Re: [GRASS-user] Searching Docs about 3D geological modelisation
On Saturday 09 January 2010, Benjamin Ducke wrote: Cheers for these. They are certainly all highly interesting. Do you have an actual link for the T-PROGS software itself? All I can seem to come up with are interfaces from other software and publications mentioning it. I would certainly be interested in taking a look at your GRASS interface. Is T-PROGS open source? My gut feeling is that the T-PROGS approach would give better results than 3D kriging, as it seems better able to to follow 3D shape trends: http://chl.erdc.usace.army.mil/chl.aspx?p=sa=ARTICLES;37g=50 ... but that certainly would need testing. Having said that, I also like this approach for a more heuristic model: http://chl.erdc.usace.army.mil/chl.aspx?p=sa=ARTICLES;41g=50 It's very simple and could easily be implemented directly in GRASS GIS. In fact, I coded something very similar to this for archaeological stratigraphy reconstruction a while back. Cheers, Ben Hi Ben and others, Here are some concerns from the author of the TPROGS software: - Steve is hesitant because he's not sure what the finished product would be. I think he's probably concerned about misapplication or perhaps some kind of ripoff. Can you provide a bit more background on where you see this going? - I think that it would be helpful to put together a small proposal, regarding how the TPROGS source code / ideas would be integrated into GRASS. It seems like the author is worried about use without citation, and once he understands what GRASS developers have in mind, should be for it. To start the discussion, I propose that the methods used within the TPROGS software be integrated (with proper citations) into a GRASS library, so that a series of modules can perform the multi-step process associated with modeling transition probabilities. Furthermore, the GRASS rast3 (voxel) datatype should be used to store the resulting structures-- this will make visualization with NVIZ / Paraview a snap. Alternatively, we may be able to link GRASS with TPROGS with a little bit of python glue. While this may work if there are limitations regarding the use of the TPROGS source, I think that having these algorithms present in the GRASS libraries would be a real benefit. I have CC-ed Graham, so that we can keep him in the conversation. Cheers, Dylan - Original Message - From: Dylan Beaudette dylan.beaude...@gmail.com To: Benjamin Ducke benjamin.du...@oxfordarch.co.uk Cc: GRASS user list grass-user@lists.osgeo.org Sent: Saturday, January 9, 2010 4:30:40 AM GMT +01:00 Amsterdam / Berlin / Bern / Rome / Stockholm / Vienna Subject: Re: [GRASS-user] Searching Docs about 3D geological modelisation Two more ideas: 1. conditional simulation, based on a 3D variogram model 2. transition probability-based interpolation of categories Check out gstat for the conditional simulation, and TPROGS for the transition probability. If anything is interested, I have done some programming to connect GRASS and TPROGS. Cheers! Dylan On Fri, Jan 8, 2010 at 1:24 PM, Benjamin Ducke benjamin.du...@oxfordarch.co.uk wrote: Woohoo, this forum is always a treasure trove of good advice. I had not idea SGemS existed! The Voronoi idea is also good, I am just not sure that the 3D Voronoi diagram is quite what one would instinctively think it is. http://en.wikipedia.org/wiki/Voronoi_diagram says: In general a cross section of a 3D Voronoi tessellation is not a 2D Voronoi tessellation itself. Need to look into that. I don't have much practical experience with Bayes models, so can't really comment on that. Cheers, Ben Christian Kaiser wrote: It seems to me that this is a 3D interpolation problem with categorical variables. Maybe the Bayesian Maximum Entropy approach could help. There are some interesting publications around also for geology and soil sciences, and they can deal with categorical data as well. Look for example here: http://www.enge.ucl.ac.be/staff/curr/Bogaert/biblioBME/BMEbibsubject.htm l#Soil%20Science Or maybe you can have a look at SGeMS (http://sgems.sourceforge.net), a tool for 3D geostatistics. None of them is available through GRASS, but the algorithms are freely available (I think open-source, but not verified). I am not a geologist, so please forgive if it is not adequate... Christian Kaiser On 8 janv. 2010, at 11:04, Benjamin Ducke wrote: Rich Shepard wrote: material. There is no interpolation algorithm in GRASS currently which can handle that sort of data well. So what is needed is a political algorithm. :-) That's actually right: given the presence of n different layer types in the vicinity of an empty voxel
Re: [GRASS-user] Searching Docs about 3D geological modelisation
Why not just ask Steve what he is concerned about and what he would like us to do so that he can shed his concerns? And then try to find a way to accommodate him? If he got more directly involved into this process, it might make him feel less uneasy about it. Ben - Original Message - From: Dylan Beaudette debeaude...@ucdavis.edu To: grass-user@lists.osgeo.org Cc: Benjamin Ducke benjamin.du...@oxfordarch.co.uk, Graham Fogg ge...@mac.com Sent: Friday, January 22, 2010 9:38:18 PM GMT +01:00 Amsterdam / Berlin / Bern / Rome / Stockholm / Vienna Subject: Re: [GRASS-user] Searching Docs about 3D geological modelisation On Saturday 09 January 2010, Benjamin Ducke wrote: Cheers for these. They are certainly all highly interesting. Do you have an actual link for the T-PROGS software itself? All I can seem to come up with are interfaces from other software and publications mentioning it. I would certainly be interested in taking a look at your GRASS interface. Is T-PROGS open source? My gut feeling is that the T-PROGS approach would give better results than 3D kriging, as it seems better able to to follow 3D shape trends: http://chl.erdc.usace.army.mil/chl.aspx?p=sa=ARTICLES;37g=50 ... but that certainly would need testing. Having said that, I also like this approach for a more heuristic model: http://chl.erdc.usace.army.mil/chl.aspx?p=sa=ARTICLES;41g=50 It's very simple and could easily be implemented directly in GRASS GIS. In fact, I coded something very similar to this for archaeological stratigraphy reconstruction a while back. Cheers, Ben Hi Ben and others, Here are some concerns from the author of the TPROGS software: - Steve is hesitant because he's not sure what the finished product would be. I think he's probably concerned about misapplication or perhaps some kind of ripoff. Can you