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. 2023 Aug 10;18(8):e0288515.
doi: 10.1371/journal.pone.0288515. eCollection 2023.

Spatial data collection and qualification methods for urban parks in Brazilian capitals: An innovative roadmap

Anne Dorothée Slovic  1 , Claudio Kanai  2 , Denise Marques Sales  3 , Solimar Carnavalli Rocha  3 , Amanda Cristina de Souza Andrade  4 , Lucas Soriano Martins  2 , Débora Morais Coelho  3 , Anderson Freitas  5 , Mika Moran  6 , Maria Antonietta Mascolli  2 , Waleska Teixeira Caiaffa  3 , Nelson Gouveia  2
Affiliations

Spatial data collection and qualification methods for urban parks in Brazilian capitals: An innovative roadmap

Anne Dorothée Slovic et al. PLoS One. .

Abstract

Urban parks have been studied for their effects on health and the environment. Accessing park data from reliable and comparable sources remains challenging, reinforcing the importance of standardized search tools, notably in Latin America. We designed a systematized methodology to identify processes of accessing, collecting, verifying, and harmonizing urban park spatial data in all Brazilian capitals included in the Urban Health in Latin America (SALURBAL) project. We developed a research protocol using official and non-official sources combining the results of Google Maps (GMaps) points and OpenStreetMap (OSM) polygons-GMaps-OSM. Descriptive analyses included the frequency of the distribution of parks before and after harmonization stratified by data source. We used the intraclass correlation coefficient (ICC) to assess agreement in the area between official and GMaps-OSM data. Official data were obtained for 16 cities; for the remaining 11 capitals, we used GMaps-OSM. After verification and harmonization, 302 urban parks were obtained from official data and 128 from GMaps-OSM. In a sub-study of the 16 cities with official data (n = 302 parks), we simulated a collection of non-official data using GMaps-OSM and OSM only. From GMaps-OSM, we obtained 142 parks, and from OSM, 230 parks. Statistical analysis showed a better agreement between official data and OSM. After completing verification and harmonization, the complete dataset (official and GMaps-OSM) included 430 urban parks with a total area of 145.14 km2. The mean number of parks across cities was 16, with a mean size area of 0.33 km2. The median number of parks was nine, with a median area of 0.07 km2. This study highlights the importance of creating mechanisms to access, collect, harmonize, and verify urban park data, which is essential for examining the impact of parks on health. It also stresses the importance of providing reliable urban park spatial data for city officials.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Flowchart of spatial urban park data collection.
See this image and copyright information in PMC

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