Geospatial Big Data processing, OGC standards and Cloud Computing intersection and resulting opportunities

These are three technological concepts that have emerged to organically play nice together and tremendously tilt the landscape of spatial data handling from storage, processing and consumption. This intersection will definitely reinvent how we use geo-information in the various verticals.

There is strong emergence of cloud geospatial processing algorithms implemented on cloud platforms like Geobrain and Terradue a cloud platform offering Data-as-a-service, Processing APIs for Earth observation data. Terradue has provided a collection of open source tools through their Github repos.

Cloud computing has definitely had a significant impact on computer science and other domains. And the Geospatial industry has definitely warmed up to this new entrance with massive investments in development of platform-as-a-service, Data-as-a-service, and processing APIs (SAAS).

Cloud like implementations that may as well be on premise deployments delivering massive processing power running on virtualized servers with parallel processing have opened the possibilities never experienced before by the industry. These implementations have exponentially increased the amount of data consumed by businesses that otherwise may not have had that massive computing capacity.

OGC standards growth, stability and industry wide adoption

OGC standards have profoundly promoted the sharing and interoperability of geospatial data. The wide niche of GIS meant that solution providers had to factor in support for various formats of data. Through implementation of OGC standards, this has become possible. One can move their data from one software to another without degradation of semantics.

The geospatial SAAS or PAAS newbies could not have made it without the great work by the OGC. Their defined semantics for developing interoperability interfaces in applications and semantics for data representation has contributed two folds to the rise of Web GIS running on open source backbone.

Open Source growth and industry wide adoption

On the other hand, the revolution is being made possible by the growth of open source tools or enterprising of the open source approach to software development.  With the large developer communities backing OpenGIS products, these tools have become very mature and highly competitive in functionality and usability. The open source cloud platforms like CARTO and Mapbox are heavily giving their proprietary compatriots like Esri a run for their cloud revenues.


The intersection between these three technological dimensions have given birth to highly usable and maintained products such as Carto, MapBox, OpenGeosuite, Digital Globe’s GDBX, QGIS Cloud, NASA’s Geobrain, Terradue Cloud Platform and  among others.

The fight for the geospatial big data processing and visualization is another angle upon which exploitation of values of cloud has gone a notch higher. The traditional GIS companies are now facing a new kind of competitor or friend depending on how you look at it. The realization of the value of location intelligence component of data by Business intelligence companies is proving to be a viable industry on its own. Platforms like Tableau, Power BI, SAP Lumira, IBM Watson, Qlik and other business intelligence solutions are aggressively introducing mapping capabilities into their products. This has quickly become a partnership frontier in the industry as every mapping API provider now wants their API integrated into these solutions.

Steve Ochieng
About Steve Ochieng 18 Articles
Geospatial Specialist | Avid Reader and Vivid Writer here | Geospatial Tech Advocacy and Evangelism | GeoProgrammer and Follower of @geohipster