Some time ago, a client told me that he has about three hundred aerial images and fifteen digital elevation models (DEMs) of the same area. He wants to use these datasets to construct a single image that his technicians can use to view and analyze. Basically, he was looking for an option to store, manage, view, and query small to large collections of raster and image data in a rather simple way using ArcGIS, hey who doesn’t.
Currently, the client and his team work with these raster datasets one at a time. For example, adding and checking to see which image covers their study area, one by one, which is, you know, very tedious.
Here is some good news: in ArcGIS 10.0, you may be glad to know that you can manage large amounts of raster datasets using a great new geodatabase data model called mosaic datasets. And yes, this functionality is available as part of the core.
What makes them different and great?
Here is the story – just like how one raster dataset stores data (photographic, elevation etc) as a continuous grid over a given area, mosaic datasets store many rasters over larger areas and present them seamlessly.
Not only large areas, but these mosaic datasets can bunch up individual datasets from different times – yes, I do mean temporal mosaics. If you have imagery of the same geographic area from several years, you can keep them all together in a single mosaic dataset, which could be used for tracking changes. And the datasets do not have to be adjoining or overlapping but can exist as unconnected or discontinuous datasets.
Also, some simple functionalities like hillshade, slope, aspect etc, which were available as separate tools in the Spatial Analyst toolbox are now a part of the mosaic dataset data model. Meaning, if you would like to be able to see hillshade of an area, you can now simply add that function to your mosaic dataset that contains your DEM(s); you don’t have to specifically run another tool and handle a different dataset for this purpose.
Mosaic datasets also have advanced raster querying capabilities and processing functions and can also be used as a source for serving image services.
Doesn’t this sound great!? – a single dataset that extends the meaning and use of a raster dataset not only by blending their neighbors in space and time but also by offering derived products from the base rasters as functions to run and view on the fly. To top it off, these datasets carrying analytical results can be easily served to clients and users as seamlessly. Needless to say how many more steps and individual files does this save.
Contributed by: Sirisha Karamchedu