A geospatial model of nature-based recreation for urban planning: Case study of Paris, France

Liu, Hongxiao; Hamel, Perrine; Tardieu, Léa; Remme, Roy P.; Han, Baolong; Ren, Hai

doi:10.1016/j.landusepol.2022.106107

Cited by 19 publications

(15 citation statements)

References 69 publications

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“…The default mode of the R model was adopted in this study. The equations are shown below (Liu et al, 2022):

G_{i} = \frac{S_{i}}{\sum_{k \in [d_{italicki} \leq d_{0}]} P_{k \times f (d_{ki})}}

where G i is the UGS‐to‐population ratio of UGS pixel i ; i refers to the count of UGS pixels; S i is the UGS area in pixel i ; p k is the population in pixel i ; d ki is the Euclidean distance between pixels k and i ; d 0 is the search radius; and f (d ki ) is the decay function describing the decline in service against distance. The default decay function in the R model was applied in this study.

R_{j} = \sum_{i \in \{d_{italicij} \leq d_{0}\}} R_{i} * f (d_{ij})

where R j is the UGS per capita supplied to pixel j ; j is any pixel in the study area; R i is the UGS‐population ratio of UGS pixel i ; d ij is the Euclidean distance between pixels i and j ; and d 0 is the search radius.…”

Section: Methodsmentioning

confidence: 99%

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A spatially explicit framework for assessing ecosystem service supply risk under multiple land‐use scenarios in the Xi'an Metropolitan Area of China

Peng,

Zhang,

et al. 2024

Land Degrad Dev

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Rapid global urbanization has perturbed ecosystem structures and functions, resulting in ecological risk and threatening sustainable human well‐being and socioeconomic development. However, scientific indicators to analyze ecosystem service (ES) risk patterns need to be explored in detail. In addition, studies on ES supply risk are stagnating on historical or status explorations, especially from the view of disturbance from land‐use changes. This study seeks to develop a framework for modeling past‐future ES supply risk pattern evaluation and probing into ES risk patterns under different future land‐use scenarios. To achieve this objective, the framework integrates the Future Land Use Simulation (FLUS) model, the Intelligent Urban Ecosystem Management System (IUEMS) model, and an established indicator system incorporating ES supply trend, hotspots and coldspots, and ES trade‐offs, and synergies. The results show that: (1) In 2050, the supply of climate regulation in the Xi'an Metropolitan Area (XMA) will increase, while that of carbon sequestration and recreation will decrease. In 2050, the supply of climate regulation is the highest under ecological protection (EP) scenario, while the supply of carbon sequestration and recreation are the highest under cropland protection (CP) scenario. (2) From 2000 to 2050, the hotspots and coldspots of climate regulation increase in both natural development (ND) scenario and CP scenario. Notably, CP scenario experiences the most significant reduction in extremely significant hotspots and coldspots of carbon sequestration. From 2000 to 2050, at the regional and pixel scales, climate regulation and carbon sequestration mainly show trade‐offs, and carbon sequestration and recreation show synergies. (3) ES supply risk in XMA is high in the center and low in the north and south. The ES supply risk from 2000 to 2050 is increasing, with expanding “extremely high risk”, “high risk”, and “extremely safe” areas. ES supply risk management should adhere to more strict land‐use policies and guidelines, management zoning for areas with different levels of ES risk, and an accurate understanding of ES trade‐offs and synergies for scientific risk management. This study could provide theoretical and technical references for ES risk assessment research and promote scientific ecological risk management.

