Calculation of Probability Maps Directly from Ordinary Kriging Weights

Probability maps are useful to analyze ores or contaminants in soils and they are helpful to make a decision duringexploration work. These probability maps are usually derived from the indicator kriging approach. Ordinary krigingweights can be used to derive probability maps as well. For testing the...

Full description

Bibliographic Details
Main Author: Jorge Kazuo Yamamoto
Format: Article
Language:English
Published: Universidade de São Paulo 2010-03-01
Series:Geologia USP. Série Científica
Subjects:
Online Access:http://ppegeo-local.igc.usp.br/pdf/guspsc/v10n1/01.pdf
_version_ 1819051642725597184
author Jorge Kazuo Yamamoto
author_facet Jorge Kazuo Yamamoto
author_sort Jorge Kazuo Yamamoto
collection DOAJ
description Probability maps are useful to analyze ores or contaminants in soils and they are helpful to make a decision duringexploration work. These probability maps are usually derived from the indicator kriging approach. Ordinary krigingweights can be used to derive probability maps as well. For testing these two approaches a sample data base was randomlydrawn from an exhaustive data set. From the exhaustive data set actual cumulative distribution functions were determined.Thus, estimated and actual conditional cumulative distribution functions were compared. The vast majority of correlationcoeffi cients between estimated and actual probability maps is greater than 0.75. Not only does the ordinary kriging approachwork, but it also gives slightly better results than median indicator kriging. Moreover, probability maps from ordinary krigingweights are much easier than the traditional approach based on either indicator kriging or median indicator kriging.
first_indexed 2024-12-21T12:07:11Z
format Article
id doaj.art-738cd83b3134473e8ead7198393711a3
institution Directory Open Access Journal
issn 1519-874X
language English
last_indexed 2024-12-21T12:07:11Z
publishDate 2010-03-01
publisher Universidade de São Paulo
record_format Article
series Geologia USP. Série Científica
spelling doaj.art-738cd83b3134473e8ead7198393711a32022-12-21T19:04:41ZengUniversidade de São PauloGeologia USP. Série Científica1519-874X2010-03-01101314Calculation of Probability Maps Directly from Ordinary Kriging WeightsJorge Kazuo YamamotoProbability maps are useful to analyze ores or contaminants in soils and they are helpful to make a decision duringexploration work. These probability maps are usually derived from the indicator kriging approach. Ordinary krigingweights can be used to derive probability maps as well. For testing these two approaches a sample data base was randomlydrawn from an exhaustive data set. From the exhaustive data set actual cumulative distribution functions were determined.Thus, estimated and actual conditional cumulative distribution functions were compared. The vast majority of correlationcoeffi cients between estimated and actual probability maps is greater than 0.75. Not only does the ordinary kriging approachwork, but it also gives slightly better results than median indicator kriging. Moreover, probability maps from ordinary krigingweights are much easier than the traditional approach based on either indicator kriging or median indicator kriging.http://ppegeo-local.igc.usp.br/pdf/guspsc/v10n1/01.pdfProbability mapIndicator krigingOrdinary kriging
spellingShingle Jorge Kazuo Yamamoto
Calculation of Probability Maps Directly from Ordinary Kriging Weights
Geologia USP. Série Científica
Probability map
Indicator kriging
Ordinary kriging
title Calculation of Probability Maps Directly from Ordinary Kriging Weights
title_full Calculation of Probability Maps Directly from Ordinary Kriging Weights
title_fullStr Calculation of Probability Maps Directly from Ordinary Kriging Weights
title_full_unstemmed Calculation of Probability Maps Directly from Ordinary Kriging Weights
title_short Calculation of Probability Maps Directly from Ordinary Kriging Weights
title_sort calculation of probability maps directly from ordinary kriging weights
topic Probability map
Indicator kriging
Ordinary kriging
url http://ppegeo-local.igc.usp.br/pdf/guspsc/v10n1/01.pdf
work_keys_str_mv AT jorgekazuoyamamoto calculationofprobabilitymapsdirectlyfromordinarykrigingweights