AI-GEOSTATS: Re: Samples in a Block
Hi, Mark, Donald Donald Myers final sentence opened a door for me: "There is no definitive answer to the question since it depends on the question, i.e., what is the data to be used for? In this perspective, I would line to raise several issues. My background and experience is mainly that of a mining geologist who is familiar with geostatistics, and has had the opportunity to work with several geostatisticians. Forgive me for broadening the problem, but such are geology and minng. In my opinion, the final purpose of aampling is estimation leading to mining extraction that achieves optimal metal recovery and minimal dilution. Estimating/ modeling of the variogram and kriging are interim objectives. Geological mapping, interpretation and modeling are also essential steps with whom sampling methods, sampling grid dimensions and geostatistical aspects should be integrated in the determination of global and local continuity (Sinclair and Vallée, 1994). The basic problem of sampling grid size should be viewed in three dimensions. Our usual sampling grids are planned for efficiency, using a stratified drilling pattern perpendicular to the plane of apparent structural / geological continuity. So far, so good! However, once we have achieved a first delineation and can calculate a semivariogram along the drill hole axis, too often we neglect or forget to verify if these continuity parameters apply are present in the other two perpendicular directions. This problem has been detected by Michel David and described in a sampling paper titled "What happens if?" given at a sampling symposium in Australia in 1976 where he describes the problem and recommends sampling specifically designed to verify continuity parameters in the second and third dimensions. Sadly, there is only one sentence in "Geostatistical Ore Reserve Estimation (which was already in print at the time this paper was prepared and presented) that refers to this problem (around page 200). Journel and Huijbregts in "Mining Geostatistics" also describe this problem (1978) and recommend a few simple tools, for instance to lay out a cross of more closely spaced drill holes within the main grid. I consider, based on my mining experience, that sampling of rock in place should be targeted stratified sampling, not random sampling. Regionalized variables require regionalized sampling When the exploration or mining geologist halves the sampling grid dimension, he/she is basically using a similar strategy. I know the results of this effort are viewed by geostatisticians as the "clustering" problem! For the mining geologist, the objective is local estimation and close determination of ore limits, whether they are grade contacts or sharp contacts both for planning and extraction. What is the ideal sampling grid dimension for the mining geologist and the mining engineer? My answer: the one that allows to plan and develop and extract the ore (from stopes or open pit) efficiently as described above. I understand the student/researcher cannot rely on similar amounts of funds for drilling. Another important consideration in the Davil paper and in Geosatistical Ore Estimaion is that of sample preparation and assaying quality control. Quoting from the paper" " ... (frequently) it is the sanple preparation procedure whick generates the nugget effect rather than the real mineralization which generates the nugget effect" [underlined in the text]. This subject makes up almost a chapter of Geostatistical Ore Reserve Estimation. A higher "induced" nugget effect, that is a higher sampling/ assaying variance of the values used for a selectin decision will reduce the accuracy of LOCAL estimation and mine selection. What is the final grid dimension (the one we call measured resource, proven reserve). This will vary depending on orebody configuration and mining method selected. In a open pit, with a fairly sizeable, not too complex and not too nuggetty ore body, you generally can get away with a wider grid for proven ore than yo can in the majority of cases underground, In an open pit you can sample more systematically, from bench to bench than you can in most underground mine. Also one has more flexibility for selection by adjusting blast limits based on test drilling on the pit floor and sampling of blast holes. For those this may interest, here are references of papers, including some I was involved in that deal with these subjects and perspectives. Best Regards Marcel Vallée Eng. Geol. Géoconseil Marcel Vallée Inc. 706 Routhier St Sainte-Foy, Québec G1X 3J9 Canada Tel: (1) 418 652 3497 Fax: (1) 418 652 9148 Email: [EMAIL PROTECTED] David M., 1976, What Happens If? A few remarks on Useful Geostatistical Concepts for the Design of Sampling Patterns. The Aus. I.M.M Melbourne Branch, Sampling Symposium, Sept. 1976, preprint of proceedings, 16 p. (A major sampling paper) Postolski, T. A., Sinclair, A. J. (1998) Geology as a Basis f
AI-GEOSTATS: re: sampling
I agree with both Marcel and Don that the first question, before any sampling strategy can be chosen, should be what the data is going to be used for, i.e. what is the sampling objective. Of course, Marcel was talking from a mining perspective, I am talking from a soil science perspective. In my sampling optimization software, I tried to include as many different optimization criteria as possible. There are at least three fundamentallydifferent objectives for spatial studies that I have come across: 1) to describe spatial variability. Sometimes finding certain variogram parameters can be an aim by itself (e.g. to detect periodicity or anisotropy). In my opinion, this might be one of the most difficult optimization criteria to formulate (although some people definitely tried, Don among others in a 1987 paper). 2) to optimize spatial interpolation. In my case, this would be important in precision agriculture, in order to produce high quality maps of soil/crop parameters and use those for remedial action. My previous e-mail was mainly focussed on this - minimizing the kriging variance is one of the optimization criteria you could try for this case. I gave this a shot in my Geoderma papers that I referred to earlier. 