# A Geospatial Framework of Food Demand Mapping
## 5 Conclusions  
This research introduces a novel framework for mapping food demand by integrating individual dietary behaviors with advanced spatial data analysis techniques. Through the application of the Shepard interpolation method, we have successfully generated high-resolution maps that highlight regional disparities in eating habits across Lithuania. This granular approach allows for the precise identification of areas, such as food deserts and food swamps, which are in urgent need of nutritional interventions. Our findings reveal significant regional variations in dietary practices, with the northern and western parts of Lithuania exhibiting healthier eating habits compared to the southern regions. In Vilnius, the spatial distribution of dietary habits shows a gradient from less favorable practices in the city center to healthier behaviors in the outskirts, reflecting socio-economic and accessibility factors. These insights are crucial for informing targeted policy interventions aimed at improving public health outcomes and ensuring equitable access to nutritious food. Based on our findings, we propose the following specific policy recommendations: Firstly, policymakers should incentivize businesses to open grocery stores in underserved areas through subsidies, tax breaks, or grants. Secondly, e-grocery platforms should be encouraged to serve economically disadvantaged neighborhoods by subsidizing delivery costs and improving digital infrastructure. Thirdly, support should be provided to farmers to align crop production with the dietary needs identified in food demand maps through local government and business partnerships. Additionally, implementing community-based nutrition education programs tailored to specific cultural and socio-economic contexts is crucial. Enhancing public transportation to improve access to grocery stores in rural and low-income urban areas is also recommended. Retail and e-grocery sectors should offer discounts or free delivery for low-income households and accommodate working families' schedules. Lastly, investing in local food hubs to aggregate and distribute produce from small farmers within the community will be beneficial. The innovative methodological framework presented in this study not only advances the field of food demand mapping but also provides a robust tool for policymakers to address nutritional challenges. By leveraging detailed survey data and sophisticated spatial analysis, our approach transcends traditional methods, offering a dynamic and context-aware representation of food environments. However, the study's reliance on a small sample size, characteristic of a pilot study, poses limitations on the generalizability of the findings. Future research will aim to expand the sample size and incorporate additional data sources, such as satellite imagery and socio-economic indicators, to enhance the accuracy and reliability of food demand predictions. This expanded approach promises to provide a more comprehensive understanding of food demand dynamics, facilitating more effective decision-making in food systems and contributing to global efforts in achieving food security and promoting healthier eating habits. In summary, this research underscores the importance of integrating micro-level dietary choices with macro-level spatial analytics to address food accessibility and nutrition challenges. The developed framework sets a foundation for future studies to build upon, offering a path forward for more precise and impactful nutritional intervention. In conclusion, this research represents a significant step forward in the application of geospatial analysis to the study of food demand and security. By providing a comprehensive and detailed view of dietary habits across Lithuania, it contributes valuable insights into the factors that influence food accessibility and consumption patterns.