Given your objectives, I think r.param.scale or r.prominence would be your best choices.
Michael On Jun 14, 2012, at 2:29 AM, Thomas Lee wrote: > Hi Michael > > My approach of voting is trying to solve the subjective human perceptaion of > landforms per culture. > > Voting here means sample population test at defined culture such as > Culture 1, Sample size n = 300, Mean = 5, S.D. = 2, Sampling Time = T1 > Culture 2, Sample size n = 500, Mean = 4, S.D. = 3, Sampling Time = T2 > Culture 3, Sample size n = 1000, Mean = 6, S.D. = 1, Sampling Time = T3 > > They are dynamic and can be stored in a database. > They are temporal information (voting information), subject to change per > year (or per month depended on the attribute sensitivity to the time), per > culture (spatial location). > It is better put in a web database server and update globally and remotely by > mobile device such as android phone and iphone. > > All come together as a knowledge base (I am used to do it in my M.Sc. thesis, > about 20 years ago, on spatial decision support system for > location-allocation analysis using concept of expert system, knowledge base, > model base, data base.. etc) > > Thanks for introducing "Prominence". > It is same as the Feng Shui "Mountain Ridge" system logic (or Form School). > The masters have been studying these for, it is beleived that, thousands of > years. > Their concept is to locate the best site by studying the lineage of > prominence. > For country capital, they focus in top range or high level hierarchies > lineage of prominence > For smaller captial such as provincial capital, they use middle range lineage > For small city or village, they use lower range lineage. > > The spot they want to locate is likely a flat area at the end of a gentle > slope ridge line with big openning in front and surrounded by embracing > ridges. > With this pattern, stream lines will be converged in front of the site and > having high quality of soil content suitable for substaintable living. > > I consider this logic can be proved by analyzing > - the prominence network > - length of lineage > - height of parent and subpeak > - total lengeth of river/stream network > - accumulated flow of water (accumulate rich content in water) > - accumulated length of ridge line (in Feng Shui, they interested in the > Energy (Qi) bring along through the mountain ridge line, longer the line, > high energy, better benefit to the site) > - formation of a complete mountain hierachies of line parent and subpeak > (stored in a mountain hierachy database) > - entropy of peak (distribution of peak) > - ridge pattern recognition (Feng Shui has its mountain dragon (ridge) > pattern system such as Lotus Pattern) > > The MH database > - Table of Mountain, point layer > - Table of lineage, line layer (route structure like road network with > junction as peak or subpeak) > - Table of stream node, point layer > - Table of stream/river, line layer (route structure) > - Table of event (like road side event such as accident, but here is Feng > Shui site, village, capital, city) > > Thomas > > > ----- Original Message ----- > From: Michael Barton > To: Thomas Lee > Sent: Thursday, 14 June, 2012 1:43 AM > Subject: Re: 回覆： Re: [GRASS-user] 回覆： Re: ridge extraction from DEM > > Hi Thomas, > > You can indeed come up with quantitative definitions. My point is that these > will have a variable match to subjective human perception of landforms. The > ranking you list below can be applied to any topographic prominence, > including landforms called hills, bluffs, ridges, etc. The question of ridges > (as long, relatively narrow landforms) is slightly different from one of > topographic prominence. There is in fact a module (I think it is called > r.prominence) in addons that will ID topographic prominence by various > characteristics that you can set. Maybe it would be of use to you. > > Michael > > > On Jun 13, 2012, at 10:20 AM, Thomas Lee wrote: > >> Michael >> >> The qualitative definition of ridge can be quantitatively modeled as >> >> size in metre; degree of size of ridge >> 1; 1 >> 5; 2 >> 10; 3 >> 50; 4 >> 100; 5 >> ..... >> 1000; 10 >> >> Normally a flat area bigger than 1000m is a platform where a small village >> can be accomodated. >> The above can be modelled by fuzzy membership function which can be >> implemented in GRASS >> >> By having questionaire in different cultures at different locations >> globally, the result could be like voting in expert system voting model for >> spatial decision support system. >> >> I am interested in the correlation of the spatial cluster of human >> settlement to the pattern of ridges. Not a ridge but spatial pattern of a >> group of ridges. >> It is going to test the Chinese Feng Shui concept. Feng Shui is the ancient >> technique in site selection. To find a site good for living over say >> hundreds or thousands of years for next generations based on geomorphically >> terrain pattern or Mountain Form. There are systems in Feng Shui where the >> Master study the ridge pattern (and stream pattern) to find the site with >> good soil content without using modern borehole or lab test technique. >> >> Thomas Lee >> >> >> >> ----- Original Message ----- >> From: Michael Barton >> To: Thomaswplee >> Cc: markus.metz.gisw...@googlemail.com ; direg...@gmail.com ; >> grass-user@lists.osgeo.org >> Sent: Wednesday, 13 June, 2012 1:39 AM >> Subject: Re: 回覆： Re: [GRASS-user] 回覆： Re: ridge extraction from DEM >> >> Thomas, >> >> Again, you'd have to look to see if this can give you the results you need. >> >> The word "ridge" is a qualitative term that refers to a general landform >> category. For your purposes, how high does a landform need to be to qualify >> as a ridge: 1m, 10m, 100m, 1000m? Similarly, how long does it need to be and >> what is the acceptable range of profile slope along a ridge-top? >> >> These feature extraction methods deal in numbers, so they will probably >> never exactly match the subjective perception of a landform as a ridge. This >> is especially true if you are interested in how people (in the past and in >> the present) perceive a landform and its suitability for settlement. But you >> should be able to get reasonably close to some kind of consistent perception >> of what is a ridge, and the GIS methods have the advantage of being >> explicit, transparent, and repeatable--essential for science of course. But >> there is probably no "best" method for ID of ridges. >> >> I haven't tried the convergence method, but will do so to see how it turns >> out. >> >> Michael >> >> On Jun 12, 2012, at 5:41 AM, Thomaswplee wrote: >> >>> What is the difference on convergence and ridge? >>> Both local convex quadratically double differentiated >>> >>> I am interesting in application of geomorphology vs social science such as >>> terrain analysis related to human settlement >>> >>> Thomas >>> >>> >>> >>> -------- Original message -------- >>> Subject: Re: [GRASS-user] 回覆： Re: ridge extraction from DEM >>> From: Markus Metz <markus.metz.gisw...@googlemail.com> >>> To: Margherita Di Leo <direg...@gmail.com> >>> CC: Michael Barton <michael.bar...@asu.edu>,grass-user grass-user >>> <grass-user@lists.osgeo.org>,Thomaswplee <thomaswp...@gmail.com> >>> >>> >>> On Tue, Jun 12, 2012 at 11:28 AM, Margherita Di Leo <direg...@gmail.com> >>> wrote: >>> > Hi, >>> > >>> > there is also r.convergence add-on: >>> > http://grass.osgeo.org/wiki/GRASS_AddOns#r.convergence >>> >>> BTW, the topographic convergence index is also available in >>> r.watershed in GRASS 7. >>> >>> Markus M >>> >>> > >>> > Regards, >>> > madi >>> > >>> > On Tue, Jun 12, 2012 at 4:24 AM, Michael Barton <michael.bar...@asu.edu> >>> > wrote: >>> >> >>> >> Invert the DEM by multiplying all values by -1 and adding the maximum >>> >> original height value. This makes the maximum height 0 and everything >>> >> less >>> >> than that increasingly greater than 0 >>> >> >>> >> Run r.watershed on the inverted DEM choosing stream segments as output. >>> >> >>> >> The stream segments from the inverted DEM are your ridgelines. You can >>> >> keep them in raster or thin them (r.thin) and convert them to vector >>> >> (r.to.vect). >>> >> >>> >> I've copied the GRASS user list again because this is a general question >>> >> that others might be interested in. >>> >> >>> >> Michael >>> >> >>> >> >>> >> >>> >> On Jun 11, 2012, at 7:29 PM, Thomaswplee wrote: >>> >> >>> >> How to make ridge vector line with reversed accumlated flow as in >>> >> watershed? >>> >> >>> >> Still reverse DEM plus vectorization of ridge raster? >>> >> >>> >> Thomas >>> >> >>> >> >>> >> >>> >> -------- Original message -------- >>> >> Subject: Re: ridge extraction from DEM >>> >> From: Michael Barton <michael.bar...