ENVI Services Engine: Scientific Data Analysis and Image Processing for the Cloud

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1 ENVI Services Engine: Scientific Data Analysis and Image Processing for the Cloud Bill Okubo, Greg Terrie, Amanda O Connor, Patrick Collins, Kevin Lausten The information contained in this document pertains to software products and services that are subject to the controls of the Export Administration Regulations (EAR). The recipient is responsible for ensuring compliance to all applicable U.S. Export Control laws and regulations.

2 Agenda Cloud Computing ENVI Services Engine Architecture Example Applications April 23,

3 Anticipating New Trends in the Geospatial Industry Key Issues Challenging the Traditional Desktop Paradigm Data Volume, Analysis Needs IT Budgets, Resources Looking Ahead > Centralized Big Data > Broader consumer base > Distributed access to best in class analytics Workstation Applications Mobile Devices Browser Access

4 Cloud Computing Advantages IT Resource Utilization > Centralized storage & tools reduces redundancy, costs > Scalable, distributed processing power Process Standardization & Collaboration > Reference repository for data, fewer silos of excellence > Standardized workflows for consistent, accurate results > Develop once, deploy many April 23,

5 ENVI Analytics in the Cloud: Online, On Demand DATA Analytical Functions App Developer ENVI IDL Python Java C++ Others ENVI Services Engine Implementations: Standards-based; Middleware agnostic April 23,

6 The ENVI Services Engine Workflow App Developer ENVI IDL Python Java C++ Others Apps Data Store ENVI Services Engine Process Process HTTP/REST Middleware System e.g. ArcGIS for Server Client Interface Interface with other enterprises Services Service Interface Browser Mobile Workstation Applications Find the latest changes in my area of interest April 23,

7 The ENVI Services Engine Workflow Service Interface Browser The Front-end Client Mobile Any client that can make an HTTP call Workstation Applications Find the latest changes in my area of interest April 23,

8 The ENVI Services Engine Workflow The Middleware Component Middleware System e.g. ArcGIS for Server Client Interface Interface with other enterprises Any middleware that uses REST protocol April 23,

9 The ENVI Services Engine Workflow App Developer ENVI IDL Python Java C++ Others Apps ENVI Services Engine Process Process The Analytical Engine Data Store Scalable: runs on a single server, multiple networked servers or the Amazon cloud April 23,

10 The ENVI Services Engine Workflow App Developer ENVI IDL Python Java C++ Others Apps Data Store ENVI Services Engine Process Process HTTP/REST Middleware System e.g. ArcGIS for Server Client Interface Interface with other enterprises Services Service Interface Browser Mobile Workstation Applications Find the latest changes in my area of interest April 23,

11 Use Scenarios Online, on-demand client-server The NGA system integrator needs to provide online, on-demand geospatial processing as web services. The image analysts need to run various ENVI processing from a variety of clients web browser, mobile device or desktop. The processing services need to scale to the size of the enterprise network or the AWS cloud instances, so incoming requests (100s or 1,000s simultaneously) can be handled without lengthy queuing of jobs. Batch processing of images The commercial data provider continuously collects large volumes of images that need to be processed within a limited time period. When a natural disaster hits, they need to deliver processed imagery of the impacted area as quickly as possible. Their ENVI developer needs a processing solution that provides load balancing and can scale to the changing demands on their server-based network. 11

12 Example Applications Preprocessing On Demand Cal, AC, Cloud masking Change Vectors Water Quality Analysis Landsat 5 Format Conversation AVIRIS April 23,

13 Examples, Con t Vegetation Health Vegetation disturbances/habitat monitoring Feature Extraction Quickbird Image Segmentation Quickbird Quickbird NAIP April 23,

14 A Reference Implementation ENVI Services Engine allows the user to package specific pieces of ENVI analytical functionality, Apps, and wrap them as a callable service for the engine. Reference Implementation Apps : Anomaly Detection > Find specific instances of anomalous materials from a large, uniform scene Pan Sharpening > Sharpen multispectral datasets by fusing it with higher resolution panchromatic data. Vegetation Delineation > Quickly identify the presence of vegetation and to visualize its level of vigor. Line of Sight > Build a viewshed of an area based on a digital elevation model, and the location and radius of the target. Find Red Roofs and Find White Planes > Leverage target detection algorithms for identifying a specific feature type in a scene. A representative web client, showing the available apps A view of the Line of Sight app, as seen on an mobile client 14

15 Implementation Benefits > Remotely access data and analysis routines from the field > Server-based: Cost savings resulting from reduced hardware, software, and administration overhead > Interoperability: ability to integrate with any existing IT infrastructure > Collaboration: data and workflows sharing across an enterprise ENVI Services Engine April 23,

16 Thank You 2013 Exelis Visual Information Solutions, Inc.

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