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spatial-analyst.net is a non-commercial website intended for users interested in advanced use of geocomputational tools. The topics discussed generally belong to spatio-temporal data analysis sciences, digital cartography, geomorphometry, geostatistics, geovisualization, GPS navigation, raster-based GIS modelling and similar. Most of the articles presented are only supplementary materials to various research publications. Visitors of the website are kindly asked to refer to the peer-reviewed publications, when citing some of the materials, instead of referring to the URL of an article. All materials are prepared on an informative basis only. This is a wiki project, which obviously means that you can edit, extend and modify much of its content. Please also read the disclaimer before using some of the materials. and NO! This site has not much to do with the ESRI's spatial analyst extension.

• Install R, ILWIS, SAGA, and GRASS GIS
• Get training in R
• Learn scripting in R
• Run regression-kriging
• Choose the best spatial predictor
• Export maps to Google Earth
• Obtain global datasets

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I have just finished with updating the second edition of my lecture notes that I have used over years for the GEOSTAT summer schools for PhD students (it includes seven case studies with self-study questions). This is an open access publication, so you can simply donwload a PDF from here. Printed copies of this book can be order via www.lulu.com for $12.78; Lulu products are eligible for discounts when you order 10, 25, or more! The book typically ships in 3–5 business days (US orders). For orders in Europe you might have to wait a bit longer. Lulu prints are really of high quality (text in figures is readable throughout the book, binding is excellent), so I advise you to better order printed copies than to print the book yourself. The book's homepage hosts all data sets and R code used in the book. If you discover errors and typos in the text, I would appreciate if you submit the errors via the book's website.

GEOSTAT focuses on important aspects of statistical analysis of spatial and spatio-temporal data using open source / free GIS tools: R, SAGA GIS, GRASS GIS, Quantum GIS, GDAL, Google Earth and similar. The course participants learn how to move data back and forth between the different environments; how to produce scripts and automate analysis. We welcome also R beginners and users needing refresh courses in programming, however, some basic knowledge of statistics and geocomputing is a prerequisite to follow the lectures. This year, we would also like to introduce/promote topics such as: web-based computing, WPS client-server environments, 3D and 4D geostatistics, combining R+SAGA/GRASS. This is a 5-day course with two parallel sessions, which means that there will be total 7 full-day blocks (three days with parallel sessions) of lectures; the last day of the summer school participants can present their research problems and ask for feedback from the whole summer school. Dead-line to register: 15th February.