Airbus Logo

Defence and Space

Airbus Logo

Defence and Space

Airbus Logo

Defence and Space

U.S. Census Bureau: Automated Detection and Classification of Nationwide Residential Construction

U.S. Census Bureau: Automated Detection and Classification of Nationwide Residential Construction

Machine Learning algorithms from Reveal analyse high-resolution Pléiades imagery from OneAtlas to count residential construction projects and assess their current stage across the US. The information derived from satellite imagery is analysed by Reveal and provided to the U.S. Census Bureau to help monitor areas under construction.
 

Challenge

The U.S. Census Bureau tracks new home construction activity in approximately 20,000 jurisdictions and unincorporated areas every month. This includes all types of residential structures - single family homes, townhomes, and condominium buildings. The Census Bureau tracks these projects in three stages: New Starts, In Progress, and Completed. These status reports are used to calculate monthly investments in residential construction, which is one of the key economic indicators measuring the health of the US economy.

The Census Bureau has traditionally gathered construction data by manually monitoring building permits and conducting surveys. Unfortunately, this information is often out of date, incomplete, or inconsistent because construction permitting and reporting processes vary from one jurisdiction to the next.

Norwalk Iowa, USA - after (in 2020)
Norwalk Iowa, USA - before (in 2016)

Our solution

Reveal has developed an automated process that uses machine learning to analyze 50cm Pléiades optical imagery to identify when land has been cleared for residential construction, determine the type of structure being built (home, townhouse, etc.), assess monthly progress, and verify completion.

Because building types vary greatly across the country, Reveal leveraged the extensive Pléiades archive from OneAtlas to train the algorithms to recognize the many building features and differentiate them from other construction projects. The algorithms learn over time to improve the accuracy of classification of construction stages, so the Census Bureau can better calculate economic value.

With approximately 90% accuracy, Reveal’s advanced process automation (APA) solution is identifying residential construction and classifying each phase of activity from groundbreaking through to completion.

Benefits

Residential construction progress reports are more accurate and reliable across the nation because building sites are monitored directly by satellites that acquire imagery that can be analyzed by machine learning in an automated process that is consistent from month-to month and region-to-region.

Reveal Consulting Logo

Organisation involved

Reveal Global Consulting, LLC is a data analytics, visualization, and modeling firm located in Fulton, Maryland. Learn more at http://www.revealgc.com/

The U.S. Census Bureau Economic Indicators Division, Construction Programs, tracks building activity every month as a key indicator of U.S. economic health.

Want to know more?

Our sales team will be happy to provide you more information about this case study and how it can meet your business needs.

satellite-image-map-airbus-product-page.jpeg

See all our case studies

See all
Banner ratio 169.png
Environmental Assessment and Prediction
Pléiades Neo

Monitoring a French remote island that has been taken over by fire

Banner Earth Observation Satellites
Defence Space Solutions and Systems
Pléiades

Signal Activity Identification over Iran

This tip-and-cueing Multi-Int analysis shows a probable P-18 Spoon Rest signal identification in a remote area.

Large tanker with container cargo
Maritime
Mobility and Transportation
Defence Space Solutions and Systems
Pléiades

Hijacked Tanker Aris 13 Located with the Help of Pléiades

By combining the Automatic Identification System (AIS) and the Pléiades satellites, Airbus helped locating the ARIS 13 oil tanker attacked by Somali pirates in only 2 days.