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 

kkrivoruchko@esri.com <mailto:kkrivoruchko@esri.com> 

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 <rossiter@itc.nl>
Subject: [R-sig-Geo] ArcGIS Geostatistical Analyst -- how does it
        display /       fit variograms?
To: r-sig-geo@stat.math.ethz.ch
Message-ID: <C78D7D02-C9B4-40B1-A085-5871251D3355@itc.nl>
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)
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