Geomorphic Change Detection Software

Calculate Linear Extraction of DEM


The Calculate Linear Extraction from Profile Route tool allows you to select a profile route from your Profile Routes LIbrary, and extract DEM values and error surface values off of that route at a specified sample spacing. The results are extracted to a CSV file, and can be exported into a database for visualization and interpretation in the Cross Section Viewer.

The command window looks like:



This short video shows you how to run the Calculate Linear Extraction from Profile Route command:


You do need to have a Linear Profile Route in your Profile Routes library to perform an extraction.


Working with the Results


If you want to view the results, right click on your linear extraction of interest, and click on View Linear Extraction Folder. This brings up the output folder in windows explorer (for the example in the video it is below):


Using CSV file in Excel

You can open the *.csv file in Excel (note you may need to open it from Excel instead of just double clicking), and you will see a simple spreadsheet of the result of the extractions:


The fields are as follows:

Field: Description:
fid The FID for the feature route. Note that if multiple routes (e.g. cross sections) are in the linear profile, they each get a unique FID identifier
Distance The linear distance (streamwise) between cross sections (if applicable) to facilitate
station The distance along an individual feature route (note this increments by the chosen sample distance)
x The X coordinate
y The Y coordinate
Surface Name The elevation value at that station along the profile route from the DEM Surface
Error Surface Name The value +/- of elevation error from the chosen error surface

You can manually plot these profiles using the station field for your horizontal axis and the Surface and Error Surface fields for your vertical in R or Excel or your favorite graphing program. You can also export them to the Cross Section Viewer.

This wandering video shows how to stumble through manually plotting up one of the 38 cross sections extracted in the above example all to make one figure:


That alone should highlight the value of extracting these to a database and leveraging the Cross Section Viewer.

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