25
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      The provision of urban green space and its accessibility: Spatial data effects in Brussels

      research-article
      1 , 2 , * , 3 , 3 , 4
      PLoS ONE
      Public Library of Science

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Urban green space (UGS) has many environmental and social benefits. UGS provision and access are increasingly considered in urban policies and must rely on data and indicators that can capture variations in the distribution of UGS within cities. There is no consensus about how UGS, and their provision and access, must be defined from different land use data types. Here we identify four spatial dimensions of UGS and critically examine how different data sources affect these dimensions and our understanding of their variation within a city region (Brussels). We compare UGS indicators measured from an imagery source (NDVI from Landsat), an official cadastre-based map, and the voluntary geographical information provided by OpenStreetMap (OSM). We compare aggregate values of provision and access to UGS as well as their spatial distribution along a centrality gradient and at neighbourhood scale. We find that there are strong differences in the value of indicators when using the different datasets, especially due to their ability to capture private and public green space. However we find that the interpretation of intra-urban spatial variations is not affected by changes in data source. Centrality in particular is a strong determinant of the relative values of UGS availability, fragmentation and accessibility, irrespective of datasets.

          Related collections

          Most cited references37

          • Record: found
          • Abstract: found
          • Article: not found

          Increasing walking: how important is distance to, attractiveness, and size of public open space?

          Well-designed public open space (POS) that encourages physical activity is a community asset that could potentially contribute to the health of local residents. In 1995-1996, two studies were conducted-an environmental audit of POS over 2 acres (n =516) within a 408-km2 area of metropolitan Perth, Western Australia; and personal interviews with 1803 adults (aged 18 to 59 years) (52.9% response rate). The association between access to POS and physical activity was examined using three accessibility models that progressively adjusted for distance to POS, and its attractiveness and size. In 2002, an observational study examined the influence of attractiveness on the use of POS by observing users of three pairs of high- and low-quality (based on attractiveness) POS matched for size and location. Overall, 28.8% of respondents reported using POS for physical activity. The likelihood of using POS increased with increasing levels of access, but the effect was greater in the model that adjusted for distance, attractiveness, and size. After adjustment, those with very good access to large, attractive POS were 50% more likely to achieve high levels of walking (odds ratio, 1.50; 95% confidence level, 1.06-2.13). The observational study showed that after matching POS for size and location, 70% of POS users observed visited attractive POS. Access to attractive, large POS is associated with higher levels of walking. To increase walking, thoughtful design (and redesign) of POS is required that creates large, attractive POS with facilities that encourage active use by multiple users (e.g., walkers, sports participants, picnickers).
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Association of park size, distance, and features with physical activity in neighborhood parks.

            We studied whether park size, number of features in the park, and distance to a park from participants' homes were related to a park being used for physical activity. We collected observational data on 28 specific features from 33 parks. Adult residents in surrounding areas (n=380) completed 7-day physical activity logs that included the location of their activities. We used logistic regression to examine the relative importance of park size, features, and distance to participants' homes in predicting whether a park was used for physical activity, with control for perceived neighborhood safety and aesthetics. Parks with more features were more likely to be used for physical activity; size and distance were not significant predictors. Park facilities were more important than were park amenities. Of the park facilities, trails had the strongest relationship with park use for physical activity. Specific park features may have significant implications for park-based physical activity. Future research should explore these factors in diverse neighborhoods and diverse parks among both younger and older populations.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Racial/ethnic and socioeconomic disparities in urban green space accessibility: Where to intervene?

              Dajun Dai (2011)
                Bookmark

                Author and article information

                Contributors
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: SupervisionRole: ValidationRole: Writing – original draft
                Role: Data curationRole: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: Funding acquisitionRole: Project administrationRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2018
                17 October 2018
                : 13
                : 10
                : e0204684
                Affiliations
                [1 ] UMR CNRS 6266 IDEES, Mont-Saint-Aignan, France
                [2 ] University Rouen Normandie, Department of Geography, Mont-Saint-Aignan, France
                [3 ] Institute of Geography and Spatial Planning, University of Luxembourg, Esch-sur-Alzette, Luxembourg
                [4 ] Luxembourg Institute of Socio-Economic Research, Esch-sur-Alzette, Luxembourg
                University College London, UNITED KINGDOM
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0003-3762-1874
                Article
                PONE-D-18-08495
                10.1371/journal.pone.0204684
                6192568
                30332449
                93195289-6926-4ebc-9799-512c180ab675
                © 2018 Le Texier et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 27 March 2018
                : 11 September 2018
                Page count
                Figures: 7, Tables: 0, Pages: 17
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100008665, Université du Luxembourg;
                Award ID: Tandem Project - ”Spatial Optima and the Social Benefits of Urban Green Space”
                Award Recipient :
                This work was supported by Tandem Project - “Spatial Optima and the Social Benefits of Urban Green Space,” Principal Investigator: G. Caruso, P. Picard, Funding: Université du Luxembourg, Duration: 2015-2018.
                Categories
                Research Article
                Computer and Information Sciences
                Network Analysis
                Centrality
                Engineering and Technology
                Management Engineering
                Privatization
                Earth Sciences
                Geography
                Geographic Areas
                Urban Areas
                Earth Sciences
                Geography
                Human Geography
                Land Use
                Social Sciences
                Human Geography
                Land Use
                Ecology and Environmental Sciences
                Terrestrial Environments
                Urban Environments
                Computer and Information Sciences
                Geoinformatics
                Earth Sciences
                Geography
                Geoinformatics
                Earth Sciences
                Geography
                Human Geography
                Urban Geography
                Social Sciences
                Human Geography
                Urban Geography
                Biology and Life Sciences
                Psychology
                Behavior
                Recreation
                Social Sciences
                Psychology
                Behavior
                Recreation
                Custom metadata
                The data underlying this study are third party. The Landsat 8 satellite image covering the Brussels region was downloaded from the Landsat Viewer website (courtesy of the United States Geological Survey - http://lv.eosda.com/). Vector shapefiles from the UrbIS Map and UrbIS Admin datasets were downloaded from the BRIC website ( http://bric.brussels/en/our-solutions/urbis-solutions/urbis-data). Vector data from Open Street Map ( http://openstreetmap.org) was extracted using the QuickOSM plugin in QGIS. For the spatial heterogeneity lens, infra-urban neighbourhoods were defined using 145 statistical entities (so-called "quartiers") built by a regional statistical body ("Monitoring des Quartiers de la Région de Bruxelles-Capitale", see https://monitoringdesquartiers.brussels/). The authors did not have special access privileges.

                Uncategorized
                Uncategorized

                Comments

                Comment on this article