3) to detect hot-spots or low-spots. In my case, this is very important in soil pollution studies, where your very precisely want to delineate polluted areas (because remediation costs money, and there are health risks involved), but you are not very interested in the areas that are well below the environmental threshold. I suspect that this is quite often the case in minin studies. I tried to tackle this sort of optimization criterion in my environmetrics paper. Of course, one cannot always go without the other. In order to optimize spatial interpolation, you probably need at least an indication of the nature of the spatial variability, and preferably a variogram. I agree with Don that a phased approach is probably best for such cases. However, I don't think I would go for a purely random approach. In my case, I would probably in the first stage lay out a coarse grid over the whole area, and include some short-distance observations (either randomly selected, or somehow clustered). This should give me an idea about the nature of the spatial variability, which I could use to optimize my second stage, additional sampling scheme for minimal kriging variance. Also, the spatial simulated annealing algorithm would allow me to make full use of the first stage samples. Hope this helps, JW. ** Jan Willem van Groenigen University of California - Davis Dept. of Agronomy and Range Science 1 Shield Avenue Davis, CA 95616 - 8515, U.S.A. -- e-mail: [EMAIL PROTECTED] http://agronomy.ucdavis.edu/groenigen tel. (530) 752-3457 fax. (530) 752-4361 * -- * To post a message to the list, send it to [EMAIL PROTECTED] * As a general service to the users, please remember to post a summary of any useful responses to your questions. * To unsubscribe, send an email to [EMAIL PROTECTED] with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list * Support to the list is provided at http://www.ai-geostats.org
AI-GEOSTATS: random start in arc/info
dear all, hope you won't mind for asking very basic question. i musk confess that i am new to the field (not more than 6 months). in raster data, i am trying to calculate average for center cell based on the values in neighbouring cells (say 3 x 3 window). i could perform this by moving window average function (which is focalmean command in arcinfo). for each iteration, i want to start the window at random points. is it possible in Arc/info? i would be grateful if any one can tell me the command to do this fucntion in Arc/info software..and i would also like to know how the moving window function operates. hope you get my problem! regards ramesh Do You Yahoo!? Send a newsletter, share photos & files, conduct polls, organize chat events. Visit http://in/ groups.yahoo.com -- * To post a message to the list, send it to [EMAIL PROTECTED] * As a general service to the users, please remember to post a summary of any useful responses to your questions. * To unsubscribe, send an email to [EMAIL PROTECTED] with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list * Support to the list is provided at http://www.ai-geostats.org
Re: AI-GEOSTATS: re: sampling
Hi folks Numerous apologies to anyone who downloaded Krigame over the last two days. The file got corrupted and isn't actually kriging!! New version now up. Sorry sorry sorry Isobel Clark PS: on Mark Burnett's sampling thing. In South African gold mining, they have 100 years of back sampling in similar reefs (or parts of reefs). This helps a lot for designing the 'coarse' sampling suggested by Jan Willem and then developing reliable local models. Do You Yahoo!? Get your free @yahoo.co.uk address at http://mail.yahoo.co.uk or your free @yahoo.ie address at http://mail.yahoo.ie -- * To post a message to the list, send it to [EMAIL PROTECTED] * As a general service to the users, please remember to post a summary of any useful responses to your questions. * To unsubscribe, send an email to [EMAIL PROTECTED] with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list * Support to the list is provided at http://www.ai-geostats.org
Re: AI-GEOSTATS: random start in arc/info
Hi everyone, I am interested in this problem also. Does anyone know how to do what Ramesh wanted in Arvciew? Regards. Basil Ramesh Krishnamurthy To: [EMAIL PROTECTED] Subject: AI-GEOSTATS: random start in Sent by: arc/info ai-geostats-li [EMAIL PROTECTED] 30-08-2001 00:47 Please respond to Ramesh Krishnamurthy dear all, hope you won't mind for asking very basic question. i musk confess that i am new to the field (not more than 6 months). in raster data, i am trying to calculate average for center cell based on the values in neighbouring cells (say 3 x 3 window). i could perform this by moving window average function (which is focalmean command in arcinfo). for each iteration, i want to start the window at random points. is it possible in Arc/info? i would be grateful if any one can tell me the command to do this fucntion in Arc/info software..and i would also like to know how the moving window function operates. hope you get my problem! regards ramesh Do You Yahoo!? Send a newsletter, share photos & files, conduct polls, organize chat events. Visit http://in/ groups.yahoo.com -- * To post a message to the list, send it to [EMAIL PROTECTED] * As a general service to the users, please remember to post a summary of any useful responses to your questions. * To unsubscribe, send an email to [EMAIL PROTECTED] with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list * Support to the list is provided at http://www.ai-geostats.org -- * To post a message to the list, send it to [EMAIL PROTECTED] * As a general service to the users, please remember to post a summary of any useful responses to your questions. * To unsubscribe, send an email to [EMAIL PROTECTED] with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list * Support to the list is provided at http://www.ai-geostats.org
