Product shifts happen. Cars replace horses, digital music replaces analog. Shifts happen in Location Intelligence data – small area demographics replace census demographics, real traffic flow information replaces modeled traffic data. The next 12-18 months will see another shift that brings higher accuracy data to your locating, analyzing and visualizing business challenges – addressed building footprint data.
This shift will move massive numbers of Location Intelligence business solutions from parcel data and address point data to the world of Building-centric Location Intelligence. Cutting edge organizations will embrace this new data model and will see results – higher accuracy analysis, improved abilities to locate their customers and opportunities, and meaningful methods to visualize information in new ways.
The BuildingFootprintUSA™ Data Solution
20 years ago, the first generation of geocoding was street segment-based geocoding, interpolating along a street segment given house numbers at the beginning and end of the street. Next came generation 2 – address point and parcel boundary data. You could geocode to address points – approximations for the locations of addresses. You could reverse geocode to parcel boundaries – reasonable proxies for the location surrounding an address.
BuildingFootprintUSA™’s Data Solution delivers the third generation of Location Intelligence accuracy – addressed building footprint data. To locate, analyze and visualize the places where people work, shop, live, and play we use buildings, polygons linked to the address information to give you the highest accuracy.
We can show you the building and tell you every bit of address information inside. We can you tell you that 200 S West St is a building, that it has additional addresses like 511 W Hargett St, and secondary units such as Suites B, C and D.
With Building-Centric Location Intelligence, you get:
The most accurate spatial object for geocoding and reverse geocodingA comprehensive set of addresses associated with the buildingThe physical characteristics of the building such as building heightThe ability to connect to any information that can be joined by address, postcode, census ID, or parcel ID
This new, highly accurate model impacts every Location Intelligence method. Take reverse geocoding – imagine being able to reliably use spatial operators when reverse geocoding such as “inside”, “moving towards”, and “near”; or think of the benefit of being able to get back a meaningful collection of addresses associated with your reverse geocode; or envision the ability to use filters such as “show me the largest building that I am near.”
We’re building a better mousetrap at BuildingFootprintUSA™… a more accurate mousetrap. Let’s see how our mousetrap compares against address points and parcel data.
Address Points Are Not Rooftop Accurate
Address points have been given the tag “rooftop geocoding,” which is frequently a misnomer. Explore many rooftop geocoding solutions and you will find that the actual locations are the centroids of the parcels of the buildings. We tested one large state that we believe has some of the most accurate address point data. In this state, we found nearly 25% of all address points do not fall within the building footprint.
At BuildingFootprintUSA™, we deliver you accurate locations. When you create a point level geocoding dataset from our Addressed Building Footprints you have rooftop geocodes. Or you can use a building footprint polygon in your analysis for the highest possible accuracy which matters if you are performing insurance risk assessment..
Above – Address points, in pink, aren’t rooftop accurate (clockwise, from upper left) near a church, in a suburban development, on a city block and for the anchor stores in a shopping mall.
Do you have mission critical business needs where accuracy matters? Delivery and logistics applications, tax applications, location based marketing, emergency response, insurance risk management and more – all benefit from highly accurate addressed building footprints.
Address Points Don’t Model Multiple Buildings
If each address point was only associated with one building; at least the error and inaccuracy would be limited. Our studies show nearly 20% of all address points are associated with property covering multiple buildings – a single family home with a detached garage, an apartment complex covering several buildings, a farm house with several out buildings, a commercial location with an adjoining warehouse, industrial properties with multiple buildings, and more.
Above – An address point, in pink, may represent many buildings with a generalized location; BuildingFootprintUSA™ models using accurate polygons (clockwise, from upper left) – warehouses, rural residential, academic campuses and manufacturing facilities.
Business applications that require a highly accurate or nuanced sense of where break down when you model many things (several buildings) with a single approximation (an address point).
Parcels Don’t Always Model One Building & One Address
If all buildings had a single address, were contained within a single parcel, and no other buildings existed in the parcel then reverse geocoding and geofencing applications would be easy.
However, a single townhouse building might fall on multiple parcels. A shopping mall may have separate parcels for the anchor store and for the rest of the shopping mall. An apartment complex with 20 buildings and 400 households may be completely contained within a single parcel.
In Boulder, Colorado if you were geofencing or reverse geocoding with parcel boundaries (in yellow), you would miss being able to distinguish the 21 unique buildings, such as 690 Walden Circle, within the parcel.
Nearly 10% of the time parcels, buildings and addresses do not follow a 1:1:1 model, which leads to inaccuracy. These locations are frequently the highest value buildings that require the highest accuracy reverse geocoding and geofencing.
Address Points and Parcels May Not Represent Anything Meaningful
Lastly, address point and parcel data may model locations that you don’t care about, locations that get in the way of accurate analysis. Parcels without buildings, and address points found on yet-to-be-developed land are just two of the many scenarios where the data’s shortcomings yield inaccuracy
Imagine an application that performs reverse geocoding on a device’s locations. These locations (red triangles) reverse geocode to the address point 9751 GOVERNMENT CENTER PKWY. On the left map you are seeing expected behavior… until you look at the context with imagery where you just reverse geocoded to a parking lot. 9 application owners out of 10 would prefer to only reverse geocode to buildings, including the purple building at 6610 PUBLIC SAFETY RD.
This scenario is not unique. Addressed building data insures you only analyze with important data.
Shift to high accuracy Location Intelligence
Building-centric analysis is the next generation of Location Intelligence and represents a fundamental shift in how we will locate, analyze and visualize. We talk with clients every data across industries – telecom, insurance, real estate analytics, utilities and more – and they explain to us what accuracy means to them. We validate every day that building-centric Location Intelligence will give them the highest accuracy their business requires.
Start a conversation with us to talk about the power and accuracy of a building-centric world – email@example.com