What to do in, and what to expect from, urban green spaces – Indicator-based approach to assess cultural ecosystem services

Krellenberg, Kerstin; Artmann, Martina; Stanley, Celina; Hecht, Robert

doi:10.1016/j.ufug.2021.126986

Cited by 38 publications

(20 citation statements)

References 82 publications

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“…Since the greenness and public accessibility were modeled separately, they can be seen as independent of each other. Therefore, the combination of these two frames of discernment was achieved by building the Cartesian product of them which yielded the new joint frame of discernment θ pg θ pg = θ p × θ g = {(green, public), (green, private), (grey, public), (grey, private)} (11) For the final fusion, the probability masses of the two models were converted to the new frame of discernment θ pg using m({(green, private), (green, public)}) = m({green}) (12) m({(grey, private), (grey, public)}) = m({grey}) (13) m({(green, public), (grey, public)}) = m({public})…”

Section: Fusion Of Greenness and Public Accessibilitymentioning

confidence: 99%

“…Recent studies even suggest that sufficient accessibility to nearby public green spaces is beneficial to the well-being and mental health of citizens [6][7][8][9] and urban nature is seen as resilient infrastructure in times of crisis, such as the COVID-19 pandemic [10]. Hence, it is very important to provide citizens and city planners with the necessary information about the location and qualities of public urban green spaces [11,12] to identify disparities and take them into account in future planning [13].…”

Section: Introductionmentioning

confidence: 99%

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Mapping Public Urban Green Spaces Based on OpenStreetMap and Sentinel-2 Imagery Using Belief Functions

Ludwig

Hecht

Lautenbach

et al. 2021

IJGI

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Public urban green spaces are important for the urban quality of life. Still, comprehensive open data sets on urban green spaces are not available for most cities. As open and globally available data sets, the potential of Sentinel-2 satellite imagery and OpenStreetMap (OSM) data for urban green space mapping is high but limited due to their respective uncertainties. Sentinel-2 imagery cannot distinguish public from private green spaces and its spatial resolution of 10 m fails to capture fine-grained urban structures, while in OSM green spaces are not mapped consistently and with the same level of completeness everywhere. To address these limitations, we propose to fuse these data sets under explicit consideration of their uncertainties. The Sentinel-2 derived Normalized Difference Vegetation Index was fused with OSM data using the Dempster–Shafer theory to enhance the detection of small vegetated areas. The distinction between public and private green spaces was achieved using a Bayesian hierarchical model and OSM data. The analysis was performed based on land use parcels derived from OSM data and tested for the city of Dresden, Germany. The overall accuracy of the final map of public urban green spaces was 95% and was mainly influenced by the uncertainty of the public accessibility model.

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Section: Fusion Of Greenness and Public Accessibilitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Mapping Public Urban Green Spaces Based on OpenStreetMap and Sentinel-2 Imagery Using Belief Functions

Ludwig

Hecht

Lautenbach

et al. 2021

IJGI

Self Cite

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show abstract

“…Regarding the experimental conclusions, this study focused on the ecosystem service value of trees under the low-carbon goal; the final conclusion also served this goal. However, the landscape and biodiversity of urban trees should also be carefully considered [59,60]. Although this study suggests the selection of high-value tree species, choosing only one or two species should be avoided.…”

Section: Limitations and Caveatsmentioning

confidence: 99%

Optimization of Ecosystem Services of Shanghai Urban–Suburban Street Trees Based on Low-Carbon Targets

et al. 2021

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Road traffic carbon emissions are an important cause of global warming, and street trees play an important role in regulating road carbon emissions. During urbanization, major differences in the planting management modes and growth status of the street trees in urban–suburban gradient may exist, leading to significant differences in the low-carbon values of the street trees in urban–suburban gradient. Based on this, this study took two typical urban–suburban gradient zones in Shanghai as an example to analyze the changes in the characteristics of street tree species, planting density, tree sizes, and low-carbon contribution with urban and rural changes, and proposed strategies for optimizing the low-carbon contribution of urban street trees. The results showed that, from the inner ring to the outer ring and the suburban ring, the proportion of London plane tree gradually changed from 82% to 11%, and the proportion of the camphor tree gradually changed from 9% to 70%; the average DBH of the trees gradually decreased from 28.81 to 23.74 cm. The number of plantings per unit road length gradually increased, and the number of plantings per unit area gradually decreased; therefore, the average low-carbon contribution of urban–suburban street trees is not significant, but the low-carbon contribution of upper street trees per unit area is higher, and suburban unit street trees have a higher low-carbon contribution. Finally, this article proposes different optimization strategies for future urban micro-renewal and suburban new-city construction.

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“…To better interpret the results of an SDSS, sensitivity analyses are used to examine the extent of output variation in a model when parameters are varied systematically over a certain range (Delgado and Sendra, 2004). Former studies on the assessment of urban green spaces using SDSS supported several research fields such as monitoring urban green spaces to aid local authorities for the enhancement of urban green spaces (Pelizaro et al, 2005), analyzing urban green spaces in terms of accessibility and quality to support sustainable urban planning (Stessens et al, 2017;Meng and Malczewski, 2015), and evaluating the suitability of sites for the further development of urban green spaces (Li et al, 2018). In this context, this paper presents a newly developed SDSS approach that allows the evaluation of urban green spaces in terms of their suitability upon a range of recreational activities.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity analysis in multi-criteria evaluation of the suitability of urban green spaces for recreational activities

Cakir

Hecht

Krellenberg

2021

AGILE GIScience Ser.

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Abstract. Urban green spaces can have potential positive impacts on climate, biodiversity, health, and generally on the quality of life for urban residents and are of great importance for pursuing recreational activities. People as urban green space users should therefore be well informed about where they are located within a city and what activities they are suitable for. As people’s individual preferences play a significant role in the decision-making process for visiting urban green spaces, we present a method that enables to assess urban green spaces upon various activities in accordance with a range of criteria. A sensitivity analysis to investigate the influence of weighting the criteria in a multi-criteria evaluation of the suitability of urban green spaces for recreational activities depending on people’s preferences is in the focus. Initial results are shown based on an exemplary use case of playing Frisbee. Overall, the study is embedded in the development of a spatial decision support system implemented in the form of a web app to assist urban residents make decisions in the context of green space use.

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What to do in, and what to expect from, urban green spaces – Indicator-based approach to assess cultural ecosystem services

Cited by 38 publications

References 82 publications

Mapping Public Urban Green Spaces Based on OpenStreetMap and Sentinel-2 Imagery Using Belief Functions

Mapping Public Urban Green Spaces Based on OpenStreetMap and Sentinel-2 Imagery Using Belief Functions

Optimization of Ecosystem Services of Shanghai Urban–Suburban Street Trees Based on Low-Carbon Targets

Sensitivity analysis in multi-criteria evaluation of the suitability of urban green spaces for recreational activities

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