Land use regression (LUR) models are widely used in epidemiological and environmental
studies to estimate humans' exposure to air pollution within urban areas. However, the early …

Accurate prediction of parameters related to the environmental exposure of chemicals is
crucial for the sound management of chemicals. However, the lack of large data sets for …

Urban air pollution is one of the serious environmental problems in the development of high-
density cities, especially for traffic-related pollution. Effective urban environmental …

Addressing the challenge of mapping hyperlocal air pollution in areas without local
monitoring, we evaluated unsupervised transfer learning-based land-use regression (LUR) …

Accurate building height estimation is key to the automatic derivation of 3D city models from
emerging big geospatial data, including Volunteered Geographical Information (VGI) …

This study investigated the utilization of images collected from low-quality dash cameras on
passenger vehicles for the estimation of traffic-related air pollution (TRAP). We conducted …

Mobile monitoring campaigns have effectively captured spatial hyperlocal variations in long-
term average concentrations of regulated and unregulated air pollutants. However, their …

This study aimed to examine the validity of a mobile air quality sensor fleet in improving
pollution exposure assessments in urban areas. The scope of this study involved …

Mobile air pollution measurements are typically aggregated by varying road segment
lengths, grid cell sizes, and time intervals. How these spatiotemporal aggregation schemas …

Many local agencies in the United States and other countries are tasked to install air
pollution monitoring systems of highly accurate sensors that have high acquisition …