Hi all, I have a region where soil survey maps have showns distinct sub-areas based on soil types, geology, and also vegetation. This can also somehow be observed in a visual interpretation of the hillshade map, which suggest a relationship with elevation.
I am trying to do something which (because of my lack of knowledge in the field) I don't know if it is feasible and/or sensible at all. 1. I would like to apply a moving window based voariogram algorithm to calculate varogram ranges and map them coutinously through the whole area covered by the DEM. 2. Then I would use this range map to classify the DEM into distinct areas following a fuzzy k-means (preferably) or a k-means approach. 3. Later I would fit a separate variogram model to each class in 2) and derive the range in that class. 4. Finally I would use each range calculated in 3) as "the search radius" to calculate 2 DEM derivatives (elevation percentile and local relief) in a plan to delineate landform units using an algorithm that uses these 2 derivatives as part of its input variables. This I believe would optimize the calculation of these 2 parameters since the search radius is estimated differently in the original algorithm. I was wondering of course if it is possible at all and sensible to use fuzzy k-means to segment raw DEM data in such a way, and if yes how could this be done? If sensible, is it then possible to use variogram ranges (derived as mentioned above) as kind of soft information to fuzzy k-means (or k-means) a DEM, or this could be simply done on the DEM directly. Thank you very much for giving me your thoughts on this. I am not very familiar with this subject, so plz excuse my ignorance if there's something that's not clear in my message. Oumar + + To post a message to the list, send it to [email protected] + To unsubscribe, send email to majordomo@ jrc.it with no subject and "unsubscribe ai-geostats" in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list + As a general service to list users, please remember to post a summary of any useful responses to your questions. + Support to the forum can be found at http://www.ai-geostats.org/
