Qualifying the urban structure type approach for urban green space analysis – A case study of Dresden, Germany

Urban greenery affects the quality of life of local residents through a wide range of ecosystem services, determined not only by the quantity of green space but also by its type and structure (height and density). To ensure that all residents benefit equally from ecosystem services, planning procedu...

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Main Authors: Juliane Mathey, Jörg Hennersdorf, Iris Lehmann, Wolfgang Wende
Format: Article
Language:English
Published: Elsevier 2021-06-01
Series:Ecological Indicators
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1470160X21001849
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author Juliane Mathey
Jörg Hennersdorf
Iris Lehmann
Wolfgang Wende
author_facet Juliane Mathey
Jörg Hennersdorf
Iris Lehmann
Wolfgang Wende
author_sort Juliane Mathey
collection DOAJ
description Urban greenery affects the quality of life of local residents through a wide range of ecosystem services, determined not only by the quantity of green space but also by its type and structure (height and density). To ensure that all residents benefit equally from ecosystem services, planning procedures should aim for an optimal quality and structure of urban green system.Basic indicators are needed to help planners set targets for the development of green space and to analyse the state of urban greenery as a whole as well as in individual districts.Unfortunately, only a few cities regularly produce digital maps of their diverse urban biotope types, which provide detailed information on urban greenery forming the basis for the analytical method of urban vegetation structure types (UVSTs) proposed by Lehmann et al. (2014) derived from the case study Dresden (Germany). While maps of urban structure types (USTs) are available for most German cities, these have insufficient detail to assess the provision of urban greenery.We describe a method by which information from the UVSTs such as vegetation layers, green volumes and proportions of green space can be applied to USTs to estimate the provision and quality of green space per capita in individual urban districts.Taking the city of Dresden (Germany) as a case study, we analysed USTs in regard to their vegetation (proportion and volume), revealing basic problems in relation to the USTs (types of the current “extended block map” EBM). The basis for analysis is the UVST approach, which provides a typology for the investigation of diverse urban ecosystem services and to assess the ecological quality of urban structures.By linking detailed information from UVSTs to less detailed USTs our approach enables the monitoring and assessment of indicators and so can be used to answer, relatively quickly, questions on the fulfilment of green standards (e.g. green space share per inhabitant, green volume per inhabitant). Population data, available for urban blocks, can be linked to planning relevant knowledge on the green system. Furthermore, tables with detailed information on green provision for urban blocks can be a basis for drawing up scenarios on how planning can affect urban greenery.For example, results for Dresden, approved by the local planning authorities, are maps showing potentials and deficits in the provision of urban vegetation for the whole city, from which requirements for action can be derived for individual city districts.
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spelling doaj.art-fbe2e61fa23d43e3aca5ec8c01cb5eac2022-12-21T19:16:18ZengElsevierEcological Indicators1470-160X2021-06-01125107519Qualifying the urban structure type approach for urban green space analysis – A case study of Dresden, GermanyJuliane Mathey0Jörg Hennersdorf1Iris Lehmann2Wolfgang Wende3Corresponding author.; Leibniz Institute of Ecological Urban and Regional Development, Weberplatz 1, D-01217 Dresden, GermanyLeibniz Institute of Ecological Urban and Regional Development, Weberplatz 1, D-01217 Dresden, GermanyLeibniz Institute of Ecological Urban and Regional Development, Weberplatz 1, D-01217 Dresden, GermanyLeibniz Institute of Ecological Urban and Regional Development, Weberplatz 1, D-01217 Dresden, GermanyUrban greenery affects the quality of life of local residents through a wide range of ecosystem services, determined not only by the quantity of green space but also by its type and structure (height and density). To ensure that all residents benefit equally from ecosystem services, planning procedures should aim for an optimal quality and structure of urban green system.Basic indicators are needed to help planners set targets for the development of green space and to analyse the state of urban greenery as a whole as well as in individual districts.Unfortunately, only a few cities regularly produce digital maps of their diverse urban biotope types, which provide detailed information on urban greenery forming the basis for the analytical method of urban vegetation structure types (UVSTs) proposed by Lehmann et al. (2014) derived from the case study Dresden (Germany). While maps of urban structure types (USTs) are available for most German cities, these have insufficient detail to assess the provision of urban greenery.We describe a method by which information from the UVSTs such as vegetation layers, green volumes and proportions of green space can be applied to USTs to estimate the provision and quality of green space per capita in individual urban districts.Taking the city of Dresden (Germany) as a case study, we analysed USTs in regard to their vegetation (proportion and volume), revealing basic problems in relation to the USTs (types of the current “extended block map” EBM). The basis for analysis is the UVST approach, which provides a typology for the investigation of diverse urban ecosystem services and to assess the ecological quality of urban structures.By linking detailed information from UVSTs to less detailed USTs our approach enables the monitoring and assessment of indicators and so can be used to answer, relatively quickly, questions on the fulfilment of green standards (e.g. green space share per inhabitant, green volume per inhabitant). Population data, available for urban blocks, can be linked to planning relevant knowledge on the green system. Furthermore, tables with detailed information on green provision for urban blocks can be a basis for drawing up scenarios on how planning can affect urban greenery.For example, results for Dresden, approved by the local planning authorities, are maps showing potentials and deficits in the provision of urban vegetation for the whole city, from which requirements for action can be derived for individual city districts.http://www.sciencedirect.com/science/article/pii/S1470160X21001849Urban green space analysisUrban green space mappingUrban green volumeUrban green provisionTyping urban structuresUrban vegetation structure type (UVST)
spellingShingle Juliane Mathey
Jörg Hennersdorf
Iris Lehmann
Wolfgang Wende
Qualifying the urban structure type approach for urban green space analysis – A case study of Dresden, Germany
Ecological Indicators
Urban green space analysis
Urban green space mapping
Urban green volume
Urban green provision
Typing urban structures
Urban vegetation structure type (UVST)
title Qualifying the urban structure type approach for urban green space analysis – A case study of Dresden, Germany
title_full Qualifying the urban structure type approach for urban green space analysis – A case study of Dresden, Germany
title_fullStr Qualifying the urban structure type approach for urban green space analysis – A case study of Dresden, Germany
title_full_unstemmed Qualifying the urban structure type approach for urban green space analysis – A case study of Dresden, Germany
title_short Qualifying the urban structure type approach for urban green space analysis – A case study of Dresden, Germany
title_sort qualifying the urban structure type approach for urban green space analysis a case study of dresden germany
topic Urban green space analysis
Urban green space mapping
Urban green volume
Urban green provision
Typing urban structures
Urban vegetation structure type (UVST)
url http://www.sciencedirect.com/science/article/pii/S1470160X21001849
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