Calculating access to parks and other polygonal resources: A description of open-source methodologies

IF 2.1 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Keith R. Spangler , Paige Brochu , Amruta Nori-Sarma , Dennis Milechin , Michael Rickles , Brandeus Davis , Kimberly A. Dukes , Kevin J. Lane
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引用次数: 0

Abstract

Public health studies routinely use simplistic methods to calculate proximity-based “access” to greenspace, such as by measuring distances to the geographic centroids of parks or, less frequently, to the perimeter of the park area. Although computationally efficient, these approaches oversimplify exposure measurement because parks often have specific entrance points. In this tutorial paper, we describe how researchers can instead calculate more-accurate access measures using freely available open-source methods. Specifically, we demonstrate processes for calculating “service areas” representing street-network-based buffers of access to parks within set distances and mode of transportation (e.g., 1-km walk or 20-minute drive) using OpenRouteService and QGIS software. We also introduce an advanced method involving the identification of trailheads or parking lots with OpenStreetMap data and show how large parks particularly benefit from this approach. These methods can be used globally and are applicable to analyses of a wide range of studies investigating proximity access to resources.

计算公园和其他多边形资源的访问:对开源方法的描述
公共卫生研究通常使用简单的方法来计算基于邻近程度的“进入”绿色空间的途径,例如测量到公园地理质心的距离,或者较少使用到公园区域周长的距离。虽然计算效率高,但这些方法过于简化了暴露测量,因为公园通常有特定的入口点。在这篇教程中,我们描述了研究人员如何使用免费的开源方法来计算更准确的访问度量。具体来说,我们演示了使用OpenRouteService和QGIS软件计算“服务区域”的过程,这些“服务区域”代表了在设定距离和交通方式(例如,1公里步行或20分钟车程)内基于街道网络的公园缓冲区。我们还介绍了一种先进的方法,包括使用OpenStreetMap数据识别小径起点或停车场,并展示了大型公园如何从这种方法中受益。这些方法可以在全球范围内使用,并适用于调查资源接近性的广泛研究的分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Spatial and Spatio-Temporal Epidemiology
Spatial and Spatio-Temporal Epidemiology PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
5.10
自引率
8.80%
发文量
63
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