Regularly working with big spatial datasets in your organization? Often too big to render, analyze and interpret? One way of dealing with this challenge is the use of a support geography - a simplified representation of your data that is more manageable. Spatial Indexes are multi-resolution, hierarchical grids that are “geolocated” by a short reference string, rather than a complex geometry. Smaller to store and faster to process; they out-compete conventional geometries for complex data analysis and visualization. In CARTO's recent guide (Spatial Indexes 101) you can find out more about how they work and why you should be using them in your analysis. Download here!
Matthew Forrest is the VP of Spatial Data Science at CARTO and is passionate about using and sharing ideas around modern GIS, helping others to use a variety of new tools in their geospatial workflows. Matthew graduated from the University of Wisconsin-Madison with a degree in Geography and has been working with GIS and in Geospatial for 11 years, the past 7 at CARTO. He has worked with businesses and governments of all sizes and scales, and enjoys helping others advance their GIS careers.