Prog Community Health Partnersh. 2020;14(1):109-115. doi: 10.1353/cpr.2020.0013.
The Greater Pittsburgh Community Food Bank (GPCFB) developed the Green Grocer mobile food market to address limited access to fresh, affordable food options in local communities. GPCFB and researchers from the University of Pittsburgh established a partnership for Green Grocer implementation and evaluation, including application of geospatial techniques to help identify locations of stops for Green Grocer.
We used geospatial analyses to identify locations in Allegheny County with limited food access as potential stops for the Green Grocer mobile food market.
Using census, county, city, and public health data, we conducted a spatial overlay analysis based on five key metrics: poverty/income rates, Supplemental Nutrition Assistance Program (SNAP) use, obesity rates, grocery/supermarket access, and mass transit access. We first defined our base target areas by finding the intersection of tracts with high rates of poverty, SNAP use, and obesity. To obtain our final recommended target neighborhoods, we then calculated the symmetric difference between these base target areas and areas of low grocery access and transit use.
As identified from our overlay analysis, six neighborhoods became the targeted pilot sites for Green Grocer. These particular communities had higher poverty rates than Pittsburgh, Allegheny County, and Pennsylvania averages. A separate pilot evaluation was conducted after the initial sites were selected to examine additional population characteristics and to help determine any modifications to the program.
Geospatial overlay analysis identified key locations to help the GPCFB target allocation of fresh food and produce. When used in tandem with other programmatic information and processes, this data-driven approach was essential in the development and identification of distribution of resources.
大匹兹堡社区食品银行（GPCFB）开发了绿色食品商移动食品市场，以解决当地社区新鲜、负担得起的食品选择有限的问题。GPCFB 和匹兹堡大学的研究人员建立了合作伙伴关系，以实施和评估绿色食品商，包括应用地理空间技术来帮助确定绿色食品商的停靠位置。
我们使用地理空间分析来确定阿勒格尼县内食品获取有限的地点，作为绿色食品商移动食品市场的潜在停靠点。
我们使用人口普查、县、市和公共卫生数据，根据五个关键指标（贫困/收入率、补充营养援助计划（SNAP）使用、肥胖率、杂货店/超市访问和大众交通访问）进行空间叠加分析。我们首先通过找到贫困率、SNAP 使用和肥胖率高的地段的交集来定义我们的基本目标区域。为了获得最终推荐的目标社区，我们计算了这些基本目标区域与杂货店和交通使用低的区域之间的对称差异。
从我们的叠加分析中确定了六个社区成为绿色食品商的试点目标社区。这些特定社区的贫困率高于匹兹堡、阿勒格尼县和宾夕法尼亚州的平均水平。在最初的地点选定后，进行了单独的试点评估，以检查其他人口特征，并帮助确定对该计划的任何修改。
地理空间叠加分析确定了关键位置，以帮助 GPCFB 确定新鲜食品和农产品的分配。当与其他计划信息和流程一起使用时，这种数据驱动的方法对于资源的开发和分配至关重要。
