Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.3390/rs14081935 |
Evaluation and Comparison of MODIS C6 and C6.1 Deep Blue Aerosol Products in Arid and Semi-Arid Areas of Northwestern China | |
Yang, Leiku; Tian, Xinyao; Liu, Chao; Ji, Weiqian; Zheng, Yu; Liu, Huan; Lu, Xiaofeng; Che, Huizheng | |
通讯作者 | Yang, LK |
来源期刊 | REMOTE SENSING
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EISSN | 2072-4292 |
出版年 | 2022 |
卷号 | 14期号:8 |
英文摘要 | The Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue (DB) algorithm was developed for aerosol retrieval on bright surfaces. Although the global validation accuracy of the DB product is satisfactory, there are still some regions found to have very low accuracy. To this end, DB has updated the surface database in the latest version of the Collection 6.1 (C6.1) algorithm. Some studies have shown that DB aerosol optical depth (AOD) of the old version Collection 6 (C6) has been seriously underestimated in Northwestern China. However, the status of the new version of the C6.1 product in this region is still unknown. This study aims to comprehensively evaluate the performance of the MODIS DB product in Northwestern China. The DB AOD with high quality (Quality Flag = 2 or 3) was selected to validate against the 23 sites from the China Aerosol Remote Sensing Network (CARSNET) and Aerosol Robotic Network (AERONET) during the period 2002-2014. By the overall analysis, the results indicate that both C6 and C6.1 show significant underestimation with a large fraction of more than 54% of collocations falling below the Expected Error (EE = +/-(0.05 + 20% AOD(ground))) envelope and with a large negative Mean Bias (MB) of less than -0.14. Furthermore, the new C6.1 products failed to achieve reasonable improvements in the region of Northwestern China. Besides, C6.1 has slightly fewer collocations than C6 due that some pixels with systematic biases have been removed from the new surface reflectance database. From the analysis of the site scale, the scatter plot of C6.1 is similar to that of C6 in most sites. Furthermore, a significant underestimation of DB AOD was observed at most sites, with the most severe underestimation at two sites located in the Taklimakan Desert region. Among 23 sites in Northwestern China, there are only two sites where C6.1 has largely improved the underestimation of C6. Furthermore, it is interesting to note that there are also two sites where the accuracy of the new C6.1 has declined. Moreover, it is surprising that there is one site where a large overestimation was observed in C6 and improved in C6.1. Additionally, we found a constant value of about 0.05 for both C6 and C6.1 at several sites with low aerosol loading, which is an obvious artifact. The significant improvements of C6.1 were observed in the Middle East and Central Asia but not in most sites of Northwestern China. The results of this study will be beneficial to further improvements in the MODIS DB algorithm. |
英文关键词 | MODIS Deep Blue CARSNET AERONET Northwestern China |
类型 | Article |
语种 | 英语 |
开放获取类型 | gold |
收录类别 | SCI-E |
WOS记录号 | WOS:000787399800001 |
WOS关键词 | OPTICAL DEPTH ; AOD VARIABILITY ; SAUDI-ARABIA ; DARK TARGET ; AERONET ; LAND ; VALIDATION ; ALGORITHMS ; CLIMATOLOGY ; PERFORMANCE |
WOS类目 | Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology |
WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/394134 |
推荐引用方式 GB/T 7714 | Yang, Leiku,Tian, Xinyao,Liu, Chao,et al. Evaluation and Comparison of MODIS C6 and C6.1 Deep Blue Aerosol Products in Arid and Semi-Arid Areas of Northwestern China[J],2022,14(8). |
APA | Yang, Leiku.,Tian, Xinyao.,Liu, Chao.,Ji, Weiqian.,Zheng, Yu.,...&Che, Huizheng.(2022).Evaluation and Comparison of MODIS C6 and C6.1 Deep Blue Aerosol Products in Arid and Semi-Arid Areas of Northwestern China.REMOTE SENSING,14(8). |
MLA | Yang, Leiku,et al."Evaluation and Comparison of MODIS C6 and C6.1 Deep Blue Aerosol Products in Arid and Semi-Arid Areas of Northwestern China".REMOTE SENSING 14.8(2022). |
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