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...
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Format: | Article |
Language: | English |
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Universidade de São Paulo
2010-03-01
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Series: | Geologia USP. Série Científica |
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Online Access: | http://ppegeo-local.igc.usp.br/pdf/guspsc/v10n1/01.pdf |
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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 |