The Evolution of Geocoding: Moving From Street Segments to Qualified Building Footprint Data

Geocoding, which is the process of converting addresses into geographic coordinates, is becoming more and more searched for by businesses offering location-related software.

My personal journey through geocoding reflects the evolution of this fascinating field, beginning with street segment data (so simply a line in the middle of the street on a map) to very advanced building polygons and rooftop-level precision (with the exact building boundaries).

This article outlines my experience and the lessons I’ve learned when moving to such high-precision building footprint data over the years.

The Early Days: Street Segments and Car GPS 

When I first delved into geocoding, the technology heavily relied on street segment data. This method uses the geographic coordinates of road centerlines to estimate the location of addresses. For instance, if an address is at 123 Main Street, the geocoding system would interpolate its position along the street based on the address range of the segment. 

This approach was instrumental in powering early car GPS systems. At the time, it offered a significant leap forward in navigation technology. Drivers could rely on relatively accurate directions, and businesses could use geocoded data for logistics and planning. However, the method came with limitations: 

1. Approximation: Street segment interpolation provides an estimate, not an exact location. This means the geocoded point might be slightly off, especially for large properties or irregular address ranges. 
2. Lack of Detail: It could not differentiate between specific buildings or account for complex urban environments, such as multi-story structures or dense residential areas. 

Despite these shortcomings, street segment geocoding laid the foundation for further innovations. 

Advancing Precision: Building Polygons 

As technology progressed, so did the need for more precise geocoding. The next step in my journey was leveraging building polygon data.

Building polygons represent the actual footprints of structures, offering a significant improvement in accuracy over street segments.

By associating addresses with their corresponding building footprints, geocoding systems could:

1. Improve Accuracy: Instead of estimating a location along a street, the system could pinpoint the building where the address is located. 
2. Enhance Context: Building polygons provide valuable contextual information, such as the size and shape of the structure. This is especially useful for urban planning, real estate, and emergency response.  

However, one challenge I encountered during this phase was the abundance of unqualified building footprint data. Many building polygons derived from spatial imagery lacked associated addresses. While these datasets are useful for understanding urban layouts and land use, their geocoding potential is limited without the address linkage. Addressing this gap requires further efforts in data enrichment and validation, highlighting the importance of integrating multiple data sources to achieve comprehensive results. 

Integrating building polygons into geocoding required access to detailed datasets and robust algorithms to process them efficiently. It marked a significant milestone in my work, enabling applications that required higher levels of precision. 

The Pinnacle of Precision: Rooftop Coordinates 

Today, the gold standard in geocoding is rooftop-level precision. Rooftop geocoding assigns coordinates to the exact center or entry point of a building’s roof. This level of accuracy is transformative for a wide range of applications like E-commerce and Delivery, they need accurate geocoding to ensure that packages reach the correct doorstep, reducing delivery errors and enhancing customer satisfaction. Other examples may be emergency services what can save lives by guiding responders to the exact location of an incident or other, like real estate and mapping companies, which use rooftop coordinates to enrich maps and property data, providing users with detailed and reliable information. 

If you would like to learn more about our building footprints, please click here to find all the information.