Mapping dustfall distribution in urban areas using remote sensing and ground spectral data.

The aim of this study was to utilize remote sensing and ground-based spectral data to assess dustfall distribution in urban areas. The ground-based spectral data denoted that dust has a significant impact on spectral features. Dusty leaves have an obviously lower reflectance than clean leaves in the near-infrared bands (780-1,300 nm). The correlation analysis between dustfall weight and spectral reflectance showed that spectroscopy in the 350-2,500-nm region produced useful dust information and could assist in dust weight estimation. A back propagation (BP) neutral network model was generated using spectral response functions and integrated remote sensing data to assess dustfall weight in the city of Beijing. Compared with actual dustfall weight, validation of the results showed a satisfactory accuracy with a lower root mean square error (RMSE) of 3.6g/m(2). The derived dustfall distribution in Beijing indicated that dustfall was easily accumulated and increased in the south of the city. In addition, our results showed that construction sites and low-rise buildings with inappropriate land use were two main sources of dust pollution. This study offers a low-cost and effective method for investigating detailed dustfall in an urban environment. Environmental authorities may use this method for deriving dustfall distribution maps and pinpointing the sources of pollutants in urban areas.