@asu.edu> >>> >> To: thomas...@starvision.com.hk >>> >> CC: grass-user grass-user <grass-user@lists.osgeo.org> >>> >> >>> >> >>> >> Thomas, >>> >> >>> >> I don't remember posting anything about r.ppa. I did a quick search and >>> >> found a post by Māris Nartišs >>> >> (http://lists.osgeo.org/pipermail/grass-user/2005-October/030883.html). >>> >> >>> >> r.param.scale will extract ridges. You will need to adjust the optional >>> >> parameters (especially processing window size) to get the ridges you >>> >> want. >>> >> >>> >> An alternative method is to invert the DEM and run r.watershed on it, >>> >> extracting the 'streams'. The 'streams' of the inverted DEM will follow >>> >> ridges. >>> >> >>> >> Michael >>> >> >>> >> >>> >> >>> >> On Jun 11, 2012, at 9:26 AM, <thomas...@starvision.com.hk> >>> >> wrote: >>> >> >>> >> > Dear Michael, >>> >> > >>> >> > I am interested in ridge extraction but not able to find the r.ppa >>> >> > mentioned by >>> >> > >>> >> > >>> >> > Chang, Y.C., Frigeri, A., 2002. Implementing the automatic >>> >> > extraction of ridge and valley axes using the PPA algorithm in >>> >> > Grass GIS. In: Open Source Free Software GIS GRASS >>> >> > Users Conference, 2002. >>> >> > >>> >> > >>> >> > Implementing the automatic extraction of ridge and >>> >> > valley axes using the PPA algorithm in Grass GIS >>> >> > >>> >> > >>> >> > Do you have any solution since your message in 2007 about ridge >>> >> > extraction. >>> >> >>> >> _____________________ >>> >> C. Michael Barton >>> >> Visiting Scientist, Integrated Science Program >>> >> National Center for Atmospheric Research & >>> >> University Corporation for Atmospheric Research >>> >> 303-497-2889 (voice) >>> >> >>> >> Director, Center for Social Dynamics & Complexity >>> >> Professor of Anthropology, School of Human Evolution & Social Change >>> >> Arizona State University >>> >> www: http://www.public.asu.edu/~cmbarton, http://csdc.asu.edu >>> >> >>> >> >>> >> _____________________ >>> >> C. Michael Barton >>> >> Visiting Scientist, Integrated Science Program >>> >> National Center for Atmospheric Research & >>> >> University Consortium for Atmospheric Research >>> >> 303-497-2889 (voice) >>> >> >>> >> Director, Center for Social Dynamics & Complexity >>> >> Professor of Anthropology, School of Human Evolution & Social Change >>> >> Arizona State University >>> >> www: http://www.public.asu.edu/~cmbarton, http://csdc.asu.edu >>> >> >>> >> >>> >> >>> >> >>> >> >>> >> >>> >> _______________________________________________ >>> >> grass-user mailing list >>> >> grass-user@lists.osgeo.org >>> >> http://lists.osgeo.org/mailman/listinfo/grass-user >>> >> >>> > >>> > >>> > >>> > -- >>> > Dr. Margherita Di Leo >>> > >>> > _______________________________________________ >>> > grass-user mailing list >>> > grass-user@lists.osgeo.org >>> > http://lists.osgeo.org/mailman/listinfo/grass-user >>> > >> >> _____________________ >> C. Michael Barton >> Visiting Scientist, Integrated Science Program >> National Center for Atmospheric Research & >> University Corporation for Atmospheric Research >> 303-497-2889 (voice) >> >> Director, Center for Social Dynamics & Complexity >> Professor of Anthropology, School of Human Evolution & Social Change >> Arizona State University >> www: http://www.public.asu.edu/~cmbarton, http://csdc.asu.edu >> >> > > _____________________ > C. Michael Barton > Visiting Scientist, Integrated Science Program > National Center for Atmospheric Research & > University Consortium for Atmospheric Research > 303-497-2889 (voice) > > Director, Center for Social Dynamics & Complexity > Professor of Anthropology, School of Human Evolution & Social Change > Arizona State University > www: http://www.public.asu.edu/~cmbarton, http://csdc.asu.edu > > > > > > _____________________ C. Michael Barton Visiting Scientist, Integrated Science Program National Center for Atmospheric Research & University Corporation for Atmospheric Research 303-497-2889 (voice) Director, Center for Social Dynamics & Complexity Professor of Anthropology, School of Human Evolution & Social Change Arizona State University www: http://www.public.asu.edu/~cmbarton, http://csdc.asu.edu
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