Geospatial Data Analysis for Restaurant Business Strategies and Urban Planning

Geospatial data analysis is a crucial tool in various domains, including urban planning and environmental studies to business strategies and healthcare. This research paper presents a comprehensive approach to geospatial data analysis using clustering techniques and heatmaps. Clustering techniques offer the ability to identify patterns and group similar data points, while heatmaps visually represent the density or intensity of specific attributes across different locations on a map. The paper discusses the challenges of applying clustering techniques to geospatial analysis and presents a methodology that leverages geocoding techniques and kernel density estimation for heatmaps generation. The results and discussions section showcases the insights derived from the generated heatmaps, such as identifying popular dining areas, assessing restaurant quality, and understanding customer preferences. The implications of this research extend to restaurant business strategies, urban planning, and decision-making processes. The findings can guide location selection, menu offerings, and marketing strategies for businesses, as well as inform urban planners in identifying areas of high dining activity for infrastructure planning.