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024 7 $a10.1007/978-3-319-15865-5
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100   $a20150330d2015      u|         0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 10$aBasic Steps in Geostatistics: The Variogram and Kriging /$fby Margaret A. Oliver, Richard Webster
205   $a1st ed. 2015.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015.
215   $a1 online resource (106 p.)
225 1 $aSpringerBriefs in Agriculture,$x2211-808X
300   $aDescription based upon print version of record.
311 08$a3-319-15864-3 
320   $aIncludes bibliographical references and index.
327   $a1. Introduction -- 1.1. Background to Geostatistics -- 1.2. Applications of geostatistics -- 1.3. Sampling -- 1.4. The Essence of Geostatistics -- 2. Regionalized Variable Theory -- 2.1. Random Variables and Regionalized Variable Theory -- 3. The Variogram and Modelling -- 3.1. The Experimental Variogram -- 3.2. Factors Affecting the Reliability of Experimental Variograms -- 3.3. Modelling the Variogram -- 3.4. Factors Affecting the Reliability of Variogram Models -- 4. Geostatistical Prediction: Kriging -- 4.1. Introduction -- 4.2. Theory -- 4.3. Cross-validation -- 4.4. Summary -- 5. Sampling -- 5.1. Sampling for the Variogram -- 5.2. Sampling Plans for Mapping -- 5.3. Summary -- 6. Dealing with Trend -- 6.1. Trend -- 6.2. Example -- 6.3. Illustration from a Case Study -- 6.4. Summary.
330   $aThis brief will provide a bridge in succinct form between the geostatistics textbooks and the computer manuals for `push-button' practice.  It is becoming increasingly important for practitioners, especially neophytes, to understand what underlies modern geostatistics and the currently available software so that they can choose sensibly and draw correct conclusions from their analysis and mapping.   The brief will contain some theory, but only that needed for practitioners to understand the essential steps in analyses. It will guide readers sequentially through the stages of properly designed sampling, exploratory data analysis, variography (computing the variogram and modelling it), followed by ordinary kriging and finally mapping kriged estimates and their errors. There will be short section on trend and universal kriging.  Other types of kriging will be mentioned so that readers can delve further in the substantive literature to tackle more complex tasks.
410  0$aSpringerBriefs in Agriculture,$x2211-808X
606   $aAgriculture
606   $aGeotechnical engineering
606   $aGeophysics
606   $aEcology
606   $aStatistics
606   $aAgriculture$3https://scigraph.springernature.com/ontologies/product-market-codes/L11006
606   $aGeotechnical Engineering & Applied Earth Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/G37010
606   $aGeophysics/Geodesy$3https://scigraph.springernature.com/ontologies/product-market-codes/G18009
606   $aEcology$3https://scigraph.springernature.com/ontologies/product-market-codes/L19007
606   $aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/S17020
615  0$aAgriculture.
615  0$aGeotechnical engineering.
615  0$aGeophysics.
615  0$aEcology.
615  0$aStatistics.
615 14$aAgriculture.
615 24$aGeotechnical Engineering & Applied Earth Sciences.
615 24$aGeophysics/Geodesy.
615 24$aEcology.
615 24$aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
676   $a550.72
700   $aOliver$b Margaret A$4aut$4http://id.loc.gov/vocabulary/relators/aut$0438180
702   $aWebster$b Richard$4aut$4http://id.loc.gov/vocabulary/relators/aut
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910768163003321
996   $aBasic Steps in Geostatistics: The Variogram and Kriging$93655311
997   $aUNINA