Wang Lu, He Yakun, Yu Zhonghai, Wang Hongrui, Ye Wenjuan, Li Xin, Liu Yingping, Zhang Junxiao
Jinan Surveying and Mapping Research Institute, Jinan, China.
Chinese Aeronautical Establishment, Beijing, China.
PLoS One. 2025 Jan 22;20(1):e0317003. doi: 10.1371/journal.pone.0317003. eCollection 2025.
The "food desert" problem has been treated under a national strategy in the United States and other countries. At present, there is little research on the phenomenon of "food desert" in China. This study takes Shanghai as the research area and proposes a multiscale analysis method using a linear tessellation model that splits the street network into homogeneous linear units. Firstly, the network kernel density estimation using a linear tessellation model is used to measure the travel-mode-based food accessibility. Considering the actual travel constraints, the GPS trajectory data of four travel modes (walking, bicycle, metro and taxi) are applied to calculate the speed of each linear unit. Secondly, the "food desert" phenomenon in Shanghai are identified combing with the results of the network K-function. Finally, the resident income conditions in different modes are fitted based on the housing price data and the spatial distribution of four "food desert" patterns are detected by the overlay analysis of food accessibility and resident income conditions. The experimental results show that fifty percent of Shanghai is characterized by low food accessibility, and half of these areas are disadvantaged and low-income areas in suburbs, which are the locations experiencing the "food desert" phenomenon. Comparing the results of the proposed method and that of the traditional planar method, the identification results for all modes based on the traditional planar method underestimate the severity of the "food desert", especially for the bicycle and taxi modes. This study also provides corresponding decision-making reference for the alleviation and resolution of "food desert" issues. Moreover, the proposed method provides a new research perspective for urban research under the street network space.
“食物沙漠”问题在美国和其他国家已在国家战略下得到处理。目前，中国对“食物沙漠”现象的研究较少。本研究以上海为研究区域，提出一种多尺度分析方法，该方法使用线性镶嵌模型将街道网络划分为同质线性单元。首先，使用线性镶嵌模型的网络核密度估计来衡量基于出行模式的食物可达性。考虑到实际出行限制，应用四种出行模式（步行、自行车、地铁和出租车）的GPS轨迹数据来计算每个线性单元的速度。其次，结合网络K函数的结果识别上海的“食物沙漠”现象。最后，基于房价数据拟合不同模式下的居民收入状况，并通过食物可达性与居民收入状况的叠加分析检测四种“食物沙漠”模式的空间分布。实验结果表明，上海50%的区域食物可达性较低，其中一半区域位于郊区的弱势和低收入地区，这些地区正经历“食物沙漠”现象。将所提方法与传统平面方法的结果进行比较，基于传统平面方法的所有模式的识别结果均低估了“食物沙漠”的严重程度，尤其是自行车和出租车模式。本研究还为缓解和解决“食物沙漠”问题提供了相应的决策参考。此外，所提方法为街道网络空间下的城市研究提供了新的研究视角。
