Polygon Simplification for Location-Based Services Using Population Density

An important group of location-based services (LBS), including 9-1-1 service, rely on the mapping between a user´s location and a service boundary in order to select the appropriate service provider. In such cases, mobile clients can cache the mapping information to reduce service latency and server load. However, caching such a mapping can be burdensome on mobile devices because representing the polygon that defines a service boundary requires a large amount of data. We present GeoPS-PD, a polygon simplification algorithm designed for LBS applications. Unlike existing algorithms, GeoPS-PD never produces a false positive, is tunable at runtime for the desired balance between target polygon size and area coverage, and optionally takes into account the population density. We demonstrate the efficacy of GeoPS-PD using the US state boundary data. For New York, GeoPS-PD produces a simplified polygon which is only 3% of the original size, yet covers 95% of the original area, and makes the LBS queries 3.17 times faster.