activity
20212025
most citedTowards the automated large-scale reconstruction of past road networks from historical maps

45 citations · 101 across the 16 of their papers we have counts for

collaborators

16 papers

physics.soc-ph2025

CHRONEX-US: City-level historical road network expansion dataset for the conterminous United States

Johannes H. Uhl, Keith A. Burghardt, Stefan Leyk

Geospatial datasets on the long-term evolution of road networks are scarce, hampering our quantitative understanding of how the contemporary road network has evolved over the cours…

physics.soc-ph2024★ 1 cited

Universal Patterns in the Long-term Growth of Urban Infrastructure in U.S. Cities from 1900 to 2015

Keith Burghardt, Johannes H. Uhl, Kristina Lerman +1

Despite the rapid growth of cities in the past century, our quantitative, in-depth understanding of how cities grow remains limited due to a consistent lack of historical data. Thu…

physics.soc-ph2024★ 2 cited

Towards localized accuracy assessment of remote-sensing derived built-up land layers across the rural-urban continuum

Johannes H. Uhl, Stefan Leyk

The accuracy assessment of remote-sensing derived built-up land data represents a specific case of binary map comparison, where class imbalance varies considerably across rural-urb…

stat.AP2024

Thematic agreement assessment of gridded, multi-modal geospatial datasets of different semantics and spatial granularities

Johannes H. Uhl, Stefan Leyk

This paper presents a method for thematic agreement assessment of geospatial data products of different semantics and spatial granularities, which may be affected by spatial offset…

physics.soc-ph2023★ 8 cited

Spatially explicit accuracy assessment of deep learning-based, fine-resolution built-up land data in the United States

Johannes H. Uhl, Stefan Leyk

Geospatial datasets derived from remote sensing data by means of machine learning methods are often based on probabilistic outputs of abstract nature, which are difficult to transl…

physics.soc-ph2022★ 3 cited

Analyzing urban scaling laws in the United States over 115 years

Keith Burghardt, Johannes H. Uhl, Kristina Lerman +1

The scaling relations between city attributes and population are emergent and ubiquitous aspects of urban growth. Quantifying these relations and understanding their theoretical fo…

physics.soc-ph2022★ 10 cited

Uncertainty prediction of built-up areas from global human settlement data in the United States based on landscape metrics

Johannes H. Uhl, Stefan Leyk

The level of landscape heterogeneity may affect the performance of remote sensing based land use / land cover classification. However, the relationship between mapping accuracy of…

physics.soc-ph2022★ 30 cited

A framework for scale-sensitive, spatially explicit accuracy assessment of binary built-up surface layers

Johannes H. Uhl, Stefan Leyk

To better understand the dynamics of human settlements, thorough knowledge of the uncertainty in geospatial built-up surface datasets is critical. While frameworks for localized ac…

physics.soc-ph2022★ 1 cited

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

Johannes H. Uhl, Stefan Leyk

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 gr…

physics.soc-ph2022

Place-level urban-rural indices for the United States from 1930 to 2018

Johannes H. Uhl, Lori M. Hunter, Stefan Leyk +5

Rural-urban classifications are essential for analyzing geographic, demographic, environmental, and social processes across the rural-urban continuum. Most existing classifications…

stat.AP2022★ 1 cited

A fine-grained, versatile index of remoteness to characterize place-level rurality

Johannes H. Uhl, Stefan Leyk, Lori M. Hunter +4

Rural-urban classifications are essential for analyzing geographic, demographic, environmental, or socioeconomic processes across the rural-urban continuum. However, existing count…

cs.CV2022★ 45 cited

Towards the automated large-scale reconstruction of past road networks from historical maps

Johannes H. Uhl, Stefan Leyk, Yao-Yi Chiang +1

Transportation infrastructure, such as road or railroad networks, represent a fundamental component of our civilization. For sustainable planning and informed decision making, a th…

eess.IV2021

A Label Correction Algorithm Using Prior Information for Automatic and Accurate Geospatial Object Recognition

Weiwei Duan, Yao-Yi Chiang, Stefan Leyk +2

Thousands of scanned historical topographic maps contain valuable information covering long periods of time, such as how the hydrography of a region has changed over time. Efficien…

cs.CV2021

Guided Generative Models using Weak Supervision for Detecting Object Spatial Arrangement in Overhead Images

Weiwei Duan, Yao-Yi Chiang, Stefan Leyk +2

The increasing availability and accessibility of numerous overhead images allows us to estimate and assess the spatial arrangement of groups of geospatial target objects, which can…

cs.AI2021

An Automatic Approach for Generating Rich, Linked Geo-Metadata from Historical Map Images

Zekun Li, Yao-Yi Chiang, Sasan Tavakkol +4

Historical maps contain detailed geographic information difficult to find elsewhere covering long-periods of time (e.g., 125 years for the historical topographic maps in the US). H…

physics.soc-ph2021

Road Network Evolution in the Urban and Rural United States Since 1900

Keith Burghardt, Johannes Uhl, Kristina Lerman +1

Road networks represent a key component of human settlements, such as cities, towns, and villages, that mediate pollution and congestion, as well as economic development. However,…