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Using a DEM, I assigned slope values to individual segments in a street network feature class. In some areas the slope values seem suspect, such as where a highway overpasses a local road. Is there a method to find those segments whose slope is radically different from adjoining segments (e.g. 5 to 25%) to locate possible inaccuaracies?

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You're probably looking for an automated/selection based solution, but you could also approach this from a manual, visual inspection. Symbolize your lines based on a classification of their slope attribute using however many classes you need to define 'radically different' and distinct colors, then pan the map and visually look for outliers.

For example 0-20% red, 21-40% blue, 41-60% green. Panning around it should be very obvious when you have one or two green lines in the middle of a bunch of red ones. Of course you'll have to do some statistical analysis of your slope range first to decide the best classes. Maybe 0-5% is pretty standard and most of the map, 5-10% in some steep areas, and anything over 10% is something funky going on. This method also shows if there is a transtion between slope classes or rapid jumps.

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Using python you could loop over each line feature and retrieve the slope values from the preceding and subsequent features. You could then calculate the difference and flag any outliers by writing to a new field. That's the theoretical approach.

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    The preceding feature as you step through a table is not guaranteed to be an adjacent connected edge in the network. You need to loop through each network edge and ask what is connecting, then do the difference and flag outliers. – Hornbydd Jun 18 '14 at 22:48
  • Good point. +1. – Radar Jun 19 '14 at 15:40

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