Spatial Uncertainty Analysis in Ecological Biology
Uncertainty analysis is the part of risk analysis that focuses on the uncertainties in the data characteristics. Important components of uncertainty analysis include qualitative analysis that identifies the uncertainties, quantitative analysis of the effects of the uncertainties on the decision proc...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Zimeras, Stelios [verfasserIn] Matsinos, Yiannis [verfasserIn] |
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| Sprache: |
Englisch |
| Erschienen: |
2013 |
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| Umfang: |
1 Online-Ressource |
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| Übergeordnetes Werk: |
Enthalten in: International journal of systems biology and biomedical technologies - Hershey, Pa : IGI Global, 2012, 2(2013), 1, Seite 14-24 |
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| Übergeordnetes Werk: |
volume:2 ; year:2013 ; number:1 ; pages:14-24 |
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| DOI / URN: |
10.4018/ijsbbt.2013010102 |
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| 520 | |a Uncertainty analysis is the part of risk analysis that focuses on the uncertainties in the data characteristics. Important components of uncertainty analysis include qualitative analysis that identifies the uncertainties, quantitative analysis of the effects of the uncertainties on the decision process, and communication of the uncertainty. (Funtowwicz & Ravetz 1990; Petersen, 2000; Regan et a1., 2002; Katz 2002). The analyses include simple descriptive procedures till quantitative estimation of uncertainty, and decision-based procedures. The analysis may be qualitative or quantitative, depending on the stage of analysis required and the amount of information available. When a neighbourhood structure lattice system is applied, a spatial connectivity between regions is defined where investigation of that structure includes modelling of the spatial homogeneity is introduced. Spatial investigation involves stochastic modelling especially in cases where the incomplete data involves hide informatiońs. In this work a spatial analysis methodology was introduced and procedures to solve the problem with spatial variability are described | ||
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10.4018/ijsbbt.2013010102 doi (DE-627)NLEJ251827704 (VZGNL)10.4018/ijsbbt.2013010102 DE-627 ger DE-627 rakwb eng Zimeras, Stelios verfasserin aut Spatial Uncertainty Analysis in Ecological Biology 2013 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Uncertainty analysis is the part of risk analysis that focuses on the uncertainties in the data characteristics. Important components of uncertainty analysis include qualitative analysis that identifies the uncertainties, quantitative analysis of the effects of the uncertainties on the decision process, and communication of the uncertainty. (Funtowwicz & Ravetz 1990; Petersen, 2000; Regan et a1., 2002; Katz 2002). The analyses include simple descriptive procedures till quantitative estimation of uncertainty, and decision-based procedures. The analysis may be qualitative or quantitative, depending on the stage of analysis required and the amount of information available. When a neighbourhood structure lattice system is applied, a spatial connectivity between regions is defined where investigation of that structure includes modelling of the spatial homogeneity is introduced. Spatial investigation involves stochastic modelling especially in cases where the incomplete data involves hide informatiońs. In this work a spatial analysis methodology was introduced and procedures to solve the problem with spatial variability are described Hierarchical Models Markov Chains Monte Carlo (MCMC) Markov Random Fields Spatial Modelling Spatial Point Analysis Uncertainty Matsinos, Yiannis verfasserin aut Enthalten in International journal of systems biology and biomedical technologies Hershey, Pa : IGI Global, 2012 2(2013), 1, Seite 14-24 Online-Ressource (DE-627)NLEJ244419450 (DE-600)2703840-3 2160-9594 nnns volume:2 year:2013 number:1 pages:14-24 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijsbbt.2013010102 X:IGIG Verlag Deutschlandweit zugänglich http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijsbbt.2013010102&buylink=true Abstract ZDB-1-GIS GBV_NL_ARTICLE AR 2 2013 1 14-24 |
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10.4018/ijsbbt.2013010102 doi (DE-627)NLEJ251827704 (VZGNL)10.4018/ijsbbt.2013010102 DE-627 ger DE-627 rakwb eng Zimeras, Stelios verfasserin aut Spatial Uncertainty Analysis in Ecological Biology 2013 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Uncertainty analysis is the part of risk analysis that focuses on the uncertainties in the data characteristics. Important components of uncertainty analysis include qualitative analysis that identifies the uncertainties, quantitative analysis of the effects of the uncertainties on the decision process, and communication of the uncertainty. (Funtowwicz & Ravetz 1990; Petersen, 2000; Regan et a1., 2002; Katz 2002). The analyses include simple descriptive procedures till quantitative estimation of uncertainty, and decision-based procedures. The analysis may be qualitative or quantitative, depending on the stage of analysis required and the amount of information available. When a neighbourhood structure lattice system is applied, a spatial connectivity between regions is defined where investigation of that structure includes modelling of the spatial homogeneity is introduced. Spatial investigation involves stochastic modelling especially in cases where the incomplete data involves hide informatiońs. In this work a spatial analysis methodology was introduced and procedures to solve the problem with spatial variability are described Hierarchical Models Markov Chains Monte Carlo (MCMC) Markov Random Fields Spatial Modelling Spatial Point Analysis Uncertainty Matsinos, Yiannis verfasserin aut Enthalten in International journal of systems biology and biomedical technologies Hershey, Pa : IGI Global, 2012 2(2013), 1, Seite 14-24 Online-Ressource (DE-627)NLEJ244419450 (DE-600)2703840-3 2160-9594 nnns volume:2 year:2013 number:1 pages:14-24 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijsbbt.2013010102 X:IGIG Verlag Deutschlandweit zugänglich http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijsbbt.2013010102&buylink=true Abstract ZDB-1-GIS GBV_NL_ARTICLE AR 2 2013 1 14-24 |
