Analyzing Relationships Between Spatial Entities

In our journey through MySQL’s capabilities, we have laid a solid foundation by creating spatial entities integral to our e-scooter startup’s operational framework. Now, we focus on a more intricate yet crucial aspect—analyzing the relationships between these spatial entities. This analysis is fundamental in extracting meaningful patterns and insights from our spatial data. MySQL’s array of spatial operators and functions allows us to explore connections, proximity, and alignments among various spatial entities like points, lines, and polygons. This step is about moving beyond the mere existence of spatial data to unraveling the complex web of relationships they form, providing us with deeper insights crucial for strategic decision-making and operational efficiency.

Measuring distance

At our e-scooter startup, the primary goal is to efficiently guide customers to the e-scooter that is closest to their current location. To simplify this process, we measure the distance in a straight line, which we believe is the most efficient method, rather than measuring the actual directions. This approach of distance measurement is an integral part of understanding the relationships between different spatial entities. In light of this necessity, MySQL offers a suite of three functions specifically designed to calculate the distance between two spatial entities, each utilizing different measurement methods. Notably, the ST_Distance() function is used in this context. It takes two spatial entities as its parameters and computes the Euclidean distance between them. The Euclidean distance refers to the shortest spatial distance that can be measured between two geometries, and this measurement is done in the length unit of their respective spatial reference system (SRS):