Random notes about ArcGIS Image Server from a session at th EESRI UC- Released with ArcGIS 9.2 late last year. Recall, imagery is a natural background for many GIS apps.
Useful for direct interpretation, statistics and analysis, used for vectorization (80% of vector data collected using imagery backdrop), data verification after GIS analysis. Diff. apps have diff demands on their imagery – time, quality, sun angle, etc…
Why Image Server?? Use of imagery growing exponentially Available from many sources (aerial cameras, scanned maps, satellites) Depth of imagery increasing, more bands of imagery, higher resolution, overlap in imagery (same image from multiple dates or diff. angles) Imagery is often available but simply not accessible (obviously Google Earth has addressed this) Fast access to imagery and metadata Directly reads multiple image formats and types Accessible from multiple clients On the fly server based processing Changeable image service properties Much more!
Recall, 3 Differentiators of imagery; - volume of data is magnitudes larger - imagery devalues quickly.. drops fast then becomes valuable again over time - fixed – imagery is a snapshot in time, however, the way we process imagery does change.
So, ArcGIS I.S. maximizes the value of your imagery: - Enterprise-wide data availability.. large datasets available to CSAD, GIS users - direct read of imagery in native format - on-the-fly server-based image processing - end users get fast image access
Demo showed… serving 500 2GB images (about 1TB)… very rapid pan and zoom, pixels are being ortho-rectified, fused, pan sharpened on the fly for distribution. Click image and view meta data within ArcMap Optionally alter image compression value to speed up navigation… then eliminate compression value once you’ve discovered an area of interest.
Components of Image server – Author (arcmap, service editor), Serve, Use Authoring an image service definition within Service Editor. Available as a toolbar within ArcMap. Use it to create and edit image service definitions. Add rasters, extract raster properties, georeference and process, define metadata – preview your service before serving to clients.
Demo – create a service - 100 TIF files (4.5 GB) 1.5 ft, NAD 83 and combine with Landsat data from landsat.org – 1 GB Landsat scenes, TIF in UTM format.
Input Rasters Direct access without data conversion enables rapid development Imagery can be tiled or mosaiced (DOQQ, NAIP, SRTM, CADRG), rectified, or non-rectified (Quickbird basic scenes). Various formats sare supported (TIF, NITF, BIL, SDE Raster Mosaic, JP2000, MrSID)
Demo – setup a server, configure, publish. - identify location and name of cfg file (wizard) - create a service provider cfg file - export data format - create data projection parameters - establish resampling method or compression for transmission - set background color, establish mosaic method, control for overlap
Create dynamically updated image services: Available image server processes: stack bands, image algebra, spectral matrix, greayscale, stretching, convolution filters (sharpen), pan-sharpen (fuse low-res with high-res) , trend, classify, colormap (show results of classifications), elevation visualization (hill shade, shaded relief), histogram
Image server is Simple to istall, no DBMS, no data conversion… fast implementation. A typical performance scenario… .2 sec/request processed per core, 72,000 requests/hr, support 120 concurrent users. Perfonrmance depends on image format (TIF is ideal), processing to be applied can add to performance.
The Road ahead Integration with ArcGIS server Image service added to ArcGIS server – similar to map or globe service Integration with ArcMap Add compiled service def’s from ArcGIS service manager or ArcCatalog
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