Applying a raster transfer-mode in a multi-scale map context
I've created a hillshade to represent the topography and the corresponding contour feature class for use in a multi-scale map service. (With help from the great info here on the Mapping Center. Thank you for a great resource!)
I found that I could improve legibility and better communicate the character of the surface by "multiplying" the counter layer "into" the hillshade (i.e. multiplying an anti-aliased raster of the contours with the hillshade raster).
Unfortunately, using the traditional raster analysis tools to do this at each the dozen or so different scales I'm working with (from 1:300 - 1:128,000) would be challenging, to say the least, and for the larger scales, impractical. Nevermind the difficulty of keeping it current as we get more and more accurate data. Suggestions?
Mapping Center Answer:
You could batch process the rasters using Python scripting since it sounds like you are simply using math algebra to combine two raster datasets. However, if you are not familiar with Python scripting then it might take longer to write a new script than simply processing the 12 sets of rasters individually.
Of course, you could build a very simple model in Model Builder and then simply change your inputs and outputs. I will be posting a blog entry tomorrow with a Model Builder template model that you can download and use to string together the tools you need to use. You might want to give it a try once the blog is posted.
In the meantime, you could use Model Builder with the Spatial Analyst math tools to create a very simple model that combines your rasters. Then you can use it 12 times to process your twelve raster data sets.
Incidentally, another advantage of scripting or using models is that it documents your data processing methods for future reference.
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