Spatial statistics and geostatistics: theory and applications for geographic information science & technology
Language: English Publication details: London: Sage, 2013. Description: xiv, 181p.; 21cmsISBN: 9781446201749Subject(s): Spatial autocorrelation -- Spatial sampling | Spatial weight matrics -- Spatial linear operatorsDDC classification: 910.285 C48| Item type | Current library | Call number | Status | Date due | Barcode |
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Dr. S. R. Ranganathan Library General Stacks | 910.285 C48 (Browse shelf(Opens below)) | Available | 3176 |
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| 910.285 B43, 3:2 Remote sensing and GIS | 910.285 B43, 3:3 Remote sensing and GIS | 910.285 B43, 3:4 Remote sensing and GIS | 910.285 C48 Spatial statistics and geostatistics: theory and applications for geographic information science & technology | 910.285 C53 Geographic information systems and environmental modeling | 910.285 F68 Geographically weighted regression: the analysis of spatially varying relationships | 910.285 H49 An introduction to geographical information systems |
Spatial Statistics and Geostatistics is the definitive text on spatial statistics. Its focus is on spatial statistics as a distinct form of statistical analysis and it includes computer components for ArcGIS, R, SAS, and WinBUGS. The teaching and learning objective of the text is to illustrate the use of basic spatial statistics and geostatistics, as well as the spatial filtering techniques used in all the relevant programs and software.
The text is a systematic overview of the canonical spatial statistical and geostatistical methods. It explains and demonstrates methods and techniques in spatial sampling; spatial autocorrelation; spatial composition (heterogeneity, homogeneity) and configuration (contiguity), spatially adjusted regression and related spatial econometrics; local statistics: hot and cold spots; geostatistics and related techniques in measuring spatial variance and co-variance; and methods for spatial interpolation in two-dimensions. A concluding section discusses advanced topics in spatial statistics: these include Bayesian methods, the Monte Carlo simulation, and error and uncertainty.
Fully explanatory, Spatial Statistics and Geostatistics uses boxed computer code, diagrams, illustrations; and includes further readings. Case study and exemplary materials and data sets are also included.