Estimating Spatio-Temporal Variations of PM2.5 Concentrations Using VIIRS-Derived AOD in the Guanzhong Basin, China
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Collection
2.2.1. Ground-Based PM2.5 Concentration Data
2.2.2. Satellite-Retrieved AOD Products
2.2.3. Meteorological Parameters
2.2.4. Land-Cover and Population Data
2.2.5. Sun–Sky Radiometer Observation Network (SONET) Data
2.2.6. Data Integration
2.3. Model Structure and Development
2.4. Model Validation for Prediction
3. Results
3.1. Validation of VIIRS AOD and Quality Flag Selection
3.2. Data Overview and Characteristics
3.3. Predictor Factors Analysis
3.4. Model Validation
3.5. Comparison of the GWR and GAM Model
3.6. Temporal and Spatial Distributions of Predicted PM2.5
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Flags | Values | Quality | Conditions |
---|---|---|---|
3 | 11 | High | Number of good-quality pixel AOD retrievals >16 (1/4 the total number of pixels in aggregated horizontal cell) |
2 | 10 | Medium | Number of good-quality retrievals ≤16 and the number of good/degraded-quality retrievals ≥16 |
1 | 01 | Low | Number of good/degraded-quality retrievals <16 |
0 | 00 | Not produced | No good/degraded-quality pixel retrievals Neither land- nor sea water-dominant Ellipsoid fill in the geolocation Night scan Solar zenith angle >80° |
Coefficient (bi) | p-Value | |
---|---|---|
Intercept | 58.848 | 0.000 |
AOD (unitless) | 46.290 | 0.000 |
NDVI (unitless) | −10.282 | 0.003 |
POP (ten thousand people/km2) | 1.478 | 0.192 a |
RH (%) | −35.053 | 0.000 |
PBLH (m) | −0.009 | 0.087 b |
WSU (m/s) | 0.956 | 0.000 |
TP (°C) | 0.057 | 0.000 |
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Zhang, K.; de Leeuw, G.; Yang, Z.; Chen, X.; Su, X.; Jiao, J. Estimating Spatio-Temporal Variations of PM2.5 Concentrations Using VIIRS-Derived AOD in the Guanzhong Basin, China. Remote Sens. 2019, 11, 2679. https://doi.org/10.3390/rs11222679
Zhang K, de Leeuw G, Yang Z, Chen X, Su X, Jiao J. Estimating Spatio-Temporal Variations of PM2.5 Concentrations Using VIIRS-Derived AOD in the Guanzhong Basin, China. Remote Sensing. 2019; 11(22):2679. https://doi.org/10.3390/rs11222679
Chicago/Turabian StyleZhang, Kainan, Gerrit de Leeuw, Zhiqiang Yang, Xingfeng Chen, Xiaoli Su, and Jiashuang Jiao. 2019. "Estimating Spatio-Temporal Variations of PM2.5 Concentrations Using VIIRS-Derived AOD in the Guanzhong Basin, China" Remote Sensing 11, no. 22: 2679. https://doi.org/10.3390/rs11222679
APA StyleZhang, K., de Leeuw, G., Yang, Z., Chen, X., Su, X., & Jiao, J. (2019). Estimating Spatio-Temporal Variations of PM2.5 Concentrations Using VIIRS-Derived AOD in the Guanzhong Basin, China. Remote Sensing, 11(22), 2679. https://doi.org/10.3390/rs11222679