MTBF-33: A multi-temporal building footprint dataset for 33 counties in the United States (1900-2015)

TL;DR

The paper introduces MTBF-33, a comprehensive dataset of over 6.2 million historical building footprints across 33 U.S. counties from 1900 to 2015, enabling long-term analysis of settlement evolution.

Contribution

It presents a novel, harmonized dataset derived from cadastral and tax data, filling a gap in long-term spatial-temporal settlement data for the U.S.

Findings

Provides a detailed, multi-temporal building footprint dataset from 1900 to 2015.

Enables retrospective analysis of urban development and settlement patterns.

Supports validation and training of remote sensing and historical mapping methods.

Abstract

Despite abundant data on the spatial distribution of contemporary human settlements, historical data on the long-term evolution of human settlements at fine spatial and temporal granularity is scarce, limiting our quantitative understanding of long-term changes of built-up areas. This is because commonly used mapping methods (e.g., image classification) and suitable data sources (i.e., aerial imagery, multi-spectral remote sensing data, LiDAR) have only been available in recent decades. However, there are alternative data sources such as cadastral records that are digitally available, containing relevant information such as building age information, allowing for an approximate, digital reconstruction of past building distributions. We conducted a non-exhaustive search of open and publicly available data resources from administrative institutions in the United States and gathered, integrated, and harmonized cadastral parcel data, tax assessment data, and building footprint data for 33 counties, wherever building footprint geometries and building construction year information was available. The result of this effort is a unique dataset which we call the Multi-Temporal Building Footprint Dataset for 33 U.S. Counties (MTBF-33). MTBF-33 contains over 6.2 million building footprints including their construction year, and can be used to derive retrospective depictions of built-up areas from 1900 to 2015, at fine spatial and temporal grain and can be used for data validation purposes, or to train statistical learning approaches aiming to extract historical information on human settlements from remote sensing data, historical maps, or similar data sources. MTBF-33 is available at http://doi.org/10.17632/w33vbvjtdy.