摘要 : Geographical research on the community food environment emphasizes the spatial dimension of food access, where food quality and nutrition are overlooked. While the nutritional quality of food stores can be evaluated by audit tools... 展开 Geographical research on the community food environment emphasizes the spatial dimension of food access, where food quality and nutrition are overlooked. While the nutritional quality of food stores can be evaluated by audit tools, such as the Nutrition Environment Measurement Survey series, these tools cannot be readily applied on a large scale. To aid in the nutrition assessment of the community food environment, this article proposes an innovative image recognition approach that identifies the nutrition information of restaurant food by crowdsourcing food images and retrieving their nutrition information in a case study of Franklin County, Ohio. As these food images are derived from food review websites, they represent consumers' actual dietary quality as a more direct, quantifiable measure of the community food environment. The derived nutrition information is applied for further analysis to characterize neighborhood obesogenity, referring to as factors in the built environments that facilitate the development of obesity. The proposed crowdsourcing-image recognition approach enriches the understanding of health inequities from a nutrition science perspective, which is beyond the tradition of food access in the spatial dimension only. 收起