GeoAnalytics Engine Blog

If you work with GPS data collected along routes you probably know that it can be messy as a result of GPS drift.  Tools like Snap Tracks are useful to clean up GPS data, by matching the GPS points to line segments.  But, you need a network dataset with from- and to-nodes defined.  In this post we explore how to add that information to network datasets.

Learn more about working with GeoAnalytics Engine in the Amazon Web Services EMR environment.

The Overture Maps Foundation released the second version of their world-wide open map data on October 19. These datasets have an incredible amount of detail and great coverage across the world, and you can easily incorporate them into your spatial analyses using GeoAnalytics Engine.  Let's take a look at how this works!

Point locations are an overwhelmingly common input to spatial big data analytics, but our raw data may not already have all of the attributes we need.  In this post, we'll explore ways to enrich point-level data to support big data analytic workflows using ArcGIS GeoAnalytics Engine.

This blog provides an example of the new Polygon Centerline function, which can help to convert GPS points for movement data into single polylines representing the common path across all tracks in the data. The functions and methods demonstrated can be used for consolidating any movement data into central paths.

This blog provides an example workflow with the new Nearest Neighbors tool. Discover how you can use the tool to determine what features (or objects or events) are closest to other features in big spatial datasets. 

This blog provides an example workflow with the new Snap Tracks tool. Discover how you can use the tool to improve visualization of track data, as well as calculate more accurate route and movement behavior patterns.