3x3 pixel standard deviation filter to detect sharp topographical changes?

[GeospatialTechnology]

Hello,

Ive just been reading an academic paper where the author has used a 3x3 pixel standard deviation filter to detect sharp topographic changes on a DTM dataset, i.e. to highlight areas of greatest variation.

I was wondering if someone could tell me how I would go about reproducing this in ESRI ArcGIS. Just a point in the right direction would be great!

I have spatial analyst and other extensions. Is this possible to do this with the tools available with arcgis?

Thanks for any help!

[JeffreyEvans · Accepted solution]

This is just a focal function and is very easy to calculate in ArcMap. These tools can be found in the spatial analyst toolbox under Neighborhood > Focal Statistics. You should be thinking about representing this type of variation at more than one scale. Process occurs across scales and is not necessary responding to a 3x3 window.

The classic metric for topographic variation is the Topographic Roughness Index which assumes the form: sum of the squared deviations within a focal window, which is in essence variance. I have an ArcToolbox in development that has a variety of metrics and utilities including a few different measures of surface texture. The toolbox is only compatible with ArcGIS v10 or later.  

http://conserveonline.org/workspaces/emt/documents/arcgis-geomorphometrics-toolbox/view.html

[GeospatialTechnology]

Thanks Jeffery. I thought it would be relatively simple to do I just need to understand the process.

Thankyou very much for pointing me in the right direction!

I'll have a look at the tool you're developing and let you know how it goes.

I hoping to use the roughness index as a measure of the severity of erosion in upland areas here in the uk.

Thanks for your help 🙂