Cloud Geospatial       


Raghu K. Ganti photo photo

Cloud Geospatial - overview

The IBM Cloud Geospatial team has been developing geospatial and spatiotemporal analytics for over a decade now. Our approach is developer centric and we created a library that enables a non-GIS expert to work with geospatial data in a seamless manner. The key features of this library are:

1. Full Earth: The library has implemented all the OGC specified 9E-DIM functions on the Full Earth without Cartesian Projections while not sacrificing performance. Hence, these functions are fully accurate and fast.

2. Geohashes: Geohashes are natively supported in the library on *all* geometries. This enables representation of uncertainity in a fundamental way and also provides significant speedup while querying and indexing geometries.

3. Built to scale: The library integrates with large scale platforms such as Spark, noSQL stores, and Streams. We have demonstrated 

4. Trajectory: Trajectory support is natively available; algorithms for sub-trajectory mining, trajectory clustering that work on varying size and granularties are supported.

5. Integrated and available through IBM products: Streams, SPSS modeler, DB2 Analytics, IIAS, SQL Query, and Geospatial Analytics on Cloud.