Impacts of AOD Correction and Spatial Scale on the Correlation between High-Resolution AOD from Gaofen-1 Satellite and In Situ PM2.5 Measurements in Shenzhen City, China
Abstract
:1. Introduction
2. Study Area, Materials, and Methods
2.1. Study Area
2.2. Materials
2.2.1. Remote Sensing Data from the GF-1 Satellite
2.2.2. In Situ PM2.5 Measurement Data
2.2.3. Meteorological Station Data
2.2.4. Planet Boundary Layer Height Data
2.2.5. Terra MODIS 3-km DT AOD Data
2.3. Methods
2.3.1. GF-1 AOD Retrieval and Validation
2.3.2. Extraction of AOD at Different Spatial Scales
2.3.3. Vertical and Humidity Corrections of AOD
3. Results
3.1. Descriptive Statistics
3.2. Retrieved and Validated GF-1 AOD
3.3. Pearson Correlation between GF-1 AOD and PM2.5 Concentrations
4. Discussion
4.1. AOD Correction Effect on Correlations between AOD and PM2.5 Concentrations
4.2. Spatial Scale Effect on Correlations between AOD and PM2.5 Concentrations
4.3. Limitations and Future Research Directions
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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2015–2017 (N = 253) | Spring (N = 47) | Summer (N = 55) | Autumn (N = 42) | Winter (N = 109) | ||
---|---|---|---|---|---|---|
PM2.5 concentrations (μg/m3) | mean | 43 | 29 | 32 | 36 | 56 |
S.D. | 22.6 | 8.77 | 23.9 | 11.1 | 22.0 | |
kurtosis | 2.29 | −0.28 | −1.38 | −0.96 | 3.20 | |
skewness | 1.03 | −0.80 | 0.58 | 0.01 | 1.41 | |
PBLH (m) | mean | 1032 | 1036 | 1197 | 1036 | 945 |
S.D. | 177.8 | 133.0 | 52.64 | 117.1 | 195.3 | |
kurtosis | −0.77 | −0.64 | −1.34 | −1.71 | −1.30 | |
skewness | −0.62 | −0.71 | −0.40 | −0.15 | 0.02 | |
RH (%) | mean | 50 | 48 | 59 | 57 | 44 |
S.D. | 14.0 | 12.8 | 7.02 | 6.26 | 15.9 | |
kurtosis | −0.46 | −0.74 | 0.97 | 0.80 | −0.91 | |
skewness | −0.41 | 0.28 | 0.54 | 0.84 | 0.20 |
O_AOD | |||||
---|---|---|---|---|---|
R | mean | 0.292 | 0.297 | 0.362 | 0.367 |
S.D. | 0.016 | 0.025 | 0.011 | 0.018 | |
minimum | 0.234 | 0.264 | 0.334 | 0.340 | |
maximum | 0.329 | 0.374 | 0.392 | 0.423 | |
p values | mean | 2.18 × 10−4 | 5.76 × 10−5 | 6.61 × 10−6 | 2.80 × 10−6 |
minimum | 1.10 × 10−6 | 2.53 × 10−7 | 2.94 × 10−9 | 8.65 × 10−10 | |
maximum | 1.03 × 10−2 | 2.93 × 10−3 | 6.29 × 10−4 | 2.16 × 10−4 |
Spatial Scales | O_AOD | ||||
---|---|---|---|---|---|
40–1000 m | mean | 0.281 | 0.309 | 0.365 | 0.382 |
S.D. | 0.026 | 0.024 | 0.018 | 0.020 | |
C.V. | 9.25% | 7.77% | 4.93% | 5.23% | |
1020–2000 m | mean | 0.308 | 0.324 | 0.373 | 0.384 |
S.D. | 0.008 | 0.008 | 0.007 | 0.007 | |
C.V. | 2.60% | 2.47% | 1.88% | 1.82% | |
2020–3000 m | mean | 0.298 | 0.306 | 0.363 | 0.371 |
S.D. | 0.007 | 0.012 | 0.004 | 0.007 | |
C.V. | 2.34% | 3.92% | 1.10% | 1.88% | |
3020–4000 m | mean | 0.284 | 0.273 | 0.356 | 0.352 |
S.D. | 0.004 | 0.003 | 0.002 | 0.002 | |
C.V. | 1.41% | 1.10% | 0.56% | 0.57% | |
4020–5000 m | mean | 0.288 | 0.272 | 0.353 | 0.346 |
S.D. | 0.004 | 0.006 | 0.003 | 0.005 | |
C.V. | 1.39% | 2.21% | 0.85% | 1.45% |
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Wu, J.; Liang, J.; Zhou, L.; Yao, F.; Peng, J. Impacts of AOD Correction and Spatial Scale on the Correlation between High-Resolution AOD from Gaofen-1 Satellite and In Situ PM2.5 Measurements in Shenzhen City, China. Remote Sens. 2019, 11, 2223. https://doi.org/10.3390/rs11192223
Wu J, Liang J, Zhou L, Yao F, Peng J. Impacts of AOD Correction and Spatial Scale on the Correlation between High-Resolution AOD from Gaofen-1 Satellite and In Situ PM2.5 Measurements in Shenzhen City, China. Remote Sensing. 2019; 11(19):2223. https://doi.org/10.3390/rs11192223
Chicago/Turabian StyleWu, Jiansheng, Jingtian Liang, Liguo Zhou, Fei Yao, and Jian Peng. 2019. "Impacts of AOD Correction and Spatial Scale on the Correlation between High-Resolution AOD from Gaofen-1 Satellite and In Situ PM2.5 Measurements in Shenzhen City, China" Remote Sensing 11, no. 19: 2223. https://doi.org/10.3390/rs11192223
APA StyleWu, J., Liang, J., Zhou, L., Yao, F., & Peng, J. (2019). Impacts of AOD Correction and Spatial Scale on the Correlation between High-Resolution AOD from Gaofen-1 Satellite and In Situ PM2.5 Measurements in Shenzhen City, China. Remote Sensing, 11(19), 2223. https://doi.org/10.3390/rs11192223