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“…The default mode of the R model was adopted in this study. The equations are shown below (Liu et al, 2022):

G_{i} = \frac{S_{i}}{\sum_{k \in [d_{italicki} \leq d_{0}]} P_{k \times f (d_{ki})}}

R_{j} = \sum_{i \in \{d_{italicij} \leq d_{0}\}} R_{i} * f (d_{ij})

Section: Methodsmentioning

confidence: 99%

“…The default mode of the R model was adopted in this study. The equations are shown below (Liu et al, 2022):…”

Section: Recreationmentioning

confidence: 99%

A spatially explicit framework for assessing ecosystem service supply risk under multiple land‐use scenarios in the Xi'an Metropolitan Area of China

Peng,

Zhang,

et al. 2024

Land Degrad Dev

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“…Some studies have explored the impact of urbanization on the expansion of urban land 2,13 or the availability of green infrastructure 14,15 . Studies have also shown the negative impact of urban growth and urban densification on biodiversity and the provisioning of ecosystem services [16][17][18] . Investigations into the implementation of green infrastructure strategies have revealed their potential to improve ecosystem service provisioning, while also highlighting the synergies and trade-offs among these services 4,19 .…”

Section: Introductionmentioning

confidence: 99%

Optimizing green and grey infrastructure planning for sustainable urban development

Oorschot,

Remme,

Slootweg

et al. 2024

Preprint

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The anticipated surge in urban populations, an additional 2.5 billion people until 2050, presents environmental challenges affecting both local ecosystems and the global environment. While various studies explore these impacts individually, integrated approaches are scarce. This study introduces a spatially explicit model to assess the impact of urbanization on both ecosystem services provisioning (green infrastructure availability, cooling, stormwater retention), and the global environmental impact associated with building construction (primary material demand, greenhouse gas emissions, land use). Applied to the Netherlands from 2018 to 2050, our results reveal that despite a growing building stock, integrating green infrastructure development with building construction could expand green areas by up to 5%, resulting in stabilization or an increase in ecosystem service provision. We found that the preference for dense or sparse urbanization depends on the sustainability aspect under study and the scale and scope of analysis. The findings improve our understanding of the environmental consequences of urbanization, guiding sustainable urban planning practices.

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“…In the past, traditional urban green space design was carried out by landscape architects during on-site surveys, and the design was completed in combination with the needs of society or of the property owners. Presently, common urban green space design methods mainly include the following: using virtual reality (VR) technology to obtain user and expert opinions for the design of green business parks (GBPs) [ 1 ]; urban green space design that responds to human needs for recreation, amenities, and environmental quality [ 2 , 3 , 4 , 5 ]; the optimal planning of an urban greening system for high-density cities in response to the urban microenvironment based on a genetic algorithm [ 6 ]; a method for planning urban green spaces that combines natural solutions and GIS tools [ 7 ]; medicinal landscape design based on the theory of the five senses [ 8 ]; and urban green space design methods based on disease prevention or suppression [ 9 , 10 , 11 , 12 , 13 , 14 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

Intelligent Generation Method and Sustainable Application of Road Systems in Urban Green Spaces: Taking Jiangnan Gardens as an Example

Yan

Chen

Zheng

et al. 2023

IJERPH

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This paper takes the garden road system as the research object and proposes a method of generating paths for classical gardens based on parametric design. Firstly, by studying the distribution characteristics of roads, the data on the curvature, angle, and view area of roads were collected. Secondly, the obtained data were transferred to the parameterized platform, and a method of intelligent generation was used for calculation. Finally, the road system was optimized by the genetic algorithm for better application in modern landscape design. According to the current situation, the road system plan generated by the algorithm inherits the characteristics of classical garden roads. This method can be applied to the courtyard, the community park, the urban park, and other objects. This research not only identifies the characteristics of landscape cultural heritage, but also produces an innovative, intelligent design tool. It provides new methods for the parameterized inheritance and application of traditional landscape heritage.

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A geospatial model of nature-based recreation for urban planning: Case study of Paris, France

Cited by 19 publications

References 69 publications

A spatially explicit framework for assessing ecosystem service supply risk under multiple land‐use scenarios in the Xi'an Metropolitan Area of China

A spatially explicit framework for assessing ecosystem service supply risk under multiple land‐use scenarios in the Xi'an Metropolitan Area of China

Optimizing green and grey infrastructure planning for sustainable urban development

Intelligent Generation Method and Sustainable Application of Road Systems in Urban Green Spaces: Taking Jiangnan Gardens as an Example

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