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10.4018/ijsbbt.2013010102 doi (DE-627)NLEJ251827704 (VZGNL)10.4018/ijsbbt.2013010102 DE-627 ger DE-627 rakwb eng Zimeras, Stelios verfasserin aut Spatial Uncertainty Analysis in Ecological Biology 2013 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Uncertainty analysis is the part of risk analysis that focuses on the uncertainties in the data characteristics. Important components of uncertainty analysis include qualitative analysis that identifies the uncertainties, quantitative analysis of the effects of the uncertainties on the decision process, and communication of the uncertainty. (Funtowwicz & Ravetz 1990; Petersen, 2000; Regan et a1., 2002; Katz 2002). The analyses include simple descriptive procedures till quantitative estimation of uncertainty, and decision-based procedures. The analysis may be qualitative or quantitative, depending on the stage of analysis required and the amount of information available. When a neighbourhood structure lattice system is applied, a spatial connectivity between regions is defined where investigation of that structure includes modelling of the spatial homogeneity is introduced. Spatial investigation involves stochastic modelling especially in cases where the incomplete data involves hide informatiońs. In this work a spatial analysis methodology was introduced and procedures to solve the problem with spatial variability are described Hierarchical Models Markov Chains Monte Carlo (MCMC) Markov Random Fields Spatial Modelling Spatial Point Analysis Uncertainty Matsinos, Yiannis verfasserin aut Enthalten in International journal of systems biology and biomedical technologies Hershey, Pa : IGI Global, 2012 2(2013), 1, Seite 14-24 Online-Ressource (DE-627)NLEJ244419450 (DE-600)2703840-3 2160-9594 nnns volume:2 year:2013 number:1 pages:14-24 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijsbbt.2013010102 X:IGIG Verlag Deutschlandweit zugänglich http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijsbbt.2013010102&buylink=true Abstract ZDB-1-GIS GBV_NL_ARTICLE AR 2 2013 1 14-24 |
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Uncertainty analysis is the part of risk analysis that focuses on the uncertainties in the data characteristics. Important components of uncertainty analysis include qualitative analysis that identifies the uncertainties, quantitative analysis of the effects of the uncertainties on the decision process, and communication of the uncertainty. (Funtowwicz & Ravetz 1990; Petersen, 2000; Regan et a1., 2002; Katz 2002). The analyses include simple descriptive procedures till quantitative estimation of uncertainty, and decision-based procedures. The analysis may be qualitative or quantitative, depending on the stage of analysis required and the amount of information available. When a neighbourhood structure lattice system is applied, a spatial connectivity between regions is defined where investigation of that structure includes modelling of the spatial homogeneity is introduced. Spatial investigation involves stochastic modelling especially in cases where the incomplete data involves hide informatiońs. In this work a spatial analysis methodology was introduced and procedures to solve the problem with spatial variability are described |
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Uncertainty analysis is the part of risk analysis that focuses on the uncertainties in the data characteristics. Important components of uncertainty analysis include qualitative analysis that identifies the uncertainties, quantitative analysis of the effects of the uncertainties on the decision process, and communication of the uncertainty. (Funtowwicz & Ravetz 1990; Petersen, 2000; Regan et a1., 2002; Katz 2002). The analyses include simple descriptive procedures till quantitative estimation of uncertainty, and decision-based procedures. The analysis may be qualitative or quantitative, depending on the stage of analysis required and the amount of information available. When a neighbourhood structure lattice system is applied, a spatial connectivity between regions is defined where investigation of that structure includes modelling of the spatial homogeneity is introduced. Spatial investigation involves stochastic modelling especially in cases where the incomplete data involves hide informatiońs. In this work a spatial analysis methodology was introduced and procedures to solve the problem with spatial variability are described |
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Uncertainty analysis is the part of risk analysis that focuses on the uncertainties in the data characteristics. Important components of uncertainty analysis include qualitative analysis that identifies the uncertainties, quantitative analysis of the effects of the uncertainties on the decision process, and communication of the uncertainty. (Funtowwicz & Ravetz 1990; Petersen, 2000; Regan et a1., 2002; Katz 2002). The analyses include simple descriptive procedures till quantitative estimation of uncertainty, and decision-based procedures. The analysis may be qualitative or quantitative, depending on the stage of analysis required and the amount of information available. When a neighbourhood structure lattice system is applied, a spatial connectivity between regions is defined where investigation of that structure includes modelling of the spatial homogeneity is introduced. Spatial investigation involves stochastic modelling especially in cases where the incomplete data involves hide informatiońs. In this work a spatial analysis methodology was introduced and procedures to solve the problem with spatial variability are described |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">NLEJ251827704</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20231205144003.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">231128s2013 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.4018/ijsbbt.2013010102</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)NLEJ251827704</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(VZGNL)10.4018/ijsbbt.2013010102</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Zimeras, Stelios</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Spatial Uncertainty Analysis in Ecological Biology</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2013</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Uncertainty analysis is the part of risk analysis that focuses on the uncertainties in the data characteristics. Important components of uncertainty analysis include qualitative analysis that identifies the uncertainties, quantitative analysis of the effects of the uncertainties on the decision process, and communication of the uncertainty. (Funtowwicz & Ravetz 1990; Petersen, 2000; Regan et a1., 2002; Katz 2002). The analyses include simple descriptive procedures till quantitative estimation of uncertainty, and decision-based procedures. The analysis may be qualitative or quantitative, depending on the stage of analysis required and the amount of information available. When a neighbourhood structure lattice system is applied, a spatial connectivity between regions is defined where investigation of that structure includes modelling of the spatial homogeneity is introduced. Spatial investigation involves stochastic modelling especially in cases where the incomplete data involves hide informatiońs. 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