The transport sector has been identified as one of the main contributors to nitrogen dioxide (NO2) pollution in Ireland. This research develops an enhanced Wind Sector Land Use Regression (WS-LUR) model estimate NO2 concentrations across Ireland, areas where air monitoring is not available. incorporates details vehicle fleet breakdown weight type flows based on emission rates type, differentiat...

Small data samples are still a critical challenge for spatial predictions. Land use regression (LUR) is widely used model predictions with observations at limited number of locations. Studies have demonstrated that LUR models can overcome the limitation exhibited by other prediction which usually require greater densities observations. However, accuracy and robustness need to be improved due li...

Noise pollution has negative health consequences, which becomes increasingly relevant with rapid urbanization. In low- and middle-income countries research on effects of noise is hampered by scarce exposure data maps. this study, we developed land use regression (LUR) models to assess spatial variability community in the Western Region São Paulo, Brazil.We measured outdoor levels continuously a...

nowadays, a noticeable part of areas with high development in different regions of the world is urban centers with touristy attractions. thus, in these cities, urban development comes forth as a basic challenge to decision makers and local planners. the aim of this research is to identify the driving forces which affect urban growth in the sareyn town, as one of the best known touristy centers ...

This study estimates the equivalent continuous sound pressure level (Leq) during peak daily periods (‘rush hour’) along New Klang Valley Expressway (NKVE) in Shah Alam, Malaysia, using a land use regression (LUR) model based on machine learning, statistical regression, and geographical information systems (GIS). The research utilises two types of soft computing methods including learning (i.e.,...

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