Combining DMSP/OLS Nighttime Light with Echo State Network for Prediction of Daily PM2.5 Average Concentrations in Shanghai, China

Atmosphere

Zhao Xu¹  Xiaopeng Xia¹  Xiangnan Liu¹  Zhiguang Qian² 

[1] School of Information Engineering, China University of Geosciences, Beijing 100083, China; E-Mails:;Qinhuangdao City Environmental Protection Bureau, Qinhuangdao 066000, China; E-Mail:

关键词: PM_2.5;    DMSP/OLS;    nighttime light;    NOAA;    echo state network;    Gaussian fitting;   

DOI  :  10.3390/atmos6101507

来源: mdpi

【 摘 要 】

The objective of this study is to investigate the potential of nighttime light data, acquired with Defense Meteorological Satellite Program Operational Linescan System (DMSP/OLS) owned by National Oceanic and Atmospheric Administration (NOAA), in predicting urban daily particulate matter (PM)_2.5 with an aerodynamic diameter of less than 2.5 µm average concentrations. To achieve the purpose, we firstly extracted two night light indices, the Nighttime Light Intensity Index (NLII) and the Nighttime Saturated Light Area Index (NSLAI) from DMSP/OLS images. Through Gaussian fitting of the relationship between the indices and the daily PM_2.5 concentrations data released by the government, we found that the intraday nighttime light indices were all more relevant with the PM_2.5 average concentrations of the next day in Shanghai. Therefore, the 56 sets of data, the light indices were collected from 3 November 2013 to 28 December 2013, the daily PM_2.5 concentrations data were collected from 4 November 2013 to 29 December 2013, and these were divided into two parts. The first 40 sets were used for training the model of echo state network (ESN). The last 16 sets were used for testing. The value of R² of predicted results was as high as 0.6318. In summary, the effectiveness of nighttime light data that used for the prediction of urban daily PM_2.5 average concentrations was verified in this study.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.