provide a bit more background on where you see this going? - I think that it would be helpful to put together a small proposal, regarding how the TPROGS source code / ideas would be integrated into GRASS. It seems like the author is worried about use without citation, and once he understands what GRASS developers have in mind, should be for it. To start the discussion, I propose that the methods used within the TPROGS software be integrated (with proper citations) into a GRASS library, so that a series of modules can perform the multi-step process associated with modeling transition probabilities. Furthermore, the GRASS rast3 (voxel) datatype should be used to store the resulting structures-- this will make visualization with NVIZ / Paraview a snap. Alternatively, we may be able to link GRASS with TPROGS with a little bit of python glue. While this may work if there are limitations regarding the use of the TPROGS source, I think that having these algorithms present in the GRASS libraries would be a real benefit. I have CC-ed Graham, so that we can keep him in the conversation. Cheers, Dylan - Original Message - From: Dylan Beaudette dylan.beaude...@gmail.com To: Benjamin Ducke benjamin.du...@oxfordarch.co.uk Cc: GRASS user list grass-user@lists.osgeo.org Sent: Saturday, January 9, 2010 4:30:40 AM GMT +01:00 Amsterdam / Berlin / Bern / Rome / Stockholm / Vienna Subject: Re: [GRASS-user] Searching Docs about 3D geological modelisation Two more ideas: 1. conditional simulation, based on a 3D variogram model 2. transition probability-based interpolation of categories Check out gstat for the conditional simulation, and TPROGS for the transition probability. If anything is interested, I have done some programming to connect GRASS and TPROGS. Cheers! Dylan On Fri, Jan 8, 2010 at 1:24 PM, Benjamin Ducke benjamin.du...@oxfordarch.co.uk wrote: Woohoo, this forum is always a treasure trove of good advice. I had not idea SGemS existed! The Voronoi idea is also good, I am just not sure that the 3D Voronoi diagram is quite what one would instinctively think it is. http://en.wikipedia.org/wiki/Voronoi_diagram says: In general a cross section of a 3D Voronoi tessellation is not a 2D Voronoi tessellation itself. Need to look into that. I don't have much practical experience with Bayes models, so can't really comment on that. Cheers, Ben Christian Kaiser wrote: It seems to me that this is a 3D interpolation problem with categorical variables. Maybe the Bayesian Maximum Entropy approach could help. There are some interesting publications around also for geology and soil sciences, and they can deal with categorical data as well. Look for example here: http://www.enge.ucl.ac.be/staff/curr/Bogaert/biblioBME/BMEbibsubject.htm l#Soil%20Science Or maybe you can have a look at SGeMS (http
Re: [GRASS-user] Searching Docs about 3D geological modelisation
Quick update: I recently heard back from Graham Fogg here on campus, and he is in favor of allowing T-PROGS to be used within GRASS. However, he is still waiting for the final go-ahead from the original author. Dylan On Monday 11 January 2010, Thomas Adams wrote: Dylan, Can you tell me how to obtain TPROGS? Is it only available commercially? Thanks, Tom Dylan Beaudette wrote: Two more ideas: 1. conditional simulation, based on a 3D variogram model 2. transition probability-based interpolation of categories Check out gstat for the conditional simulation, and TPROGS for the transition probability. If anything is interested, I have done some programming to connect GRASS and TPROGS. Cheers! Dylan On Fri, Jan 8, 2010 at 1:24 PM, Benjamin Ducke benjamin.du...@oxfordarch.co.uk wrote: Woohoo, this forum is always a treasure trove of good advice. I had not idea SGemS existed! The Voronoi idea is also good, I am just not sure that the 3D Voronoi diagram is quite what one would instinctively think it is. http://en.wikipedia.org/wiki/Voronoi_diagram says: In general a cross section of a 3D Voronoi tessellation is not a 2D Voronoi tessellation itself. Need to look into that. I don't have much practical experience with Bayes models, so can't really comment on that. Cheers, Ben Christian Kaiser wrote: It seems to me that this is a 3D interpolation problem with categorical variables. Maybe the Bayesian Maximum Entropy approach could help. There are some interesting publications around also for geology and soil sciences, and they can deal with categorical data as well. Look for example here: http://www.enge.ucl.ac.be/staff/curr/Bogaert/biblioBME/BMEbibsubject.ht ml#Soil%20Science Or maybe you can have a look at SGeMS (http://sgems.sourceforge.net), a tool for 3D geostatistics. None of them is available through GRASS, but the algorithms are freely available (I think open-source, but not verified). I am not a geologist, so please forgive if it is not adequate... Christian Kaiser On 8 janv. 2010, at 11:04, Benjamin Ducke wrote: Rich Shepard wrote: material. There is no interpolation algorithm in GRASS currently which can handle that sort of data well. So what is needed is a political algorithm. :-) That's actually right: given the presence of n different layer types in the vicinity of an empty voxel, the algorithm would need to decide by some sort of majority vote which type to assign to that voxel. Kidding aside, I suspect that a fuzzy interpolation algorithm would solve the problem. How? You could make the interpolated value depend on a fuzzy set member function, I suppose, but the situation here is actually so well defined that I think a probabilistic approach would be preferable. Since each voxel can only store one value, a second output map could store the classification probability. That may be very useful for visualization (you could show voxels with little probability hazier). Ben Rich ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user -- Benjamin Ducke Geospatial Consultant Oxford Archaeology Digital Janus House Osney Mead OX2 0ES Oxford, U.K. Tel: +44 (0)1865 263 800 (switchboard) Tel: +44 (0)1865 980 758 (direct) Fax :+44 (0)1865 793 496 benjamin.du...@oadigital.net http://oadigital.net -- Files attached to this email may be in ISO 26300 format (OASIS Open Document Format). If you have difficulty opening them, please visit http://iso26300.info for more information. ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user -- Benjamin Ducke Geospatial Consultant Oxford Archaeology Digital Janus House Osney Mead OX2 0ES Oxford, U.K. Tel: +44 (0)1865 263 800 (switchboard) Tel: +44 (0)1865 980 758 (direct) Fax :+44 (0)1865 793 496 benjamin.du...@oadigital.net http://oadigital.net -- Files attached to this email may be in ISO 26300 format (OASIS Open Document Format). If you have difficulty opening them, please visit http://iso26300.info for more information. ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user -- Dylan Beaudette Soil Resource Laboratory http://casoilresource.lawr.ucdavis.edu/ University
