Brasil | Otro
dc.contributorUniversidade Estadual Paulista (UNESP)
dc.creatorQueiroz, Joaquim C. B.
dc.creatorSturaro, Jose R.
dc.creatorSaraiva, Augusto C. F.
dc.creatorBarbosa Landim, Paulo M.
dc.date2013-09-30T18:51:09Z
dc.date2014-05-20T14:16:56Z
dc.date2016-10-25T17:39:43Z
dc.date2013-09-30T18:51:09Z
dc.date2014-05-20T14:16:56Z
dc.date2016-10-25T17:39:43Z
dc.date2008-07-01
dc.date.accessioned2017-04-05T22:23:17Z
dc.date.available2017-04-05T22:23:17Z
dc.identifierEnvironmental Geology. New York: Springer, v. 55, n. 1, p. 95-105, 2008.
dc.identifier0943-0105
dc.identifierhttp://hdl.handle.net/11449/25079
dc.identifierhttp://acervodigital.unesp.br/handle/11449/25079
dc.identifier10.1007/s00254-007-0968-3
dc.identifierWOS:000256473900011
dc.identifierhttp://dx.doi.org/10.1007/s00254-007-0968-3
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/870011
dc.descriptionThis paper describes a geostatistical method, known as factorial kriging analysis, which is well suited for analyzing multivariate spatial information. The method involves multivariate variogram modeling, principal component analysis, and cokriging. It uses several separate correlation structures, each corresponding to a specific spatial scale, and yields a set of regionalized factors summarizing the main features of the data for each spatial scale. This method is applied to an area of high manganese-ore mining activity in Amapa State, North Brazil. Two scales of spatial variation (0.33 and 2.0 km) are identified and interpreted. The results indicate that, for the short-range structure, manganese, arsenic, iron, and cadmium are associated with human activities due to the mining work, while for the long-range structure, the high aluminum, selenium, copper, and lead concentrations, seem to be related to the natural environment. At each scale, the correlation structure is analyzed, and regionalized factors are estimated by cokriging and then mapped.
dc.languageeng
dc.publisherSpringer
dc.relationEnvironmental Geology
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectheavy metal pollution
dc.subjectAmapa State
dc.subjectBrazil
dc.subjectfactorial kriging
dc.subjectmultivariate geostatistics
dc.titleGeochemical characterization of heavy metal contaminated area using multivariate factorial kriging
dc.typeOtro


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