Mosaic Pivot Viewer Demonstration Using The Silverlight PivotViewer Control

It’s been a while since we have heard from the Applications Prototype Team in Redlands. As always they are busy working on the next greatest idea that could eventuate into a product or provide a good showcase of technology.

The Applications Prototype Team has built a sample web application using the Silverlight PivotViewer control to browse a large imagery collection of New Zealand. The Silverlight PivotViewer makes it easier to interact with massive amounts of data on the web in ways that are powerful, informative, and valuable and the team has been able to leverage these capabilities in this excellent demonstration.

The Silverlight PivotViewer control allows rapid image filtering and smooth zooming down to a full resolution of the imagery.

The lab integrated the ArcGIS API for Microsoft Silverlight/WPF into the application. Images that have focus will display a hyperlink labeled “View Map”. When the “View Map” hyperlink is clicked, a child window will appear containing ArcGIS.com’s topographic basemap and the source image service.

Imagery can be sorted and filtered in many different ways allowing you to quickly find the image you are after. Once found you can view the metadata for the image or the image overlaid on a map.

This demonstration can be viewed here: http://maps.esri.com/sldemos/… and a video walkthough can be found here: http://www.youtube.com/watch?v=…

As Richie mentions:

Using the PivotViewer demonstrates one approach for rapid discovery of content. However viewing an image in isolation is of limited use. Spatially enabling content with Esri’s Web Mapping API’s allows users to perform analysis.

This is a great example of how users can interact with a large amount of content in a quick, powerful and valuable manor using the power of Silverlight and the ArcGIS API’s. The next step would be to utilise some of the geoprocessing and analysis capabilities of ArcGIS Server 10 and allow users to download the image they have found via a clip, zip and ship task.

Richie has posted about this demonstration here: http://blogs.esri.com/dev/…