Re: [GRASS-user] Searching Docs about 3D geological modelisation
Hey, good news. Please keep us updated! Ben - Original Message - From: Dylan Beaudette debeaude...@ucdavis.edu To: Thomas Adams thomas.ad...@noaa.gov Cc: grass list grass-user@lists.osgeo.org Sent: Wednesday, January 20, 2010 8:10:45 PM GMT +01:00 Amsterdam / Berlin / Bern / Rome / Stockholm / Vienna Subject: Re: [GRASS-user] Searching Docs about 3D geological modelisation Quick update: I recently heard back from Graham Fogg here on campus, and he is in favor of allowing T-PROGS to be used within GRASS. However, he is still waiting for the final go-ahead from the original author. Dylan On Monday 11 January 2010, Thomas Adams wrote: Dylan, Can you tell me how to obtain TPROGS? Is it only available commercially? Thanks, Tom Dylan Beaudette wrote: Two more ideas: 1. conditional simulation, based on a 3D variogram model 2. transition probability-based interpolation of categories Check out gstat for the conditional simulation, and TPROGS for the transition probability. If anything is interested, I have done some programming to connect GRASS and TPROGS. Cheers! Dylan On Fri, Jan 8, 2010 at 1:24 PM, Benjamin Ducke benjamin.du...@oxfordarch.co.uk wrote: Woohoo, this forum is always a treasure trove of good advice. I had not idea SGemS existed! The Voronoi idea is also good, I am just not sure that the 3D Voronoi diagram is quite what one would instinctively think it is. http://en.wikipedia.org/wiki/Voronoi_diagram says: In general a cross section of a 3D Voronoi tessellation is not a 2D Voronoi tessellation itself. Need to look into that. I don't have much practical experience with Bayes models, so can't really comment on that. Cheers, Ben Christian Kaiser wrote: It seems to me that this is a 3D interpolation problem with categorical variables. Maybe the Bayesian Maximum Entropy approach could help. There are some interesting publications around also for geology and soil sciences, and they can deal with categorical data as well. Look for example here: http://www.enge.ucl.ac.be/staff/curr/Bogaert/biblioBME/BMEbibsubject.ht ml#Soil%20Science Or maybe you can have a look at SGeMS (http://sgems.sourceforge.net), a tool for 3D geostatistics. None of them is available through GRASS, but the algorithms are freely available (I think open-source, but not verified). I am not a geologist, so please forgive if it is not adequate... Christian Kaiser On 8 janv. 2010, at 11:04, Benjamin Ducke wrote: Rich Shepard wrote: material. There is no interpolation algorithm in GRASS currently which can handle that sort of data well. So what is needed is a political algorithm. :-) That's actually right: given the presence of n different layer types in the vicinity of an empty voxel, the algorithm would need to decide by some sort of majority vote which type to assign to that voxel. Kidding aside, I suspect that a fuzzy interpolation algorithm would solve the problem. How? You could make the interpolated value depend on a fuzzy set member function, I suppose, but the situation here is actually so well defined that I think a probabilistic approach would be preferable. Since each voxel can only store one value, a second output map could store the classification probability. That may be very useful for visualization (you could show voxels with little probability hazier). Ben Rich ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user -- Benjamin Ducke Geospatial Consultant Oxford Archaeology Digital Janus House Osney Mead OX2 0ES Oxford, U.K. Tel: +44 (0)1865 263 800 (switchboard) Tel: +44 (0)1865 980 758 (direct) Fax :+44 (0)1865 793 496 benjamin.du...@oadigital.net http://oadigital.net -- Files attached to this email may be in ISO 26300 format (OASIS Open Document Format). If you have difficulty opening them, please visit http://iso26300.info for more information. ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user -- Benjamin Ducke Geospatial Consultant Oxford Archaeology Digital Janus House Osney Mead OX2 0ES Oxford, U.K. Tel: +44 (0)1865 263 800 (switchboard) Tel: +44 (0)1865 980 758 (direct) Fax :+44 (0)1865 793 496 benjamin.du...@oadigital.net http://oadigital.net -- Files attached to this email may be in ISO 26300 format (OASIS Open Document Format). If you have difficulty opening them, please visit http://iso26300.info for more information
Re: [GRASS-user] Searching Docs about 3D geological modelisation
Hi Thomas, I am pretty sure that the program (maybe not the source code) are in the public domain. I'll contact the author, and post back. Cheers, Dylan On Mon, Jan 11, 2010 at 6:56 AM, Thomas Adams thomas.ad...@noaa.gov wrote: Dylan, Can you tell me how to obtain TPROGS? Is it only available commercially? Thanks, Tom Dylan Beaudette wrote: Two more ideas: 1. conditional simulation, based on a 3D variogram model 2. transition probability-based interpolation of categories Check out gstat for the conditional simulation, and TPROGS for the transition probability. If anything is interested, I have done some programming to connect GRASS and TPROGS. Cheers! Dylan On Fri, Jan 8, 2010 at 1:24 PM, Benjamin Ducke benjamin.du...