Geocoding is one of the foundational processes of geographic information systems (GIS). However, there are many different types of geocoding, each with distinct implications for data accuracy and analytics. This guide breaks down the various levels of geocoding precision often used in geospatial analysis as well as the impact each has on top use cases for geocoding.

What is geocoding?

Geocoding is the process of converting an address string to geographic coordinates so it can be mapped. It’s what makes it possible to associate 30 Rockefeller Plaza, New York, New York 10112 with 40°45′32″N 73°58′45″W. When an address is translated into coordinates, the process is called “forward geocoding;” “reverse geocoding” refers to coordinates being converted into a text string, such as an address or place name. Both processes are commonly used in location-based applications and analysis to link addresses with physical places.

Types of geocoding precision

There are a few different geocoding methodologies that can be used to place an address on a map. Which one to use depends on the level of precision needed for the particular application and whether “close enough” is good enough. 

Here is a summary of the different types of geocoding and their respective levels of precision:

Rooftop-level geocode

The gold standard in geocoding, rooftop-level geocodes associate an address string or place name with the geographic coordinates of the building it represents. Also referred to as building-based or structure point geocoding, this methodology is the most accurate for representing an address’s location on Earth’s surface.

Parcel-level geocode

If understanding exactly where a building is located is not integral to the use case, parcel-level or parcel centroid geocoding may suffice. Parcels comprise a property’s entire spatial extent, including land and any structures that may be present. These geocodes are typically assigned at the parcel centroid to generally represent where a property is located.

Street-level geocode

If no parcel information is available, geocodes can be placed according to street segments. Street segment data is often appended with a range of the addresses it encompasses, such as “100-200 Main Street.” An address string can be plotted along the appropriate street segment in this scenario, typically offset from the street centerline perpendicularly at a distance set by the data provider.

Parcel point interpolation geocode

When specific property or street information is not available, geocodes can be interpolated from nearby parcel data. This method indicates the location between two parcel centroids, offset from the street centerline based on the distance between those two centroids and the street centerline.

Parcel-street interpolation geocode

If only one nearby parcel is available, nearby street segments can also be used to derive a geocode. In this case, the geocode is placed between a parcel centroid and a street segment endpoint, usually offset from the street centerline perpendicularly at a set distance specific to the data provider.

Intersection point geocode

In conversation, place locations are often described as the intersection of two streets. Intersection point geocoding takes this approach, assigning address coordinates to the point where two street centerlines intersect or the centroid of a pre-defined intersection polygon. 

ZIP code centroid geocodes

In the event that no parcel or street geometry is available to derive an address point from, the ZIP code from the address string can be used. Geocodes can be placed at the centroid of a ZIP code boundary; however, the number of digits available in the address string’s ZIP code will determine how close to the actual property the geocode will be. 

The more digits in a ZIP code, the smaller the boundary and the more specific the derived geocode. 

Why is geocoding precision important?

Geocoding underpins many location-based applications, powering “find my nearest”-style searches and GPS routing as well as various property analytics use cases in insurance, real estate, telecommunications, and more. While less precise geocoding methods may be sufficient for some use cases, others require the most accurate geolocation for address strings. 

Here are a few real-world examples of how geocoding precision directly impacts geospatial applications:

Risk assessment

Geocoding is commonly used to locate a property in risk assessment workflows. Insurance carriers price policies, define reinsurance strategies, and respond to claims based on a property’s location, so understanding exactly where it is on Earth’s surface is critical. For instance, if an inaccurate geocode incorrectly places an address point in a flood zone, any resulting analytics and decision-making will be skewed. 

Prior to adopting a building-based geocoding methodology, Harford Mutual regularly had to investigate the locations of each individual property they were analyzing for reinsurance purposes, often needing to correct the geocoded location. Once they made the switch to rooftop-level geocoding, they were able to reduce building location mapping time by 75% and optimize their reinsurance strategy with true structure-based risk insights. 

Routing

Routing applications leverage geocoding to establish beginning and end points. In consumer-facing routing, inaccurate geocodes can result in user frustration and annoyance, but close enough can often be good enough. However, accurate geocoding is essential for emergency service routing systems that can make a huge difference in situations where every second counts.

Emergency services teams in Collier County, Florida use structure point geocodes to ensure they are routed to a property’s main building, where callers are most likely to be located. To further enhance the efficiency and accuracy of their routing system, they layer in driveways and parking lots associated with these geocoded buildings. This ensures first responders can access the geocoded location, reducing response times and increasing positive outcomes in emergency situations.

Network planning

Telecommunications services are typically address-based. For example, internet providers will determine whether a property is broadband-serviceable as they plan their network access. Less precise geocoding methods can result in the missed identification of broadband-serviceable locations (BSLs), a major factor in the digital divide.

In many underserved areas, properties that are in fact BSLs do not have any network access. Building-based geocoding techniques helped several states identify these underserved locations and secure more than $3.5 billion in federal funding to expand broadband access.

Get started with Building-Based Geocoding

As the creator of the first and only complete map of buildings in the US, Ecopia AI (Ecopia) is the leading provider of rooftop-level geocoding. Our Building-Based Geocoding product associates 270M+ primary and secondary addresses with our database of 176M+ high-precision building footprints, ultimately providing a 97% accurate geocoding dataset (compared to an industry standard of 58%). We’re transparent about our data, appending each geocode with a confidence score that indicates what type it is in the rare case that a rooftop-level match is unavailable. 

Ecopia is able to achieve this level of precision by placing building footprints at the center of our process. Extracted from the most current high-resolution geospatial imagery by Ecopia’s AI-based mapping systems, these foundational building footprints have been proven to have a 97%+  geometric accuracy through independent evaluation. This enables us to associate addresses directly with structures while also providing contextual property relationship information such as parent/child addresses and assessor’s parcel numbers (APNs), all connected through a system of unique identifiers for master data management.

To learn more about Ecopia’s Building-Based Geocoding, get in touch with our team.