I am extremely excited about the growth of geospatial in the non-GIS world. In some cases, technologists are reinventing geospatial analysis with a fresh perspective and better algorithms. In other cases, open source is allowing technologists to build geospatial capabilities into solutions without the overhead burden of a back-office GIS.

With all the exciting innovations in geospatial and location intelligence, what will happen to GIS? Touted by large vendors as a platform, GIS has become an expensive, bloated and complex set of tools bundled in an even more complex business model. But, there are some bright spots. New, forward-thinking companies are building geospatial capabilities into their products, not building applications on top of a big backend system. These solutions are designed for a particular market or problem and are faster, less expensive and reliable.

Signs of GIS decline

Geospatial data is increasingly available.

Many GIS projects were implemented to build and maintain geographic data. These datasets are becoming readily available for analysis, mapping, etc. For example, Koordinates focuses on publishing geospatial data. These datasets will fuel the growth of new/modern geospatial tools. Maintaining these datasets will be integrated into workflows that take advantage of new architectures and devices. Microsoft and Mapbox are working on HD maps that will be updated in real-time for example.

Other organizations such as MapD include geospatial analytics as part of the analysis engine for big data. (Note, MapD is now OmniSci.)

Satellite, drone, LiDAR and imagery data is now readily available. Companies are building applications to utilize this vast amount of data that is just not plentiful but current.

Geospatial analysis not just for specialists.

Large, well-known companies are integrating geospatial analysis and mapping right into their products.

Tableau - Adding spatial joins in the next release and focusing on geospatial analysis.

Amazon - Hiring a Geospatial Intelligence Engineer for their logistics team. I imagine they will make it available for others once they perfect it for their own use.

Uber - Recently released open source geo tools.

Foam - Building geospatial right into new technology frontiers of Blockchain.

Carto - Building geospatial solutions with ease-of-use in mind to leverage all the geospatial data available.

Microsoft is making a big push with Azure Maps. Keep an eye on their efforts including partnerships (like Mapbox) and hires.

Open Source continues to evolve.

I have to mention open source as a continuing trend. The Open Source Geospatial (OSGeo) community continues to grow and get more energy from government organizations like NGA and technology companies like Uber. Organizations like Boundlessgeo continue to support and expand on this dynamic market. And, I highly recommend FOSS4G events. They are always interesting and you get to meet the folks pushing the geospatial technology boundaries!

Looking forward

It just makes sense that traditional GIS, back office tools will be replaced in modern solutions and architectures. With the wealth of data and applications growing in the location/geospatial space, it is just a matter of time until GIS is a chapter in the history of geography textbooks. This is a good thing! Geospatial technology should be part of any modern analytics solution, not an addon.

I recently discussed this topic with Chris and Mark from Geoadorable. We covered many topics. Here is a sample:

With the mainstream emergence of business intelligence/data science as well as commoditized digital mapping are location specialists being marginalized?

Not at all. Individual GIS specialists will be if they keep looking back. The spatial skills that they master are not being marginalized. The particular GIS technology they use at their job will be commoditized but how they think about solving problems will be in even more demand. Technology comes and goes, but spatial problem-solving skills don’t. I've talked to a number of Data Scientists in Silicon Valley who are just now understanding the complexities of a spatial analysis. BUT once they get it, they solve it ways never thought of before! That is exciting. Teaming geospatial experts with AI/IoT/Machine learners, etc. will change how we approach many of our most pressing problems.

I go into more details in the podcast. Click here to listen to the full interview. Let know what you think!