@oxfordarch.co.uk wrote: Woohoo, this forum is always a treasure trove of good advice. I had not idea SGemS existed! The Voronoi idea is also good, I am just not sure that the 3D Voronoi diagram is quite what one would instinctively think it is. http://en.wikipedia.org/wiki/Voronoi_diagram says: In general a cross section of a 3D Voronoi tessellation is not a 2D Voronoi tessellation itself. Need to look into that. I don't have much practical experience with Bayes models, so can't really comment on that. Cheers, Ben Christian Kaiser wrote: It seems to me that this is a 3D interpolation problem with categorical variables. Maybe the Bayesian Maximum Entropy approach could help. There are some interesting publications around also for geology and soil sciences, and they can deal with categorical data as well. Look for example here: http://www.enge.ucl.ac.be/staff/curr/Bogaert/biblioBME/BMEbibsubject.html#Soil%20Science Or maybe you can have a look at SGeMS (http://sgems.sourceforge.net), a tool for 3D geostatistics. None of them is available through GRASS, but the algorithms are freely available (I think open-source, but not verified). I am not a geologist, so please forgive if it is not adequate... Christian Kaiser On 8 janv. 2010, at 11:04, Benjamin Ducke wrote: Rich Shepard wrote: material. There is no interpolation algorithm in GRASS currently which can handle that sort of data well. So what is needed is a political algorithm. :-) That's actually right: given the presence of n different layer types in the vicinity of an empty voxel, the algorithm would need to decide by some sort of majority vote which type to assign to that voxel. Kidding aside, I suspect that a fuzzy interpolation algorithm would solve the problem. How? You could make the interpolated value depend on a fuzzy set member function, I suppose, but the situation here is actually so well defined that I think a probabilistic approach would be preferable. Since each voxel can only store one value, a second output map could store the classification probability. That may be very useful for visualization (you could show voxels with little probability hazier). Ben Rich ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user -- Benjamin Ducke Geospatial Consultant Oxford Archaeology Digital Janus House Osney Mead OX2 0ES Oxford, U.K. Tel: +44 (0)1865 263 800 (switchboard) Tel: +44 (0)1865 980 758 (direct) Fax :+44 (0)1865 793 496 benjamin.du...@oadigital.net http://oadigital.net -- Files attached to this email may be in ISO 26300 format (OASIS Open Document Format). If you have difficulty opening them, please visit http://iso26300.info for more information. ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user -- Benjamin Ducke Geospatial Consultant Oxford Archaeology Digital Janus House Osney Mead OX2 0ES Oxford, U.K. Tel: +44 (0)1865 263 800 (switchboard) Tel: +44 (0)1865 980 758 (direct) Fax :+44 (0)1865 793 496 benjamin.du...@oadigital.net http://oadigital.net -- Files attached to this email may be in ISO 26300 format (OASIS Open Document Format). If you have difficulty opening them, please visit http://iso26300.info for more information. ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user -- Thomas E Adams National Weather Service Ohio River Forecast Center 1901 South State Route 134 Wilmington, OH 45177 EMAIL: thomas.ad...@noaa.gov VOICE: 937-383-0528 FAX: 937-383-0033 ___
Re: [GRASS-user] Searching Docs about 3D geological modelisation
Cheers for these. They are certainly all highly interesting. Do you have an actual link for the T-PROGS software itself? All I can seem to come up with are interfaces from other software and publications mentioning it. I would certainly be interested in taking a look at your GRASS interface. Is T-PROGS open source? My gut feeling is that the T-PROGS approach would give better results than 3D kriging, as it seems better able to to follow 3D shape trends: http://chl.erdc.usace.army.mil/chl.aspx?p=sa=ARTICLES;37g=50 ... but that certainly would need testing. Having said that, I also like this approach for a more heuristic model: http://chl.erdc.usace.army.mil/chl.aspx?p=sa=ARTICLES;41g=50 It's very simple and could easily be implemented directly in GRASS GIS. In fact, I coded something very similar to this for archaeological stratigraphy reconstruction a while back. Cheers, Ben - Original Message - From: Dylan Beaudette dylan.beaude...@gmail.com To: Benjamin Ducke benjamin.du...@oxfordarch.co.uk Cc: GRASS user list grass-user@lists.osgeo.org Sent: Saturday, January 9, 2010 4:30:40 AM GMT +01:00 Amsterdam / Berlin / Bern / Rome / Stockholm / Vienna Subject: Re: [GRASS-user] Searching Docs about 3D geological modelisation Two more ideas: 1. conditional simulation, based on a 3D variogram model 2. transition probability-based interpolation of categories Check out gstat for the conditional simulation, and TPROGS for the transition probability. If anything is interested, I have done some programming to connect GRASS and TPROGS. Cheers! Dylan On Fri, Jan 8, 2010 at 1:24 PM, Benjamin Ducke benjamin.du...@oxfordarch.co.uk wrote: Woohoo, this forum is always a treasure trove of good advice. I had not idea SGemS existed! The Voronoi idea is also good, I am just not sure that the 3D Voronoi diagram is quite what one would instinctively think it is. http://en.wikipedia.org/wiki/Voronoi_diagram says: In general a cross section of a 3D Voronoi tessellation is not a 2D Voronoi tessellation itself. Need to look into that. I don't have much practical experience with Bayes models, so can't really comment on that. Cheers, Ben Christian Kaiser wrote: It seems to me that this is a 3D interpolation problem with categorical variables. Maybe the Bayesian Maximum Entropy approach could help. There are some interesting publications around also for geology and soil sciences, and they can deal with categorical data as well. Look for example here: http://www.enge.ucl.ac.be/staff/curr/Bogaert/biblioBME/BMEbibsubject.html#Soil%20Science Or maybe you can have a look at SGeMS (http://sgems.sourceforge.net), a tool for 3D geostatistics. None of them is available through GRASS, but the algorithms are freely available (I think open-source, but not verified). I am not a geologist, so please forgive if it is not adequate... Christian Kaiser On 8 janv. 2010, at 11:04, Benjamin Ducke wrote: Rich Shepard wrote: material. There is no interpolation algorithm in GRASS currently which can handle that sort of data well. So what is needed is a political algorithm. :-) That's actually right: given the presence of n different layer types in the vicinity of an empty voxel, the algorithm would need to decide by some sort of majority vote which type to assign to that voxel. Kidding aside, I suspect that a fuzzy interpolation algorithm would solve the problem. How? You could make the interpolated value depend on a fuzzy set member function, I suppose, but the situation here is actually so well defined that I think a probabilistic approach would be preferable. Since each voxel can only store one value, a second output map could store the classification probability. That may be very useful for visualization (you could show voxels with little probability hazier). Ben Rich ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user -- Benjamin Ducke Geospatial Consultant Oxford Archaeology Digital Janus House Osney Mead OX2 0ES Oxford, U.K. Tel: +44 (0)1865 263 800 (switchboard) Tel: +44 (0)1865 980 758 (direct) Fax :+44 (0)1865 793 496 benjamin.du...@oadigital.net http://oadigital.net -- Files attached to this email may be in ISO 26300 format (OASIS Open Document Format). If you have difficulty opening them, please visit http://iso26300.info for more information. ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user -- Benjamin Ducke Geospatial Consultant Oxford Archaeology Digital Janus House Osney Mead OX2 0ES Oxford, U.K. Tel: +44 (0)1865 263 800 (switchboard) Tel
