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Visualizing and Analyzing Imagery with ArcGIS
Convener: Alexandru Vasile  | Co-Convener: Ionut Cosmin Sandric 
Thu, 27 Apr, 17:30–19:00  / Room -2.16
ArcGIS Pro provides a rich collection of tools to manage and serve large collections of imagery. There are two features that make up the core components of image management: mosaic datasets and raster products. Traditionally, a mosaic is created when you stitch together a collection of images to create one seamless image. The mosaic dataset can do that, but it also uses image attributes, such as acquisition date, cloud cover, or spatial resolution, to help you manage a huge collection of imagery, even one comprised of overlapping images or images with varying spatial resolutions. The mosaic dataset processes the imagery in-memory, enabling it to quickly display your imagery of interest, regardless of the size of your collection. Traditionally, image and raster analysis is realized through geoprocessing tools. The geoprocessing tools, Python scripting, and Model Builder work in unison to provide efficient automation of data management operations in the geoprocessing framework. While t hese geoprocessing tools are vital to many workflows, there is another modern approach to image and raster analysis that processes and displays your results immediately as you pan and zoom to imagery. This approach uses raster functions to process imagery as it is accessed. Raster functions work in-memory and avoid the time and overhead of reading and writing intermediate files to disk.
In this course, you will learn how to use out of the box raster functions as well as create custom raster function chains (such as a site suitability analysis) and apply it to your mosaic dataset to get a quick understanding of both your data and your analysis model. Afterwards, you will learn how to attach several raster chain templates to a mosaic dataset which will be served out as a service to a portal; this service can be than consumed by clients along with the associated raster function chains (with on the fly processing done by the server).