Dear David,
You can find information on Geostatistical Analyst here: http://www.esri.com/software/arcgis/extensions/geostatistical/index.html http://www.esri.com/software/arcgis/extensions/geostatistical/eval/evalcd.html http://webhelp.esri.com/arcgisdesktop/9.3/index.cfm?TopicName=An_overview_of_Geostatistical_Analyst (online documentation; i.e. condensed version of the Geostatistical Analyst manual) Several research papers on the models implemented in Geostatistical Analyst can be found here: http://www.esri.com/software/arcgis/extensions/geostatistical/about/literature.html. These papers are relatively old since I was busy writing a book on spatial statistics for GIS users. The book's content: "Introduction to Spatial Statistical Data Analysis for GIS Users" Konstantin Krivoruchko Preface PART ONE. INTRODUCTION TO STATISTICAL DATA ANALYSIS Chapter 1: Statistical approach to GIS data analysis Chapter 2: Examples of the importance of estimating data and model uncertainty Chapter 3: Uncertainty and error in GIS data Chapter 4: Importance of the distribution assumption Chapter 5: Methods for sensitivity and uncertainty analysis Chapter 6: Types of spatial data, statistical models, and model diagnostics Chapter 7: Spatial interpolation using deterministic models PART TWO. PRINCIPLES OF MODELING SPATIAL DATA Chapter 8: Principles of modeling geostatistical data: basic models and tools Chapter 9: Kriging models and their assumptions Chapter 10. Optimal monitoring network design and principles of geostatistical simulation Chapter 11: Principles of modeling regional data Chapter 12: Spatial regression models: concepts and comparison Chapter 13. Principles of modeling discrete points PART THREE. STATISTICAL SOFTWARE USAGE Chapter 14: Geostatistics for exploratory spatial data analysis Chapter 15: Using commercial statistical software for spatial data analysis Chapter 16. Using freeware R statistical packages for spatial data analysis Appendix A: Using ArcGIS Geostatistical Analyst 9.2 Appendix B: Using R as a companion to ArcGIS Appendix C: Introduction to Bayesian modeling using WinBUGS Appendix D: Introduction to spatial regression modeling using SAS Glossary Bibliography Index ESRI Press plans to publish this book in January-February of 2009. In this book, I'm explaining how to use several R software packages (NON-GEOSTATISTICAL because I don't know a good reason to use non-Bayesian geostatistical R packages if one has access to Geostatistical Analyst). FYI: for the future version of Geostatistical Analyst, we are developing several new models and tools, including the following: - interpolation using non-Euclidean distance metric (see paper Krivoruchko, K. and Gribov, A. (2004) Geostatistical interpolation in the presence of barriers. In: geoENV IV - Geostatistics for Environmental Applications: Proceedings of the Fourth European Conference on Geostatistics for Environmental Applications 2002 (Quantitative Geology and Geostatistics), 331-342. at http://www.esri.com/software/arcgis/extensions/geostatistical/about/literature.html) - "areal interpolation" (see Gotway, C.A. and Young, L.J. (2007) A geostatistical approach to linking geographically aggregated data from different sources. Journal of Computational and Graphical Statistics 16 (1), pp. 115-135.) - non-Gaussian disjunctive kriging models - monitoring network design tools - additional options for Gaussian geostatistical simulation Best wishes, Konstantin Krivoruchko, Ph.D. Senior Research Associate, Software Development Team Environmental Systems Research Institute 380 New York St. Redlands, CA, 92373-8100 USA [EMAIL PROTECTED] <mailto:[EMAIL PROTECTED]> http://www.esri.com/software/arcgis/extensions/geostatistical/about/literature.html <http://www.esri.com/software/arcgis/extensions/geostatistical/about/literature.html> ________________________________ Message: 1 Date: Sat, 6 Sep 2008 16:06:47 +0200 From: D G Rossiter <[EMAIL PROTECTED]> Subject: [R-sig-Geo] ArcGIS Geostatistical Analyst -- how does it display / fit variograms? To: [email protected] Message-ID: <[EMAIL PROTECTED]> Content-Type: text/plain Hi, I know this is mostly an R-spatial list but this is where the most computational geostats experts hang out, so please forgive me for asking an ArcGIS question. I use R almost exclusively for my own work, but have been asked to supervise the development of an introductory geostats course for our partner at the University of Rwanda. They have standardized on ArcGIS for all of their GIS work (and SPSS for non-spatial stats), and the prospective students (mostly centre workers and collaborating researchers) are familiar with it. The decision was taken by their administration not to use my R/gstat material from the ITC distance education course, rather to develop the course with ArcGIS. My counterpart is now with me developing the course. The deficiencies of ESRI documentation are well-known. I have dug around quite a bit both within the ESRI docs (on-line and with the program) and through various mailing lists and the web and can not find out some basic information. I hope you can shed some light, 1. What exactly is the display of the empirical variogram? The doc. implies there is one average semivariance per bin (as is usual) but the display often has several at the same bin. The variogram can be exported as a table, where it shows multiple (2 - 6 or so) semivariances for each bin; the table also shows a "weight" for each of these, but they do not add to 1 or 100 or anything I can recognize! The close-range bins usually have one, then the number increases. So I guess each dot represents some number of point-pairs. 2. How is the variogram being fit? What weighting, what solver? If the user changes the cutoff/bin width, the solution changes (as it should); but I can't see how it's solving, and I can't find any option to change the weighting (as in e.g. gstat). 3. When fitting direct and cross-variograms for co-kriging, it seems that a linear model of co-regionalization is being enforced (i.e. same range). Again, how is the fit being done? Like fit.lmc in gstat? Naturally we want the students to understand what the program is doing for them! Although ESRI promotes "press the button and look at the cross-validation". I do like their disclaimer in the ArcGIS Desktop 9.3 help: "Kriging is a complex procedure that requires greater knowledge about spatial statistics than can be conveyed in this command reference". They then ref. Burrough (1986! not even the revised book), Heine (1986), McBratney & Webster Journal of Soil Sci. 37:317 (1986), Oliver IJGIS 4 (1990), Press etc. Numerical Recipes, and Royle et al. Geoprocessing 1 (1981). Not exactly the most up to date or accessible reference list (no offrence to the fine authors mentioned). Thanks for your help. D. G. Rossiter Senior University Lecturer Department of Earth Systems Analysis International Institute for Geo-Information Science and Earth Observation (ITC) PO Box 6, 7500 AA Enschede, The Netherlands Internet: http://www.itc.nl/personal/rossiter/pubs/list.html#pubs_m_R International Institute for Geo-Information Science and Earth Observation (ITC) Chamber of Commerce: 410 27 560 [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-geo