Re: [GRASS-user] Searching Docs about 3D geological modelisation
it seems to me that the TPROGS word only refers tp a method and not a software, here is slide I found about if by Gary Weissmann (from google's cache as the pdf's link is dead) : http://209.85.229.132/search?q=cache:5JU5t4eQ4HYJ:www.isgs.illinois.edu/research/3DWorkshop/2005/pdf-files/Weissmann-GSA-2005_ppt.pdf+TPROGScd=24hl=frct=clnkgl=frclient=firefox-a From forum's post he seems to have a software package available for transition probability geostatistics which he then import into GSM (the software linked in the previous mails) Le 09/01/2010 11:51, Benjamin Ducke a écrit : Cheers for these. They are certainly all highly interesting. Do you have an actual link for the T-PROGS software itself? All I can seem to come up with are interfaces from other software and publications mentioning it. I would certainly be interested in taking a look at your GRASS interface. Is T-PROGS open source? My gut feeling is that the T-PROGS approach would give better results than 3D kriging, as it seems better able to to follow 3D shape trends: http://chl.erdc.usace.army.mil/chl.aspx?p=sa=ARTICLES;37g=50 ... but that certainly would need testing. Having said that, I also like this approach for a more heuristic model: http://chl.erdc.usace.army.mil/chl.aspx?p=sa=ARTICLES;41g=50 It's very simple and could easily be implemented directly in GRASS GIS. In fact, I coded something very similar to this for archaeological stratigraphy reconstruction a while back. Cheers, Ben - Original Message - From: Dylan Beaudettedylan.beaude...@gmail.com To: Benjamin Duckebenjamin.du...@oxfordarch.co.uk Cc: GRASS user listgrass-user@lists.osgeo.org Sent: Saturday, January 9, 2010 4:30:40 AM GMT +01:00 Amsterdam / Berlin / Bern / Rome / Stockholm / Vienna Subject: Re: [GRASS-user] Searching Docs about 3D geological modelisation Two more ideas: 1. conditional simulation, based on a 3D variogram model 2. transition probability-based interpolation of categories Check out gstat for the conditional simulation, and TPROGS for the transition probability. If anything is interested, I have done some programming to connect GRASS and TPROGS. Cheers! Dylan On Fri, Jan 8, 2010 at 1:24 PM, Benjamin Ducke benjamin.du...@oxfordarch.co.uk wrote: Woohoo, this forum is always a treasure trove of good advice. I had not idea SGemS existed! The Voronoi idea is also good, I am just not sure that the 3D Voronoi diagram is quite what one would instinctively think it is. http://en.wikipedia.org/wiki/Voronoi_diagram says: In general a cross section of a 3D Voronoi tessellation is not a 2D Voronoi tessellation itself. Need to look into that. I don't have much practical experience with Bayes models, so can't really comment on that. Cheers, Ben Christian Kaiser wrote: It seems to me that this is a 3D interpolation problem with categorical variables. Maybe the Bayesian Maximum Entropy approach could help. There are some interesting publications around also for geology and soil sciences, and they can deal with categorical data as well. Look for example here: http://www.enge.ucl.ac.be/staff/curr/Bogaert/biblioBME/BMEbibsubject.html#Soil%20Science Or maybe you can have a look at SGeMS (http://sgems.sourceforge.net), a tool for 3D geostatistics. None of them is available through GRASS, but the algorithms are freely available (I think open-source, but not verified). I am not a geologist, so please forgive if it is not adequate... Christian Kaiser On 8 janv. 2010, at 11:04, Benjamin Ducke wrote: Rich Shepard wrote: material. There is no interpolation algorithm in GRASS currently which can handle that sort of data well. So what is needed is a political algorithm. :-) That's actually right: given the presence of n different layer types in the vicinity of an empty voxel, the algorithm would need to decide by some sort of majority vote which type to assign to that voxel. Kidding aside, I suspect that a fuzzy interpolation algorithm would solve the problem. How? You could make the interpolated value depend on a fuzzy set member function, I suppose, but the situation here is actually so well defined that I think a probabilistic approach would be preferable. Since each voxel can only store one value, a second output map could store the classification probability. That may be very useful for visualization (you could show voxels with little probability hazier). Ben Rich ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user -- Benjamin Ducke Geospatial Consultant Oxford Archaeology Digital Janus House Osney Mead OX2 0ES Oxford, U.K. Tel: +44 (0)1865 263 800 (switchboard) Tel: +44 (0)1865 980 758 (direct) Fax :+44 (0)1865 793 496 benjamin.du...@oadigital.net http://oadigital.net -- Files attached to this email may be in ISO 26300 format (OASIS Open Document Format). If you have difficulty opening them
Re: [GRASS-user] Searching Docs about 3D geological modelisation
On Sat, Jan 9, 2010 at 2:51 AM, Benjamin Ducke benjamin.du...@oxfordarch.co.uk wrote: Cheers for these. They are certainly all highly interesting. Do you have an actual link for the T-PROGS software itself? All I can seem to come up with are interfaces from other software and publications mentioning it. I would certainly be interested in taking a look at your GRASS interface. Is T-PROGS open source? My gut feeling is that the T-PROGS approach would give better results than 3D kriging, as it seems better able to to follow 3D shape trends: http://chl.erdc.usace.army.mil/chl.aspx?p=sa=ARTICLES;37g=50 ... but that certainly would need testing. Having said that, I also like this approach for a more heuristic model: http://chl.erdc.usace.army.mil/chl.aspx?p=sa=ARTICLES;41g=50 It's very simple and could easily be implemented directly in GRASS GIS. In fact, I coded something very similar to this for archaeological stratigraphy reconstruction a while back. Cheers, Ben Hi Ben, Yes. It would be very interesting to have these functions within GRASS libraries, as opposed to the kludgy interfacing that I did via shell scripting + awk. Here are some of the details, from *several* years ago (GRASS 5.x): http://169.237.35.250/~dylan/grass_and_tp/ ... note that this is rather old work, and somethings may have changed since then. Here is the reference for the software: Carle, Steven F. T-PROGS Transition Probability Geostatistical Software Version 2.1 manual. University of California, Davis. 