1. ZHAW digitalcollection
  2. School of Engineering
  3. Publikationen
  4. Publikationen School of Engineering
Full metadata record
DC FieldValueLanguage
dc.contributor.authorHofer, Christoph-
dc.contributor.authorPapritz, Andreas-
dc.date.accessioned2018-11-30T10:43:15Z-
dc.date.available2018-11-30T10:43:15Z-
dc.date.issued2010-
dc.identifier.issn1874-8961de_CH
dc.identifier.issn1874-8953de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/13421-
dc.description.abstractSoil contamination by heavy metals and organic pollutants around industrial premises is a problem in many countries around the world. Delineating zones where pollutants exceed tolerable levels is a necessity for successfully mitigating related health risks. Predictions of pollutants are usually required for blocks because remediation or regulatory decisions are imposed for entire parcels. Parcel areas typically exceed the observation support, but are smaller than the survey domain. Mapping soil pollution therefore involves a local change of support. The goal of this work is to find a simple, robust, and precise method for predicting block means (linear predictions) and threshold exceedance by block means (nonlinear predictions) from data observed at points that show a spatial trend. By simulations, we compared the performance of universal block kriging (UK), Gaussian conditional simulations (CS), constrained (CK), and covariance-matching constrained kriging (CMCK), for linear and nonlinear local change of support prediction problems. We considered Gaussian and positively skewed spatial processes with a nonstationary mean function and various scenarios for the autocorrelated error. The linear predictions were assessed by bias and mean square prediction error and the nonlinear predictions by bias and Peirce skill scores. For Gaussian data and blocks with locally dense sampling, all four methods performed well, both for linear and nonlinear predictions. When sampling was sparse CK and CMCK gave less precise linear predictions, but outperformed UK for nonlinear predictions, irrespective of the data distribution. CK and CMCK were only outperformed by CS in the Gaussian case when threshold exceedance was predicted by the conditional quantiles. However, CS was strongly biased for the skewed data whereas CK and CMCK still provided unbiased and quite precise nonlinear predictions. CMCK did not show any advantages over CK. CK is as simple to compute as UK. We recommend therefore this method to predict block means and nonlinear transforms thereof because it offers a good compromise between robustness, simplicity, and precision.de_CH
dc.language.isoende_CH
dc.publisherSpringerde_CH
dc.relation.ispartofMathematical Geosciencesde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subject.ddc363: Umwelt- und Sicherheitsproblemede_CH
dc.titlePredicting threshold exceedance by local block means in soil pollution surveysde_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Datenanalyse und Prozessdesign (IDP)de_CH
dc.identifier.doi10.1007/s11004-010-9287-4de_CH
zhaw.funding.euNode_CH
zhaw.issue6de_CH
zhaw.originated.zhawNode_CH
zhaw.pages.end656de_CH
zhaw.pages.start631de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume42de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
Appears in collections:Publikationen School of Engineering

Files in This Item:
There are no files associated with this item.
Show simple item record
Hofer, C., & Papritz, A. (2010). Predicting threshold exceedance by local block means in soil pollution surveys. Mathematical Geosciences, 42(6), 631–656. https://doi.org/10.1007/s11004-010-9287-4
Hofer, C. and Papritz, A. (2010) ‘Predicting threshold exceedance by local block means in soil pollution surveys’, Mathematical Geosciences, 42(6), pp. 631–656. Available at: https://doi.org/10.1007/s11004-010-9287-4.
C. Hofer and A. Papritz, “Predicting threshold exceedance by local block means in soil pollution surveys,” Mathematical Geosciences, vol. 42, no. 6, pp. 631–656, 2010, doi: 10.1007/s11004-010-9287-4.
HOFER, Christoph und Andreas PAPRITZ, 2010. Predicting threshold exceedance by local block means in soil pollution surveys. Mathematical Geosciences. 2010. Bd. 42, Nr. 6, S. 631–656. DOI 10.1007/s11004-010-9287-4
Hofer, Christoph, and Andreas Papritz. 2010. “Predicting Threshold Exceedance by Local Block Means in Soil Pollution Surveys.” Mathematical Geosciences 42 (6): 631–56. https://doi.org/10.1007/s11004-010-9287-4.
Hofer, Christoph, and Andreas Papritz. “Predicting Threshold Exceedance by Local Block Means in Soil Pollution Surveys.” Mathematical Geosciences, vol. 42, no. 6, 2010, pp. 631–56, https://doi.org/10.1007/s11004-010-9287-4.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.