High-Spatial-Resolution Aerosol Optical Properties Retrieval Algorithm Using Chinese High-Resolution Earth Observation Satellite i
文献类型：期刊论文
| 作者 | Bao, Fangwen1; Gu, Xingfa1; Cheng, Tianhai1; Wang, Ying1; Guo, Hong1; Chen, Hao1; Wei, Xi1; Xiang, Kunsheng1; Li, Yinong1 |
| 刊名 | IEEE Transactions on Geoscience and Remote Sensing
 |
| 出版日期 | 2016 |
| 卷号 | 54期号:9页码:5544-5552 |
| 关键词 | POL-INSAR DATA FOREST BIOMASS PARAMETER-ESTIMATION HEIGHT RADAR |
| 英文摘要 | The high-spatial-resolution aerosol retrieval algorithm using Chinese High-Resolution Earth Observation Satellite I (GF-1) wide-field images is developed, which retrieves the aerosol optical depth (AOD) over China for studying the impact of aerosol on climatic and environmental change. The algorithm is based on the red/blue surface reflectance correlations and the lookup table method. To reduce the enormous relative error caused by the constant surface reflectance relationship in the retrieval algorithm, the correlation is parameterized as a function of low, medium, and high values of normalized difference vegetation index (NDVI). Three linear relationships are simulated using MODIS BRDF-adjusted reflectance products (MCD43A4), and MODIS NDVI products are used to ascertain the value of NDVI. By applying the present algorithm to GF-1 images, two different aerosol cases of clear and turbid are analyzed to test the algorithm. Compared with the 10-km MODIS aerosol properties productions, the GF-1 retrieved AOD by our algorithm revealed a significant correlation coefficient with MODIS Dark Target AOD $(R=0.912)$ and Deep Blue AOD $(R=0.895)$. Otherwise, the retrieved AOD results are found to be highly correlated with Aerosol Robotic Network (AERONET) sunphotometer observations $(R=0.931)$. Compared with the results relying on the MODIS surface reflectance model, preliminary validation is encouraging that the method based on our updated surface reflectance assumptions successfully improved the accuracy, particularly under the clear sky background and over bright surface. © 2016 IEEE. |
| 学科主题 | Geochemistry & Geophysics; Engineering; Remote Sensing; Imaging Science & Photographic Technology |
| 类目[WOS] | Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:20162402498692 |
| 源URL | [http://ir.radi.ac.cn/handle/183411/39186]  |
| 专题 | 遥感与数字地球研究所_SCI/EI期刊论文_期刊论文 |
| 作者单位 | 1. State Key Laboratory of Remote Sensing, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 2.100101, China 3. University of Chinese Academy of Sciences, Beijing 4.100049, China 5. University of New South Wales, Sydney 6.2052, Australia 7. Beijing Aerospace TITAN Technology Company, Beijing 8.100070, China |
| 推荐引用方式 GB/T 7714 | Bao, Fangwen,Gu, Xingfa,Cheng, Tianhai,et al. High-Spatial-Resolution Aerosol Optical Properties Retrieval Algorithm Using Chinese High-Resolution Earth Observation Satellite i[J]. IEEE Transactions on Geoscience and Remote Sensing,2016,54(9):5544-5552. |
| APA | Bao, Fangwen.,Gu, Xingfa.,Cheng, Tianhai.,Wang, Ying.,Guo, Hong.,...&Li, Yinong.(2016).High-Spatial-Resolution Aerosol Optical Properties Retrieval Algorithm Using Chinese High-Resolution Earth Observation Satellite i.IEEE Transactions on Geoscience and Remote Sensing,54(9),5544-5552. |
| MLA | Bao, Fangwen,et al."High-Spatial-Resolution Aerosol Optical Properties Retrieval Algorithm Using Chinese High-Resolution Earth Observation Satellite i".IEEE Transactions on Geoscience and Remote Sensing 54.9(2016):5544-5552. |
入库方式： OAI收割
来源：遥感与数字地球研究所
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