoys going on hikes, painting landscapes and listening to Bollywood music.

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