1999. I can get in touch with Graham Fogg here at UC Davis, whom I believe is in charge of maintaining the current implementation of T-PROGS-- basically fortran source + a tcl/tk interface. Having this functionality in GRASS would greatly add to the capabilities of the voxel framework. Also, by 'conditional simulation' I wasn't referring to kriging per se, rather the conditional simulation of an indicator (categorical) variable, based on random fields + variogram model. the gstat library can perform both unconditional simulation (randomness only tied to a variogram model), and conditional simulation (randomness tied to real point data + variogram model). I'll report back here with my findings. Cheers, Dylan - Original Message - From: Dylan Beaudette dylan.beaude...@gmail.com To: Benjamin Ducke benjamin.du...@oxfordarch.co.uk Cc: GRASS user list grass-user@lists.osgeo.org Sent: Saturday, January 9, 2010 4:30:40 AM GMT +01:00 Amsterdam / Berlin / Bern / Rome / Stockholm / Vienna Subject: Re: [GRASS-user] Searching Docs about 3D geological modelisation Two more ideas: 1. conditional simulation, based on a 3D variogram model 2. transition probability-based interpolation of categories Check out gstat for the conditional simulation, and TPROGS for the transition probability. If anything is interested, I have done some programming to connect GRASS and TPROGS. Cheers! Dylan On Fri, Jan 8, 2010 at 1:24 PM, Benjamin Ducke benjamin.du...@oxfordarch.co.uk wrote: Woohoo, this forum is always a treasure trove of good advice. I had not idea SGemS existed! The Voronoi idea is also good, I am just not sure that the 3D Voronoi diagram is quite what one would instinctively think it is. http://en.wikipedia.org/wiki/Voronoi_diagram says: In general a cross section of a 3D Voronoi tessellation is not a 2D Voronoi tessellation itself. Need to look into that. I don't have much practical experience with Bayes models, so can't really comment on that. Cheers, Ben Christian Kaiser wrote: It seems to me that this is a 3D interpolation problem with categorical variables. Maybe the Bayesian Maximum Entropy approach could help. There are some interesting publications around also for geology and soil sciences, and they can deal with categorical data as well. Look for example here: http://www.enge.ucl.ac.be/staff/curr/Bogaert/biblioBME/BMEbibsubject.html#Soil%20Science Or maybe you can have a look at SGeMS (http://sgems.sourceforge.net), a tool for 3D geostatistics. None of them is available through GRASS, but the algorithms are freely available (I think open-source, but not verified). I am not a geologist, so please forgive if it is not adequate... Christian Kaiser On 8 janv. 2010, at 11:04, Benjamin Ducke wrote: Rich Shepard wrote: material. There is no interpolation algorithm in GRASS currently which can handle that sort of data well. So what is needed is a political algorithm. :-) That's actually right: given the presence of n different layer types in the vicinity of an empty voxel, the algorithm would need to decide by some sort of majority vote which type to assign to that voxel. Kidding aside, I suspect that a fuzzy interpolation algorithm would solve the problem. How? You could make the interpolated value depend on a fuzzy set member function, I suppose, but the situation here is actually so well defined that I think
Re: [GRASS-user] Searching Docs about 3D geological modelisation
Rich Shepard wrote: material. There is no interpolation algorithm in GRASS currently which can handle that sort of data well. So what is needed is a political algorithm. :-) That's actually right: given the presence of n different layer types in the vicinity of an empty voxel, the algorithm would need to decide by some sort of majority vote which type to assign to that voxel. Kidding aside, I suspect that a fuzzy interpolation algorithm would solve the problem. How? You could make the interpolated value depend on a fuzzy set member function, I suppose, but the situation here is actually so well defined that I think a probabilistic approach would be preferable. Since each voxel can only store one value, a second output map could store the classification probability. That may be very useful for visualization (you could show voxels with little probability hazier). Ben Rich ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user -- Benjamin Ducke Geospatial Consultant Oxford Archaeology Digital Janus House Osney Mead OX2 0ES Oxford, U.K. Tel: +44 (0)1865 263 800 (switchboard) Tel: +44 (0)1865 980 758 (direct) Fax :+44 (0)1865 793 496 benjamin.du...@oadigital.net http://oadigital.net -- Files attached to this email may be in ISO 26300 format (OASIS Open Document Format). If you have difficulty opening them, please visit http://iso26300.info for more information. ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user
Re: [GRASS-user] Searching Docs about 3D geological modelisation
On Fri, 8 Jan 2010, Benjamin Ducke wrote: That's actually right: given the presence of n different layer types in the vicinity of an empty voxel, the algorithm would need to decide by some sort of majority vote which type to assign to that voxel. Ben, I'm not a geologist so I don't know how best to extrapolate from well logs. I've used water well logs to determine the presence of impervious layers and aquifer surfaces, but not tried to imcorporate those data into a GRASS analysis. But your comment above makes me wonder if calculating Veronoi diagram of these various layers would provide that majority vote. Rich ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user
Re: [GRASS-user] Searching Docs about 3D geological modelisation
