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

Incorporating nature-based recreation into urban planning analyses requires understanding the accessibility, quality, and demand for urban greenspace (UGS) across a city. Here, we present a novel tool that lowers the barriers to such information by (i) providing a spatially-explicit assessment of re...

Full description

Saved in:
Bibliographic Details
Main Authors: Liu, Hongxiao, Hamel, Perrine, Tardieu, Léa, Remme, Roy P., Han, Baolong, Ren, Hai
Other Authors: Asian School of the Environment
Format: Article
Language:English
Published: 2022
Subjects:
Online Access:https://hdl.handle.net/10356/156897
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-156897
record_format dspace
spelling sg-ntu-dr.10356-1568972023-02-28T16:41:02Z 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 Asian School of the Environment Social sciences::Geography::Environmental sciences Recreation Ecosystem Services Model Incorporating nature-based recreation into urban planning analyses requires understanding the accessibility, quality, and demand for urban greenspace (UGS) across a city. Here, we present a novel tool that lowers the barriers to such information by (i) providing a spatially-explicit assessment of recreational UGS supply and demand; (ii) differentiating results by population group or UGS type; and (iii) using an accessible open-source software platform that facilitates scenario comparison and communication. In a case study in Paris, France, we demonstrate how the tool helps address important urban planning questions. We show that between 42% and 55% of the population is currently below the UGS target of 10 m2 per person, depending on the accessibility criteria used. Using revealed preference data, we demonstrate that older adults are disproportionately affected by the UGS deficit. Our assessment of future scenarios reveals that UGS targets set by public policies are largely insufficient (500–2800 ha are planned by 2030, while more than 4000 ha are needed to meet the policy target). By combining the strengths of established geospatial methods, the tool helps researchers and practitioners produce a more nuanced analysis of the recreation benefits of UGS implementation. National Research Foundation (NRF) Submitted/Accepted version PH acknowledges the Singapore National Research Foundation, Prime Minister's Office (NRF-NRFF12-2020-000) 2022-05-05T00:23:56Z 2022-05-05T00:23:56Z 2022 Journal Article Liu, H., Hamel, P., Tardieu, L., Remme, R. P., Han, B. & Ren, H. (2022). A geospatial model of nature-based recreation for urban planning: case study of Paris, France. Land Use Policy, 117, 106107-. https://dx.doi.org/10.1016/j.landusepol.2022.106107 0264-8377 https://hdl.handle.net/10356/156897 10.1016/j.landusepol.2022.106107 2-s2.0-85127330027 117 106107 en NRF-NRFF12-2020-0009 Land Use Policy © 2022 Elsevier Ltd. All rights reserved. This paper was published in Land Use Policy and is made available with permission of Elsevier Ltd. application/pdf application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Social sciences::Geography::Environmental sciences
Recreation
Ecosystem Services
Model
spellingShingle Social sciences::Geography::Environmental sciences
Recreation
Ecosystem Services
Model
Liu, Hongxiao
Hamel, Perrine
Tardieu, Léa
Remme, Roy P.
Han, Baolong
Ren, Hai
A geospatial model of nature-based recreation for urban planning: case study of Paris, France
description Incorporating nature-based recreation into urban planning analyses requires understanding the accessibility, quality, and demand for urban greenspace (UGS) across a city. Here, we present a novel tool that lowers the barriers to such information by (i) providing a spatially-explicit assessment of recreational UGS supply and demand; (ii) differentiating results by population group or UGS type; and (iii) using an accessible open-source software platform that facilitates scenario comparison and communication. In a case study in Paris, France, we demonstrate how the tool helps address important urban planning questions. We show that between 42% and 55% of the population is currently below the UGS target of 10 m2 per person, depending on the accessibility criteria used. Using revealed preference data, we demonstrate that older adults are disproportionately affected by the UGS deficit. Our assessment of future scenarios reveals that UGS targets set by public policies are largely insufficient (500–2800 ha are planned by 2030, while more than 4000 ha are needed to meet the policy target). By combining the strengths of established geospatial methods, the tool helps researchers and practitioners produce a more nuanced analysis of the recreation benefits of UGS implementation.
author2 Asian School of the Environment
author_facet Asian School of the Environment
Liu, Hongxiao
Hamel, Perrine
Tardieu, Léa
Remme, Roy P.
Han, Baolong
Ren, Hai
format Article
author Liu, Hongxiao
Hamel, Perrine
Tardieu, Léa
Remme, Roy P.
Han, Baolong
Ren, Hai
author_sort Liu, Hongxiao
title A geospatial model of nature-based recreation for urban planning: case study of Paris, France
title_short A geospatial model of nature-based recreation for urban planning: case study of Paris, France
title_full A geospatial model of nature-based recreation for urban planning: case study of Paris, France
title_fullStr A geospatial model of nature-based recreation for urban planning: case study of Paris, France
title_full_unstemmed A geospatial model of nature-based recreation for urban planning: case study of Paris, France
title_sort geospatial model of nature-based recreation for urban planning: case study of paris, france
publishDate 2022
url https://hdl.handle.net/10356/156897
_version_ 1759855749946671104