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Air pollution modelling 1

GDAL/OGR Python 1

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PyLUR: Efficient software for land use regression modeling the spatial distribution of air pollutants using GDAL/OGR library in Python

Xuying Ma, Ian Longley, Jennifer Salmond, Jay Gao

Frontiers of Environmental Science & Engineering 2020, Volume 14, Issue 3, doi: 10.1007/s11783-020-1221-5

Abstract: PyLUR comprises four modules for developing and applying a LUR model.Land use regression (LUR) models have been widely used in air pollution modeling.In this contribution, we present a LUR modeling and pollution-mapping software named PyLUR.It uses GDAL/OGR libraries based on the Python platform and can build a LUR model and generate pollutantThe performance of the newly developed PyLUR is compared to an existing LUR modeling software called

Keywords： LUR     Air pollution modelling     GIS spatial analysis     GDAL/OGR Python     Pollutant concentration mapping    

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PyLUR: Efficient software for land use regression modeling the spatial distribution of air pollutants using GDAL/OGR library in Python

Xuying Ma, Ian Longley, Jennifer Salmond, Jay Gao

Journal Article