A multiple scale, function, and type approach to determine and improve Green Infrastructure of urban watersheds Article Swipe
Nils Arthur
,
Jochen Hack
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1016/j.ufug.2022.127459
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1016/j.ufug.2022.127459
Related Topics
Concepts
Green infrastructure
Neighbourhood (mathematics)
Watershed
Recreation
Biodiversity
Geography
Land use
Ecosystem services
Environmental resource management
Land cover
Environmental science
Computer science
Ecology
Ecosystem
Mathematics
Civil engineering
Engineering
Biology
Mathematical analysis
Machine learning
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.ufug.2022.127459
- OA Status
- hybrid
- Cited By
- 31
- References
- 54
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4206371149
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4206371149Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.ufug.2022.127459Digital Object Identifier
- Title
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A multiple scale, function, and type approach to determine and improve Green Infrastructure of urban watershedsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-01-05Full publication date if available
- Authors
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Nils Arthur, Jochen HackList of authors in order
- Landing page
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https://doi.org/10.1016/j.ufug.2022.127459Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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hybridOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1016/j.ufug.2022.127459Direct OA link when available
- Concepts
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Green infrastructure, Neighbourhood (mathematics), Watershed, Recreation, Biodiversity, Geography, Land use, Ecosystem services, Environmental resource management, Land cover, Environmental science, Computer science, Ecology, Ecosystem, Mathematics, Civil engineering, Engineering, Biology, Mathematical analysis, Machine learningTop concepts (fields/topics) attached by OpenAlex
- Cited by
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31Total citation count in OpenAlex
- Citations by year (recent)
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2025: 5, 2024: 12, 2023: 9, 2022: 5Per-year citation counts (last 5 years)
- References (count)
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54Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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