Retrieval and Validation of Aerosol Optical Depth by using the GF-1 Remote Sensing Data

3rd International Conference on Advances in Environment Research

生态环境科学;地球科学

Zhang, L.^1,2 ; Xu, S.^3 ; Wang, L.^1,2 ; Cai, K.^1,2 ; Ge, Q.^2

State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China^1

Computer and Information Engineering College, Henan University, Henan, China^2

School of Mathematics and Computer Science, Xinyang Vocational and Technical College, Xinyang, China^3

关键词: Aerosol optical depths;    Cloud contamination;    Deep blue algorithms;    Processing procedures;    Retrieval uncertainty;    Satellite retrieval;    Surface contribution;    Surface reflectance;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/68/1/012001/pdf
DOI  :  10.1088/1755-1315/68/1/012001

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Based on the characteristics of GF-1 remote sensing data, the method and data processing procedure to retrieve the Aerosol Optical Depth (AOD) are developed in this study. The surface contribution over dense vegetation and urban bright target areas are respectively removed by using the dark target and deep blue algorithms. Our method is applied for the three serious polluted Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD) regions. The retrieved AOD are validated by ground-based AERONET data from Beijing, Hangzhou, Hong Kong sites. Our results show that, 1) the heavy aerosol loadings are usually distributed in high industrial emission and dense populated cities, with the AOD value near 1. 2) There is a good agreement between satellite-retrievals and in-site observations, with the coefficient factors of 0.71 (BTH), 0.55 (YRD) and 0.54(PRD). 3) The GF-1 retrieval uncertainties are mainly from the impact of cloud contamination, high surface reflectance and assumed aerosol model.