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• W2308284328 abstract "Satellite-retrieved aerosol optical depth (AOD) has been increasingly utilized for the mapping of fine particulate matter (PM <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2.5</sub> ) concentrations. An accurate estimation and mapping of PM <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2.5</sub> concentrations depends on the high-resolution AOD data and a robust mathematical model that takes into account the spatial nonstationary relationship between PM <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2.5</sub> and AOD. Take the core portion of the Beijing-Hebei-Tianjin (Jing-Jin-Ji) urban agglomeration as case study (the most seriously polluted region in China). Land use, population, meteorological variables, and simplified aerosol retrieval algorithm-retrieved AOD at 1-km resolution are employed as the predictors for the geographically weighted regression (GWR) and the ordinary least squares (OLS) model to map the spatial distribution of PM <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2.5</sub> concentrations. The GWR model shows significant spatial variations in PM <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2.5</sub> concentrations over the region than the traditional OLS model, which reveals relative homogeneous variations. Validation with ground-level PM <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2.5</sub> concentrations demonstrates that PM <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2.5</sub> concentrations predicted by the GWR model (R <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</sup> = 0.75, RMSE = 10 μg/m <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>3</sup> ) correlate better than those by the OLS model (R <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</sup> = 0.53, RMSE = 16 μg/m <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>3</sup> ). These results suggest that the GWR model offered a more reliable way for the prediction of spatial distribution of PM <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2.5</sub> concentrations over urban areas." @default.
• W2308284328 created "2016-06-24" @default.
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• W2308284328 date "2016-04-01" @default.
• W2308284328 modified "2023-10-18" @default.
• W2308284328 title "High-Resolution Satellite Mapping of Fine Particulates Based on Geographically Weighted Regression" @default.
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• W2308284328 doi "https://doi.org/10.1109/lgrs.2016.2520480" @default.
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