Open source tools for geospatial analysis, image science, and machine learning are breaking down barriers between traditional fields such as GIS, remote sensing, and computer vision and creating a new landscape for geospatial analysis. This emerging landscape offers the promise of automated mapping and extraction of features at unprecedented spatial and temporal scales. However, for many, that promise remains constrained by the availability and cost of high resolution imagery.

DigitalGlobe’s Geospatial Big Data Platform (GBDX) was built to solve this problem. Using GBDX, you can bring your algorithms together with a massive archive of high resolution imagery to perform geospatial analysis at scale. In this session we will provide an introduction to and hands on experience with GBDX, with a focus on one or more applications pertinent to OpenStreetMap.

The session will start with an introduction to GBDX and demonstration of its capabilities. We will then move into an interactive session where we will walk through an example of leveraging OpenStreetMap vector datasets and imagery analysis algorithms within GBDX to perform spatial and/or spatiotemporal analysis. We will close with a discussion of how GBDX is enabling base-mapping of features in the built and natural environment at continental scale.

There are no basic requirements for participants to follow along with the workshop and demonstrations; however, to participate in the interactive portions of the workshop, attendees will need:

• A laptop
• Basic experience with Python and geospatial analysis
• Pre-registration (in order to be provided access to the GBDX platform)

Register now to attend this workshop: http://explore.digitalglobe.com/GBDX-Workshop.html