spatiotemporal land use regression (lur) model (Environment and Climate Change Canada)
90
Structured Review
Environment and Climate Change Canada
spatiotemporal land use regression (lur) model
Spatiotemporal Land Use Regression (Lur) Model, supplied by Environment and Climate Change Canada, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/spatiotemporal+land+use+regression+(lur)+model/spatiotemporal+land+use+regression++lur++model/pm33716024-8-59-24
Average 90 stars, based on 1 article reviews
Spatiotemporal Land Use Regression (Lur) Model, supplied by Environment and Climate Change Canada, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/spatiotemporal+land+use+regression+(lur)+model/spatiotemporal+land+use+regression++lur++model/pm33716024-8-59-24
Average 90 stars, based on 1 article reviews
spatiotemporal land use regression (lur) model - by Bioz Stars,
2026-10
90/100 stars
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other:Article Title: Characterizing long-term NO 2 concentration surfaces across a large metropolitan area through spatiotemporal land use regression modelling of mobile measurements. Article Snippet: A spatiotemporal land use regression (LUR) model optimized to predict nitrogen dioxide (NO2) concentrations obtained from on-road, mobile measurements collected in 2015–16 was independently evaluated using concentrations observed at multiple sites across Toronto, Canada, obtained more than ten years earlier.. This spatiotemporal LUR modelling approach improves upon estimates of historical NO2 concentrations derived from the previously used method of back-extrapolation.. The optimal spatiotemporal LUR model (R2 = 0.71 for prediction of NO2 data in 2002 and 2004) uses daily average NO2 concentrations observed at multiple long-term monitoring sites and hourly average wind speed recorded at a single site, along with spatial predictors based on geographical information system data, to estimate NO2 levels for time periods outside of those used for model development. |