In the study of local-level food security, terms such as food variety, availability, accessibility and utilization represent quantitative metrics to describe one's relationship to the tangible and intangible food environment. Food availability entails how close one is located to the nearest food location. These locations could be healthy and fresh food as applied explicitly to the study food deserts, generally considered to be low-income areas that are far from healthy and fresh food. In the Geographic Information Systems (GIS) network model where travel times and distances are either calculated along a line network such as a series of roads or via more traditional techniques such as Manhattan or Euclidean distance, healthy and fresh food locations are defined as destinations. The places people are traveling from are referred to as sources. However, modeling source locations can be increasingly complex. In just measuring food availability between all residential parcels to the closest healthy food destination in Guilford County, North Carolina, it requires more than 177,000 route calculations, one for each of the residential parcels in Guilford County, North Carolina. Research (Zandbergen and Hart 2009; Fischer 2004; Sahar et al. 2019; Winn 2014) has highlighted the challenges in efficiently locating many addresses and calculating so many routes. In order to simplify the number of network calculations, this research explores ways to model, agglomerate or simplify source locations to decrease the sheer number of calculations while not degrading results when compared to calculations using all original 177,000 source locations. Studies in the field of food security have modeled source locations as census tract centroids, block group centroids, as well as random points and even fishnets or grids. In this paper, we explore the use of different techniques to simulate source locations in the study of food availability in Guilford County, North Carolina. These results are compared to calculations using all residential source locations in the county as a baseline. While all eleven techniques, which include random, stratified and systematic, as well as combinations of them, showed some level of agreement with baseline measurements, sources simulated as block centroids, population-weighted block group centroids and even a randomized-strata technique were strongest using t-tests of two means and equivalence tests for dissimilarity for both drive-distance and drive-time.

在地方一级的粮食安全研究中，诸如食物品种，可获得性，可及性和利用等术语代表了定量指标，用以描述人们与有形和无形食物环境的关系。食物的可获得性意味着人们离最近的食物位置有多近。这些位置可能是健康和新鲜食物，明确应用于研究食物沙漠，通常被认为是远离健康和新鲜食物的低收入地区。在地理信息系统（GIS）网络模型中，旅行时间和距离要么沿着诸如一系列道路之类的路线网络计算，要么通过诸如曼哈顿或欧几里得距离之类的更传统的技术来计算，健康和新鲜食品的位置被定义为目的地。人们所旅行的地方称为来源。但是，对源位置进行建模可能会越来越复杂。仅测量距离北卡罗来纳州吉尔福德县最近的健康食品目的地的所有住宅地块之间的食物供应量，就需要进行超过177,000条路线计算，这是针对北卡罗来纳州吉尔福德县的每个住宅地块进行的计算。研究（Zandbergen and Hart 2009; Fischer 2004; Sahar et al.2019; Winn 2014）强调了有效定位许多地址和计算这么多路线所面临的挑战。为了简化网络计算的数量，与使用所有原始的177,000个源位置进行的计算相比，本研究探索了建模，聚集或简化源位置的方法，以减少纯粹的计算数量，而不会降低结果。粮食安全领域的研究已对源位置进行了建模，如普查区质心，街区组质心，随机点甚至渔网或网格。在本文中，我们在北卡罗来纳州吉尔福德县的食物供应研究中探索了使用不同技术来模拟货源位置的方法。将这些结果与以县中所有住宅源位置为基准的计算结果进行比较。虽然所有11种技术（包括随机，分层和系统的以及它们的组合）都显示与基线测量值有一定程度的一致性，但是模拟为块质心，总体加权块组质心甚至随机分层技术的源最强使用两个均值的t检验和等效性检验来确定行驶距离和行驶时间的不相似性。