A multiple scale, function, and type approach to determine and improve Green Infrastructure of urban watersheds

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Autoren

  • Nils Arthur
  • Jochen Hack

Externe Organisationen

  • Technische Universität Darmstadt
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Aufsatznummer127459
FachzeitschriftUrban Forestry & Urban Greening
Jahrgang68
Frühes Online-Datum5 Jan. 2022
PublikationsstatusVeröffentlicht - Feb. 2022
Extern publiziertJa

Abstract

Green Infrastructure (GI) connects different types of green features via various scales, thereby supporting urban biodiversity and service provision. This study presents a methodology capable of identifying multiple functions to assess GI in less-developed countries, where such methodologies are lacking. GI was assessed based on a high-resolution land use classification using both landscape metrics and spatial data within an urbanized region of San José, Costa Rica, at different scales (watershed, neighbourhood, object). Results showed highly fragmented green spaces (often <10 ha), typically unable to support high levels of biodiversity, along with a low amount of green space per inhabitant (<7.4 m²) within the watershed. Substantially higher tree cover (x6) and tree density (x5) were found in the greenest neighbourhood in comparison to the least green neighbourhood. Potential areas for new GI in the form of green roofs (4.03 ha), permeable pavement (27.3), and potential retention areas (85.3) were determined. Several green spaces (n = 11) were identified as promising GI sites with the potential to increase provision (18.6 m²/inhabitant). The adopted methodology demonstrates the potential of GI for increasing recreational green space access, runoff reduction, and flood retentions while supporting biodiversity, validating its utility in guiding decision-making and policy generation.

ASJC Scopus Sachgebiete

Zitieren

A multiple scale, function, and type approach to determine and improve Green Infrastructure of urban watersheds. / Arthur, Nils; Hack, Jochen.
in: Urban Forestry & Urban Greening, Jahrgang 68, 127459, 02.2022.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Download
@article{2f92bb17135d4d36b72b963dd9eb2b7b,
title = "A multiple scale, function, and type approach to determine and improve Green Infrastructure of urban watersheds",
abstract = "Green Infrastructure (GI) connects different types of green features via various scales, thereby supporting urban biodiversity and service provision. This study presents a methodology capable of identifying multiple functions to assess GI in less-developed countries, where such methodologies are lacking. GI was assessed based on a high-resolution land use classification using both landscape metrics and spatial data within an urbanized region of San Jos{\'e}, Costa Rica, at different scales (watershed, neighbourhood, object). Results showed highly fragmented green spaces (often <10 ha), typically unable to support high levels of biodiversity, along with a low amount of green space per inhabitant (<7.4 m²) within the watershed. Substantially higher tree cover (x6) and tree density (x5) were found in the greenest neighbourhood in comparison to the least green neighbourhood. Potential areas for new GI in the form of green roofs (4.03 ha), permeable pavement (27.3), and potential retention areas (85.3) were determined. Several green spaces (n = 11) were identified as promising GI sites with the potential to increase provision (18.6 m²/inhabitant). The adopted methodology demonstrates the potential of GI for increasing recreational green space access, runoff reduction, and flood retentions while supporting biodiversity, validating its utility in guiding decision-making and policy generation.",
keywords = "Green infrastructure, Nature-based solutions, Costa Rica, Urban ecology and landscape architecture, SEE-URBAN-WATER, FRAGSTATS, Urban ecology, Spatial analysis, Green Infrastructure, Landscape metrics",
author = "Nils Arthur and Jochen Hack",
note = "Funding Information: We acknowledge the funding that we received from the German Federal Ministry of Research and Education (Grant ID: 01UU1704 ).",
year = "2022",
month = feb,
doi = "10.1016/j.ufug.2022.127459",
language = "English",
volume = "68",
journal = "Urban Forestry & Urban Greening",
issn = "1610-8167",
publisher = "Urban und Fischer Verlag GmbH und Co. KG",

}

Download

TY - JOUR

T1 - A multiple scale, function, and type approach to determine and improve Green Infrastructure of urban watersheds

AU - Arthur, Nils

AU - Hack, Jochen

N1 - Funding Information: We acknowledge the funding that we received from the German Federal Ministry of Research and Education (Grant ID: 01UU1704 ).

PY - 2022/2

Y1 - 2022/2

N2 - Green Infrastructure (GI) connects different types of green features via various scales, thereby supporting urban biodiversity and service provision. This study presents a methodology capable of identifying multiple functions to assess GI in less-developed countries, where such methodologies are lacking. GI was assessed based on a high-resolution land use classification using both landscape metrics and spatial data within an urbanized region of San José, Costa Rica, at different scales (watershed, neighbourhood, object). Results showed highly fragmented green spaces (often <10 ha), typically unable to support high levels of biodiversity, along with a low amount of green space per inhabitant (<7.4 m²) within the watershed. Substantially higher tree cover (x6) and tree density (x5) were found in the greenest neighbourhood in comparison to the least green neighbourhood. Potential areas for new GI in the form of green roofs (4.03 ha), permeable pavement (27.3), and potential retention areas (85.3) were determined. Several green spaces (n = 11) were identified as promising GI sites with the potential to increase provision (18.6 m²/inhabitant). The adopted methodology demonstrates the potential of GI for increasing recreational green space access, runoff reduction, and flood retentions while supporting biodiversity, validating its utility in guiding decision-making and policy generation.

AB - Green Infrastructure (GI) connects different types of green features via various scales, thereby supporting urban biodiversity and service provision. This study presents a methodology capable of identifying multiple functions to assess GI in less-developed countries, where such methodologies are lacking. GI was assessed based on a high-resolution land use classification using both landscape metrics and spatial data within an urbanized region of San José, Costa Rica, at different scales (watershed, neighbourhood, object). Results showed highly fragmented green spaces (often <10 ha), typically unable to support high levels of biodiversity, along with a low amount of green space per inhabitant (<7.4 m²) within the watershed. Substantially higher tree cover (x6) and tree density (x5) were found in the greenest neighbourhood in comparison to the least green neighbourhood. Potential areas for new GI in the form of green roofs (4.03 ha), permeable pavement (27.3), and potential retention areas (85.3) were determined. Several green spaces (n = 11) were identified as promising GI sites with the potential to increase provision (18.6 m²/inhabitant). The adopted methodology demonstrates the potential of GI for increasing recreational green space access, runoff reduction, and flood retentions while supporting biodiversity, validating its utility in guiding decision-making and policy generation.

KW - Green infrastructure

KW - Nature-based solutions

KW - Costa Rica

KW - Urban ecology and landscape architecture

KW - SEE-URBAN-WATER

KW - FRAGSTATS

KW - Urban ecology

KW - Spatial analysis

KW - Green Infrastructure

KW - Landscape metrics

UR - http://www.scopus.com/inward/record.url?scp=85122300168&partnerID=8YFLogxK

U2 - 10.1016/j.ufug.2022.127459

DO - 10.1016/j.ufug.2022.127459

M3 - Article

VL - 68

JO - Urban Forestry & Urban Greening

JF - Urban Forestry & Urban Greening

SN - 1610-8167

M1 - 127459

ER -