It seems to me that this is a 3D interpolation problem with categorical variables. Maybe the Bayesian Maximum Entropy approach could help. There are some interesting publications around also for geology and soil sciences, and they can deal with categorical data as well. Look for example here: http://www.enge.ucl.ac.be/staff/curr/Bogaert/biblioBME/BMEbibsubject.html#Soil%20Science Or maybe you can have a look at SGeMS (http://sgems.sourceforge.net), a tool for 3D geostatistics. None of them is available through GRASS, but the algorithms are freely available (I think open-source, but not verified). I am not a geologist, so please forgive if it is not adequate... Christian Kaiser On 8 janv. 2010, at 11:04, Benjamin Ducke wrote: Rich Shepard wrote: material. There is no interpolation algorithm in GRASS currently which can handle that sort of data well. So what is needed is a political algorithm. :-) That's actually right: given the presence of n different layer types in the vicinity of an empty voxel, the algorithm would need to decide by some sort of majority vote which type to assign to that voxel. Kidding aside, I suspect that a fuzzy interpolation algorithm would solve the problem. How? You could make the interpolated value depend on a fuzzy set member function, I suppose, but the situation here is actually so well defined that I think a probabilistic approach would be preferable. Since each voxel can only store one value, a second output map could store the classification probability. That may be very useful for visualization (you could show voxels with little probability hazier). Ben Rich ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user -- Benjamin Ducke Geospatial Consultant Oxford Archaeology Digital Janus House Osney Mead OX2 0ES Oxford, U.K. Tel: +44 (0)1865 263 800 (switchboard) Tel: +44 (0)1865 980 758 (direct) Fax :+44 (0)1865 793 496 benjamin.du...@oadigital.net http://oadigital.net -- Files attached to this email may be in ISO 26300 format (OASIS Open Document Format). If you have difficulty opening them, please visit http://iso26300.info for more information. ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user
Re: [GRASS-user] Searching Docs about 3D geological modelisation
Thanks for the answers, Having used it a little with archaeological structures it was no wonder that the first software I thought about was grass, but the main difference is, as you pointed out, that in this case I do not have a well defined volume. I was thinking about using r3.in.ascii and then r.to.rast3 but it doesn't seems to be the right thing to do on a large scale (150km²) due to potential multiple top/bottom crossing of the generated layers. Your screenshots are exactly the kind of data visualization I'm seeking to obtain. Jean Roc Le 08/01/2010 00:34, Benjamin Ducke a écrit : Well, you are in luck and trouble at the same time. Out of all GIS I know, GRASS is the only one that's competent at handling 3D, volumetric rasters (aka voxels, which is really what you want for stratigraphic models). On the other hand, efficient voxel modelling from sparse 3D data, such as well logs and transects remains really challenging. The problem with well logs is also that often the data is of a qualitative nature, indicating the presence and absence of types of material. There is no interpolation algorithm in GRASS currently which can handle that sort of data well. I have attached two screenshots of models that I once produced from log data. One has been interpolated with GRASS' 3D splines algorithm (which was a bit cheating, really), the other is some sort of 3D IDW interpolation done directly in VisIt. I don't think they turned out too great. But, hey: it's still more realistic than drawing on a piece of paper and playing the old connect the logs with lines game... You missed the use of Illustrator Ben MORREALE Jean Roc wrote: Hello Grasslist, I'm searching for papers, books or usecases covering the use of GRASS in geology, mainly on the stratigraphic representations (well log, schematic block diagram) and geomorphological (erosion, georelief reconstruction) aspects. This is an area I've not practiced so far so I would be interested to know how people here deal with it in Grass (especially their rules for building a 3d model from logs and exploiting it correctly but also any kind of spicy stuff you can obtain from it). Thre is some related papers I've already find on these subjects : HydroGIS 96: Application of Geographic Information Systems in Hydrology and Water Resources Management (Proceedings of the Vienna Conference, April 1996). IAHS Publ. no. 235, 1996. Spatial Geologic Hazard Analysis in Practice, J. David Rogers, 2004 Three-dimensional Geological Modeling by FOSS GRASS GIS, Atsushi Kajiyama et al., 2004 Volume modeling of soils using GRASS GIS 3D-Tools, Markus Neteler, 2001 Regards, MORREALE Jean Roc ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user
Re: [GRASS-user] Searching Docs about 3D geological modelisation
Woohoo, this forum is always a treasure trove of good advice. I had not idea SGemS existed! The Voronoi idea is also good, I am just not sure that the 3D Voronoi diagram is quite what one would instinctively think it is. http://en.wikipedia.org/wiki/Voronoi_diagram says: In general a cross section of a 3D Voronoi tessellation is not a 2D Voronoi tessellation itself. Need to look into that. I don't have much practical experience with Bayes models, so can't really comment on that. Cheers, Ben Christian Kaiser wrote: It seems to me that this is a 3D interpolation problem with categorical variables. Maybe the Bayesian Maximum Entropy approach could help. There are some interesting publications around also for geology and soil sciences, and they can deal with categorical data as well. Look for example here: http://www.enge.ucl.ac.be/staff/curr/Bogaert/biblioBME/BMEbibsubject.html#Soil%20Science Or maybe you can have a look at SGeMS (http://sgems.sourceforge.net), a tool for 3D geostatistics. None of them is available through GRASS, but the algorithms are freely available (I think open-source, but not verified). I am not a geologist, so please forgive if it is not adequate... Christian Kaiser On 8 janv. 2010, at 11:04, Benjamin Ducke wrote: Rich Shepard wrote: material. There is no interpolation algorithm in GRASS currently which can handle that sort of data well. So what is needed is a political algorithm. :-) That's actually right: given the presence of n different layer types in the vicinity of an empty voxel, the algorithm would need to decide by some sort of majority vote which type to assign to that voxel. Kidding aside, I suspect that a fuzzy interpolation algorithm would solve the problem. How? You could make the interpolated value depend on a fuzzy set member function, I suppose, but the situation here is actually so well defined that I think a probabilistic approach would be preferable. Since each voxel can only store one value, a second output map could store the classification probability. That may be very useful for visualization (you could show voxels with little probability hazier). Ben Rich ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user -- Benjamin Ducke Geospatial Consultant Oxford Archaeology Digital Janus House Osney Mead OX2 0ES Oxford, U.K. Tel: +44 (0)1865 263 800 (switchboard) Tel: +44 (0)1865 980 758 (direct) Fax :+44 (0)1865 793 496 benjamin.du...