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020 _a9780470517260
040 _aCIBESPAM MFL
041 _aeng
082 _a519.5
_bW377
_c2007
100 _aWebster, Richard
245 _aGeostatistics for environmental scientists.
250 _aSecond Edition
260 _aEngland
_bEditorial Wiley
_c2007
300 _ax, 315 páginas;
_btable, illustration, figure;
_c23.5 cm x 16 cm
490 _a Statistics for Social Sciences
505 _a--Preface 1.- Introduction 2.- Basic Statistics 3.- Prediction and Interpolation 4.- Characterizing Spatial Processes: The Covariance and Variogram 5.- Modelling the Variogram 6.- Reliability of the Experimental Variogram and Nested Sampling 7.- Spectral Analysis 8.- Local Estimation or Prediction: Kriging 9.- Kriging in the Presence of Trend and Factorial Kriging 10.- Cross-Correlation, Coregionalization and Cokriging 11.- Disjunctive Kriging 12.- Stochastic Simulation (new file) --Appendix A --Appendix B --References --Index
520 _aGeostatistics is essential for environmental scientists. Weather and climate vary from place to place, soil varies at every scale at which it is examined, and even man-made attributes – such as the distribution of pollution – vary. The techniques used in geostatistics are ideally suited to the needs of environmental scientists, who use them to make the best of sparse data for prediction, and top plan future surveys when resources are limited. Geostatistical technology has advanced much in the last few years and many of these developments are being incorporated into the practitioner’s repertoire. This second edition describes these techniques for environmental scientists. Topics such as stochastic simulation, sampling, data screening, spatial covariances, the variogram and its modeling, and spatial prediction by kriging are described in rich detail. At each stage the underlying theory is fully explained, and the rationale behind the choices given.
650 _aReliability
650 _aSpectral
650 _aVariogram
650 _aInterpolation
650 _aKriging
650 _aCokriging
700 _aOliver, Margaret A.
912 _c2023-12-12
_dMaría Zambrano
913 _aFNME
_bCIA
_dGARNB
942 _2ddc
_cBK
999 _c12992
_d12992