The VISeon Project
As demand for commercial and industry software services in the cloud has grown, so has the demand for cloud-based geospatial image analysis services. This demand has increased because it gives a wider user-base easy access to the tools needed to analyze geospatial imagery and make critical decisions, independent of where they are located. To explore the relationship between web-based services and geospatial products, we began developing the “VISeon Project”, which demonstrates the capabilities of our ENVI Services Engine in real-world cloud based applications. The ENVI Services Engine is a web-based platform that gives users access to ENVI image analysis tools and capabilities on variety of devices.
The goals for the project were to:
- Develop an enterprise system based on OGC standards and highlight the flexibility of the engine’s lightweight REST interface for integration.
- Demonstrate data discovery, visualization and processing through intuitive web and mobile clients.
- Illustrate how ENVI analytic capabilities could be accessed through simple apps accessing an enterprise server.
Using “Agile” development methods, which are “based on iterative and incremental development
”, our team was able to meet the project goals on a shorten timeline. In addition to developing a flexible web-based services engine we wanted to demonstrate that such an engine could be fully interoperable, work with other COTS products, and could be integrated with other applications and architectures.
During development, the VISeon Project, ENVI Services Engine, and associated apps were integrated with Esri’s ArcGIS for Server and BAE’s GXP Xplorer. We have since deployed Project VISeon in the Amazon Cloud to make it more readily accessible for demonstrations and continued development. Through the experimental development and deployment of Project VISeon, we have been able to see image analysis capabilities accessible in the cloud. This experience helps us understand how such capabilities would be used to address online and on-demand need of geospatial imagery users.
How do you see cloud based services impacting your image analysis?