@oadigital.net http://oadigital.net -- Files attached to this email may be in ISO 26300 format (OASIS Open Document Format). If you have difficulty opening them, please visit http://iso26300.info for more information. ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user -- Benjamin Ducke Geospatial Consultant Oxford Archaeology Digital Janus House Osney Mead OX2 0ES Oxford, U.K. Tel: +44 (0)1865 263 800 (switchboard) Tel: +44 (0)1865 980 758 (direct) Fax :+44 (0)1865 793 496 benjamin.du...@oadigital.net http://oadigital.net -- Files attached to this email may be in ISO 26300 format (OASIS Open Document Format). If you have difficulty opening them, please visit http://iso26300.info for more information. ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user
Re: [GRASS-user] Searching Docs about 3D geological modelisation
Two more ideas: 1. conditional simulation, based on a 3D variogram model 2. transition probability-based interpolation of categories Check out gstat for the conditional simulation, and TPROGS for the transition probability. If anything is interested, I have done some programming to connect GRASS and TPROGS. Cheers! Dylan On Fri, Jan 8, 2010 at 1:24 PM, Benjamin Ducke benjamin.du...@oxfordarch.co.uk wrote: Woohoo, this forum is always a treasure trove of good advice. I had not idea SGemS existed! The Voronoi idea is also good, I am just not sure that the 3D Voronoi diagram is quite what one would instinctively think it is. http://en.wikipedia.org/wiki/Voronoi_diagram says: In general a cross section of a 3D Voronoi tessellation is not a 2D Voronoi tessellation itself. Need to look into that. I don't have much practical experience with Bayes models, so can't really comment on that. Cheers, Ben Christian Kaiser wrote: It seems to me that this is a 3D interpolation problem with categorical variables. Maybe the Bayesian Maximum Entropy approach could help. There are some interesting publications around also for geology and soil sciences, and they can deal with categorical data as well. Look for example here: http://www.enge.ucl.ac.be/staff/curr/Bogaert/biblioBME/BMEbibsubject.html#Soil%20Science Or maybe you can have a look at SGeMS (http://sgems.sourceforge.net), a tool for 3D geostatistics. None of them is available through GRASS, but the algorithms are freely available (I think open-source, but not verified). I am not a geologist, so please forgive if it is not adequate... Christian Kaiser On 8 janv. 2010, at 11:04, Benjamin Ducke wrote: Rich Shepard wrote: material. There is no interpolation algorithm in GRASS currently which can handle that sort of data well. So what is needed is a political algorithm. :-) That's actually right: given the presence of n different layer types in the vicinity of an empty voxel, the algorithm would need to decide by some sort of majority vote which type to assign to that voxel. Kidding aside, I suspect that a fuzzy interpolation algorithm would solve the problem. How? You could make the interpolated value depend on a fuzzy set member function, I suppose, but the situation here is actually so well defined that I think a probabilistic approach would be preferable. Since each voxel can only store one value, a second output map could store the classification probability. That may be very useful for visualization (you could show voxels with little probability hazier). Ben Rich ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user -- Benjamin Ducke Geospatial Consultant Oxford Archaeology Digital Janus House Osney Mead OX2 0ES Oxford, U.K. Tel: +44 (0)1865 263 800 (switchboard) Tel: +44 (0)1865 980 758 (direct) Fax :+44 (0)1865 793 496 benjamin.du...@oadigital.net http://oadigital.net -- Files attached to this email may be in ISO 26300 format (OASIS Open Document Format). If you have difficulty opening them, please visit http://iso26300.info for more information. ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user -- Benjamin Ducke Geospatial Consultant Oxford Archaeology Digital Janus House Osney Mead OX2 0ES Oxford, U.K. Tel: +44 (0)1865 263 800 (switchboard) Tel: +44 (0)1865 980 758 (direct) Fax :+44 (0)1865 793 496 benjamin.du...@oadigital.net http://oadigital.net -- Files attached to this email may be in ISO 26300 format (OASIS Open Document Format). If you have difficulty opening them, please visit http://iso26300.info for more information. ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user
[GRASS-user] Searching Docs about 3D geological modelisation
Hello Grasslist, I'm searching for papers, books or usecases covering the use of GRASS in geology, mainly on the stratigraphic representations (well log, schematic block diagram) and geomorphological (erosion, georelief reconstruction) aspects. This is an area I've not practiced so far so I would be interested to know how people here deal with it in Grass (especially their rules for building a 3d model from logs and exploiting it correctly but also any kind of spicy stuff you can obtain from it). Thre is some related papers I've already find on these subjects : HydroGIS 96: Application of Geographic Information Systems in Hydrology and Water Resources Management (Proceedings of the Vienna Conference, April 1996). IAHS Publ. no. 235, 1996. Spatial Geologic Hazard Analysis in Practice, J. David Rogers, 2004 Three-dimensional Geological Modeling by FOSS GRASS GIS, Atsushi Kajiyama et al., 2004 Volume modeling of soils using GRASS GIS 3D-Tools, Markus Neteler, 2001 Regards, MORREALE Jean Roc ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user
Re: [GRASS-user] Searching Docs about 3D geological modelisation
On Thu, 7 Jan 2010, Benjamin Ducke wrote: The problem with well logs is also that often the data is of a qualitative nature, indicating the presence and absence of types of material. There is no interpolation algorithm in GRASS currently which can handle that sort of data well. So what is needed is a political algorithm. :-) Kidding aside, I suspect that a fuzzy interpolation algorithm would solve the problem. Rich ___ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user
