Enhancing an unsupervised clustering algorithm with a spatial contiguity constraint for river habitat analysis.
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| Title: | Enhancing an unsupervised clustering algorithm with a spatial contiguity constraint for river habitat analysis. |
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| Authors: | Rooijen, Erik1 (AUTHOR) vanrooijen@vaw.baug.ethz.ch, Vanzo, Davide1 (AUTHOR), Vetsch, David F.1 (AUTHOR), Boes, Robert M.1 (AUTHOR), Siviglia, Annunziato2 (AUTHOR) |
| Source: | Ecohydrology. Jun2021, Vol. 14 Issue 4, p1-22. 22p. |
| Subject Terms: | *Habitats, Algorithms, Automatic identification, Hierarchical clustering (Cluster analysis) |
| Abstract: | The spread of two‐dimensional numerical hydrodynamic tools for ecohydraulic applications allowed for the development of automatic habitat detection methods, adopted as predicting tools for river habitat analysis. These automatic approaches differ for the employed identification rules, such as preference curves, fuzzy rules and clustering methods. Previous research has shown promising results in the automatic identification of mesoscale habitat patches by using clustering algorithms together with numerical hydrodynamic model results. These algorithms attempt to implement and simulate some of the expert‐based requirements adopted in the field to delineate habitat patches. Spatial contiguity is one of such expert‐based requirements that has not been enforced and exploited in automatic mesohabitat identification so far. In this work, we propose a novel tool (BASEmeso) based on an agglomerative hierarchical clustering algorithm where we enforced a spatial contiguity criteria. We compare our approach with a more established method without spatial constraints, considering a synthetic river reach where the composition of mesohabitat patches is known a priori, and on three experimental river reaches, to investigate the effects of different river morphologies. Our results show that when employing a contiguity constraint, a patch's extent is better captured, different patches can be distinguished better and the distribution of patch characteristics is smoother. This holds for all investigated morphologies. Together, it suggests that including a spatial contiguity constraint can improve the automatic delineation of river mesohabitat patches. The proposed methodology could positively contribute in the development of automatic, objective and predictive meso‐scale habitat assessment workflows. [ABSTRACT FROM AUTHOR] |
| Copyright of Ecohydrology is the property of Wiley-Blackwell 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.) | |
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| Header | DbId: 8gh DbLabel: GreenFILE An: 151047861 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Enhancing an unsupervised clustering algorithm with a spatial contiguity constraint for river habitat analysis. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Rooijen%2C+Erik%22">Rooijen, Erik</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> vanrooijen@vaw.baug.ethz.ch</i><br /><searchLink fieldCode="AR" term="%22Vanzo%2C+Davide%22">Vanzo, Davide</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Vetsch%2C+David+F%2E%22">Vetsch, David F.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Boes%2C+Robert+M%2E%22">Boes, Robert M.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Siviglia%2C+Annunziato%22">Siviglia, Annunziato</searchLink><relatesTo>2</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Ecohydrology%22">Ecohydrology</searchLink>. Jun2021, Vol. 14 Issue 4, p1-22. 22p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Habitats%22">Habitats</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Automatic+identification%22">Automatic identification</searchLink><br /><searchLink fieldCode="DE" term="%22Hierarchical+clustering+%28Cluster+analysis%29%22">Hierarchical clustering (Cluster analysis)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The spread of two‐dimensional numerical hydrodynamic tools for ecohydraulic applications allowed for the development of automatic habitat detection methods, adopted as predicting tools for river habitat analysis. These automatic approaches differ for the employed identification rules, such as preference curves, fuzzy rules and clustering methods. Previous research has shown promising results in the automatic identification of mesoscale habitat patches by using clustering algorithms together with numerical hydrodynamic model results. These algorithms attempt to implement and simulate some of the expert‐based requirements adopted in the field to delineate habitat patches. Spatial contiguity is one of such expert‐based requirements that has not been enforced and exploited in automatic mesohabitat identification so far. In this work, we propose a novel tool (BASEmeso) based on an agglomerative hierarchical clustering algorithm where we enforced a spatial contiguity criteria. We compare our approach with a more established method without spatial constraints, considering a synthetic river reach where the composition of mesohabitat patches is known a priori, and on three experimental river reaches, to investigate the effects of different river morphologies. Our results show that when employing a contiguity constraint, a patch's extent is better captured, different patches can be distinguished better and the distribution of patch characteristics is smoother. This holds for all investigated morphologies. Together, it suggests that including a spatial contiguity constraint can improve the automatic delineation of river mesohabitat patches. The proposed methodology could positively contribute in the development of automatic, objective and predictive meso‐scale habitat assessment workflows. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Ecohydrology is the property of Wiley-Blackwell 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: BibEntity: Identifiers: – Type: doi Value: 10.1002/eco.2285 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 22 StartPage: 1 Subjects: – SubjectFull: Habitats Type: general – SubjectFull: Algorithms Type: general – SubjectFull: Automatic identification Type: general – SubjectFull: Hierarchical clustering (Cluster analysis) Type: general Titles: – TitleFull: Enhancing an unsupervised clustering algorithm with a spatial contiguity constraint for river habitat analysis. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Rooijen, Erik – PersonEntity: Name: NameFull: Vanzo, Davide – PersonEntity: Name: NameFull: Vetsch, David F. – PersonEntity: Name: NameFull: Boes, Robert M. – PersonEntity: Name: NameFull: Siviglia, Annunziato IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2021 Type: published Y: 2021 Identifiers: – Type: issn-print Value: 19360584 Numbering: – Type: volume Value: 14 – Type: issue Value: 4 Titles: – TitleFull: Ecohydrology Type: main |
| ResultId | 1 |
