FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3134131752> ?p ?o ?g. }

• W3134131752 endingPage "100494" @default.
• W3134131752 startingPage "100494" @default.
• W3134131752 abstract "We address the problem of characterizing spatially variable Natural Background Levels (NBLs) of concentrations of chemical species of environmental concern in a large-scale groundwater body. Assessment of NBLs is critical to identify significant trends of (possibly hazardous) chemical concentrations in aquifer systems, the latter being typically associated with spatially heterogeneous hydrogeochemical characteristics. Our study considers the entire probability density function (PDF) of the concentration of the chemical species of interest as atom of the statistical analysis. These PDFs are estimated across a network of observation boreholes in the investigated spatial domain, and modeled as random points in a Bayes Hilbert space, in the context of Object Oriented Data Analysis. This approach enables one to take advantage of the entire information content provided by these objects for the purpose of spatial prediction and uncertainty quantification. As a key element of innovation, we investigate the use of depth measures for distributional data with the distinctive aims of (i) detecting central and outlying NBL distributions in the dataset, and (ii) building prediction regions for NBL distribution at unsampled locations. We illustrate the results of the proposed approach to the analysis of NBLs of a selected chemical species detected at an environmental monitoring network within a large-scale alluvial aquifer in Northern Italy." @default.
• W3134131752 created "2021-03-15" @default.
• W3134131752 creator A5004415634 @default.
• W3134131752 creator A5016716189 @default.
• W3134131752 creator A5043309612 @default.
• W3134131752 creator A5063994264 @default.
• W3134131752 date "2021-06-01" @default.
• W3134131752 modified "2023-10-17" @default.
• W3134131752 title "Object oriented spatial analysis of natural concentration levels of chemical species in regional-scale aquifers" @default.
• W3134131752 cites W1495929194 @default.
• W3134131752 cites W1570886746 @default.
• W3134131752 cites W1599435328 @default.
• W3134131752 cites W1964090321 @default.
• W3134131752 cites W1966493274 @default.
• W3134131752 cites W1969903564 @default.
• W3134131752 cites W1973744648 @default.
• W3134131752 cites W1989659377 @default.
• W3134131752 cites W1997892237 @default.
• W3134131752 cites W1998132159 @default.
• W3134131752 cites W2007873570 @default.
• W3134131752 cites W2008528491 @default.
• W3134131752 cites W2012491154 @default.
• W3134131752 cites W2019317784 @default.
• W3134131752 cites W2019926951 @default.
• W3134131752 cites W2029763864 @default.
• W3134131752 cites W2030360243 @default.
• W3134131752 cites W2031084363 @default.
• W3134131752 cites W2067167380 @default.
• W3134131752 cites W2069933289 @default.
• W3134131752 cites W2070179406 @default.
• W3134131752 cites W2085570173 @default.
• W3134131752 cites W2088298220 @default.
• W3134131752 cites W2093071433 @default.
• W3134131752 cites W2108258626 @default.
• W3134131752 cites W2111716572 @default.
• W3134131752 cites W2116576469 @default.
• W3134131752 cites W2118388017 @default.
• W3134131752 cites W2119178247 @default.
• W3134131752 cites W2163169537 @default.
• W3134131752 cites W2194234745 @default.
• W3134131752 cites W2205619076 @default.
• W3134131752 cites W2207209165 @default.
• W3134131752 cites W2263497564 @default.
• W3134131752 cites W2284033163 @default.
• W3134131752 cites W2290213948 @default.
• W3134131752 cites W2462228393 @default.
• W3134131752 cites W2464895787 @default.
• W3134131752 cites W2529486112 @default.
• W3134131752 cites W2607755259 @default.
• W3134131752 cites W2620616433 @default.
• W3134131752 cites W2785575956 @default.
• W3134131752 cites W2886603640 @default.
• W3134131752 cites W2895464103 @default.
• W3134131752 cites W2904727216 @default.
• W3134131752 cites W2964050710 @default.
• W3134131752 cites W3034719083 @default.
• W3134131752 cites W3094363956 @default.
• W3134131752 cites W4250766106 @default.
• W3134131752 cites W71689223 @default.
• W3134131752 cites W792722683 @default.
• W3134131752 cites W963581000 @default.
• W3134131752 doi "https://doi.org/10.1016/j.spasta.2021.100494" @default.
• W3134131752 hasPublicationYear "2021" @default.
• W3134131752 type Work @default.
• W3134131752 sameAs 3134131752 @default.
• W3134131752 citedByCount "4" @default.
• W3134131752 countsByYear W31341317522022 @default.
• W3134131752 countsByYear W31341317522023 @default.
• W3134131752 crossrefType "journal-article" @default.
• W3134131752 hasAuthorship W3134131752A5004415634 @default.
• W3134131752 hasAuthorship W3134131752A5016716189 @default.
• W3134131752 hasAuthorship W3134131752A5043309612 @default.
• W3134131752 hasAuthorship W3134131752A5063994264 @default.
• W3134131752 hasBestOaLocation W31341317522 @default.
• W3134131752 hasConcept C105795698 @default.
• W3134131752 hasConcept C127313418 @default.
• W3134131752 hasConcept C158709400 @default.
• W3134131752 hasConcept C159390177 @default.
• W3134131752 hasConcept C159620131 @default.
• W3134131752 hasConcept C166957645 @default.
• W3134131752 hasConcept C187320778 @default.
• W3134131752 hasConcept C18903297 @default.
• W3134131752 hasConcept C197055811 @default.
• W3134131752 hasConcept C205649164 @default.
• W3134131752 hasConcept C2777016058 @default.
• W3134131752 hasConcept C2778755073 @default.
• W3134131752 hasConcept C2779343474 @default.
• W3134131752 hasConcept C33923547 @default.
• W3134131752 hasConcept C39432304 @default.
• W3134131752 hasConcept C58640448 @default.
• W3134131752 hasConcept C75622301 @default.
• W3134131752 hasConcept C76177295 @default.
• W3134131752 hasConcept C76886044 @default.
• W3134131752 hasConcept C86803240 @default.
• W3134131752 hasConceptScore W3134131752C105795698 @default.
• W3134131752 hasConceptScore W3134131752C127313418 @default.
• W3134131752 hasConceptScore W3134131752C158709400 @default.
• W3134131752 hasConceptScore W3134131752C159390177 @default.

• next