Dr. Jing Guo Profile

Dr. Jing Guo

at Institute of Remote Sensing and Digital Earth

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Author

Publications (3)

Proceedings Article | 23 September 2013 Paper

Trend analysis of the aerosol optical depth over China using fusion of MODIS and MISR aerosol products via adaptive weighted estimate algorithm

Jing Guo, Xingfa Gu, Tao Yu, Tianhai Cheng, Hao Chen, Donghai Xie

Proceedings Volume 8866, 88661X (2013) https://doi.org/10.1117/12.2024687

KEYWORDS: Aerosols, MODIS, Sensors, Data fusion, Atmospheric particles, Satellites, Clouds, Atmospheric modeling, Adaptive optics, Solar radiation models

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SPIE Journal Paper | 21 August 2013 Open Access

Latest decade’s spatial–temporal properties of aerosols over China based on Multiangle Imaging SpectroRadiometer observations

Xingfa Gu, Jing Guo, Tianhai Cheng, Tao Yu, Hao Chen, Donghai Xie, Yu Wu

JARS, Vol. 7, Issue 01, 073518, (August 2013) https://doi.org/10.1117/12.10.1117/1.JRS.7.073518

KEYWORDS: Aerosols, MODIS, Atmospheric particles, Satellites, Atmospheric modeling, Climate change, Statistical analysis, Sensors, Atmospheric optics, Reflection

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The analysis of the spatial–temporal variability and trends of aerosols over China based on ∼11 years (February 2000 to December 2010) of Terra-Multiangle Imaging SpectroRadiometer (MISR) Level 3 aerosol products is the focus. The study shows that the MISR aerosol optical depth (AOD) is in good agreement with corresponding AOD from AERONET stations and suggests that MISR aerosol products have higher applicability compared with MODIS AOD products over China. The spatial–temporal distribution and trends for annual and seasonal AOD values over the middle and eastern regions of China are the main focus. The results of our analysis show the significant characteristics and seasonal variation of the aerosol distribution over the study areas. The seasonal distribution in AOD over the study areas is not consistent with the MODIS data. An insignificant trend (5.3%) is observed over the whole study area during the study period. The larger positive tendencies are found in the Yangtze River Delta and the Pearl River Delta (PRD); the values increased by 24.4% and 18% and are considered to be significant with a confidence level of >95% . However, in contrast to the recently reported negligible AOD trends of 0.002 per decade using MODIS data over Sichuan, significant increasing trends of 0.046 per 11 years for MISR over the same areas have been measured. The analysis of seasonal variation revealed the seasonal trend in the AOD and the main types of aerosols. During spring, the largest increasing trend (30.2%) is observed in the PRD with a stable composition of fine and coarse aerosols. A pronounced decreasing trend is found over Shanxi and decreased by −18.7% in spring during the period, which has not been previously reported. MODIS-Terra currently shows artificial negative AOD trends over land. Therefore, trends derived from MODIS-Terra may not reflect the realistic decadal aerosol changes and variability. The study shows that seasonal distribution and trend analyses are inconsistent when using MISR AOD products and MODIS AOD products over study areas, which indicates that the analysis of aerosol variation using MISR sensors is necessary.

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Proceedings Article | 14 September 2011 Paper

Latest decade's spatial-temporal properties of aerosols over China

Xingfa Gu, Tao Yu, Tianhai Cheng, Guo Jing, Hao Chen, Donghai Xie

Proceedings Volume 8153, 81531G (2011) https://doi.org/10.1117/12.895300

KEYWORDS: Aerosols, MODIS, Climatology, Satellites, Atmospheric particles, Environmental sensing, Clouds, Remote sensing, Robotics, Satellite imaging

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