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Comparative study of fuzzy-AHP and BBN for spatially-explicit prediction of bark beetle predisposition.

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Title: Comparative study of fuzzy-AHP and BBN for spatially-explicit prediction of bark beetle predisposition.
Authors: Tahri, Meryem1 (AUTHOR) tahri@fld.czu.cz, Kašpar, Jan1 (AUTHOR), Madsen, Anders L.2,3 (AUTHOR), Modlinger, Roman1 (AUTHOR), Zabihi, Khodabakhsh1 (AUTHOR), Marušák, Róbert1 (AUTHOR), Vacik, Harald4 (AUTHOR)
Source: Environmental Modelling & Software. Jan2022, Vol. 147, pN.PAG-N.PAG. 1p.
Subject Terms: Bark beetles, Analytic network process, Ips typographus, Analytic hierarchy process, Geographic information systems, Norway spruce
Abstract: The European spruce bark beetle ' Ips typographus L.' is the most serious disturbance agent for European forests. The complex interactions of many influencing factors need to be integrated into a model-based decision-support system to reduce the potential loss of forests. This paper compares two methodological approaches for spatially-explicit prediction of the predisposition for bark beetle infestations. The fuzzy analytic hierarchy process and the Bayesian belief networks were used in combination with a geographical information system to manage uncertainties. Using available data resources, the two approaches were evaluated to produce robust results for forest practitioners and to support measures to minimize the spread of bark beetles. The findings revealed that nearly 32% of the sites investigated in a case study were moderately-high or high risk categories. It is concluded that BBN is more efficient. Both methods can easily be used to analyze environmental problems involving complex interactions among various criteria. [Display omitted] • Comparison of the application of spatial BBN and fuzzy-AHP in forest ecology. • Spatially explicit evaluation of the predisposition of bark beetle infestation. • Participatory process to quantify expert and stakeholder perceptions. • BBN approach more efficient than fuzzy-AHP. [ABSTRACT FROM AUTHOR]
Copyright of Environmental Modelling & Software is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: GreenFILE
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Header DbId: 8gh
DbLabel: GreenFILE
An: 153869097
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Comparative study of fuzzy-AHP and BBN for spatially-explicit prediction of bark beetle predisposition.
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  Data: <searchLink fieldCode="AR" term="%22Tahri%2C+Meryem%22">Tahri, Meryem</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> tahri@fld.czu.cz</i><br /><searchLink fieldCode="AR" term="%22Kašpar%2C+Jan%22">Kašpar, Jan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Madsen%2C+Anders+L%2E%22">Madsen, Anders L.</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Modlinger%2C+Roman%22">Modlinger, Roman</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zabihi%2C+Khodabakhsh%22">Zabihi, Khodabakhsh</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Marušák%2C+Róbert%22">Marušák, Róbert</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Vacik%2C+Harald%22">Vacik, Harald</searchLink><relatesTo>4</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Environmental+Modelling+%26+Software%22">Environmental Modelling & Software</searchLink>. Jan2022, Vol. 147, pN.PAG-N.PAG. 1p.
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%22Bark+beetles%22">Bark beetles</searchLink><br /><searchLink fieldCode="DE" term="%22Analytic+network+process%22">Analytic network process</searchLink><br /><searchLink fieldCode="DE" term="%22Ips+typographus%22">Ips typographus</searchLink><br /><searchLink fieldCode="DE" term="%22Analytic+hierarchy+process%22">Analytic hierarchy process</searchLink><br /><searchLink fieldCode="DE" term="%22Geographic+information+systems%22">Geographic information systems</searchLink><br /><searchLink fieldCode="DE" term="%22Norway+spruce%22">Norway spruce</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The European spruce bark beetle ' Ips typographus L.' is the most serious disturbance agent for European forests. The complex interactions of many influencing factors need to be integrated into a model-based decision-support system to reduce the potential loss of forests. This paper compares two methodological approaches for spatially-explicit prediction of the predisposition for bark beetle infestations. The fuzzy analytic hierarchy process and the Bayesian belief networks were used in combination with a geographical information system to manage uncertainties. Using available data resources, the two approaches were evaluated to produce robust results for forest practitioners and to support measures to minimize the spread of bark beetles. The findings revealed that nearly 32% of the sites investigated in a case study were moderately-high or high risk categories. It is concluded that BBN is more efficient. Both methods can easily be used to analyze environmental problems involving complex interactions among various criteria. [Display omitted] • Comparison of the application of spatial BBN and fuzzy-AHP in forest ecology. • Spatially explicit evaluation of the predisposition of bark beetle infestation. • Participatory process to quantify expert and stakeholder perceptions. • BBN approach more efficient than fuzzy-AHP. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Environmental Modelling & Software is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.envsoft.2021.105233
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      – Code: eng
        Text: English
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      – SubjectFull: Bark beetles
        Type: general
      – SubjectFull: Analytic network process
        Type: general
      – SubjectFull: Ips typographus
        Type: general
      – SubjectFull: Analytic hierarchy process
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      – SubjectFull: Geographic information systems
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      – SubjectFull: Norway spruce
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      – TitleFull: Comparative study of fuzzy-AHP and BBN for spatially-explicit prediction of bark beetle predisposition.
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              M: 01
              Text: Jan2022
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              Y: 2022
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