Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/14380
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yoo, E. H. | - |
dc.contributor.author | Kyriakidis, Phaedon | - |
dc.date.accessioned | 2019-07-08T08:07:31Z | - |
dc.date.available | 2019-07-08T08:07:31Z | - |
dc.date.issued | 2006-10-01 | - |
dc.identifier.citation | Journal of Geographical Systems, Volume 8, Issue 4, October 2006, Pages 357-390 | en_US |
dc.identifier.issn | 14355930 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.14279/14380 | - |
dc.description.abstract | In practical applications of area-to-point spatial interpolation, inequality constraints, such as non-negativity or more general constraints on the maximum and/or minimum attribute value, should be taken into account. The geostatistical framework proposed in this paper deals with the spatial interpolation problem of downscaling areal data under such constraints, while: (1) explicitly accounting for support differences between sample data and unknown values, (2) guaranteeing coherent (mass-preserving) predictions, and (3) providing a measure of reliability (uncertainty) for the resulting predictions. The formal equivalence between Kriging and spline interpolation allows solving constrained area-to-point interpolation problems via quadratic programming (QP) algorithms, after accounting for the support differences between various constraints involved in the problem formulation. In addition, if inequality constraints are enforced on the entire set of points discretizing the study domain, the numerical algorithms for QP problems are applied only to selected locations where the corresponding predictions violate such constraints. The application of the proposed method of area-to-point spatial interpolation with inequality constraints in one and two dimension is demonstrated using realistically simulated data. © Springer-Verlag 2006. | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | Journal of Geographical Systems | en_US |
dc.subject | Coherence | en_US |
dc.subject | Downscaling | en_US |
dc.subject | Quadraticprogramming | en_US |
dc.subject | Spline interpolation | en_US |
dc.title | Area-to-point Kriging with inequality-type data | en_US |
dc.type | Article | en_US |
dc.collaboration | University of California Santa Barbara | en_US |
dc.subject.category | Civil Engineering | en_US |
dc.journals | Subscription Journal | en_US |
dc.country | United States | en_US |
dc.subject.field | Engineering and Technology | en_US |
dc.publication | Peer Reviewed | en_US |
dc.identifier.doi | 10.1007/s10109-006-0036-7 | en_US |
dc.identifier.scopus | 2-s2.0-33750682343 | en |
dc.identifier.url | https://api.elsevier.com/content/abstract/scopus_id/33750682343 | en |
dc.contributor.orcid | #NODATA# | en |
dc.contributor.orcid | #NODATA# | en |
dc.relation.issue | 4 | en |
dc.relation.volume | 8 | en |
cut.common.academicyear | 2006-2007 | en_US |
item.fulltext | No Fulltext | - |
item.cerifentitytype | Publications | - |
item.grantfulltext | none | - |
item.openairecristype | http://purl.org/coar/resource_type/c_6501 | - |
item.openairetype | article | - |
item.languageiso639-1 | en | - |
crisitem.journal.journalissn | 1435-5949 | - |
crisitem.journal.publisher | Springer Nature | - |
crisitem.author.dept | Department of Civil Engineering and Geomatics | - |
crisitem.author.faculty | Faculty of Engineering and Technology | - |
crisitem.author.orcid | 0000-0003-4222-8567 | - |
crisitem.author.parentorg | Faculty of Engineering and Technology | - |
Appears in Collections: | Άρθρα/Articles |
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