Scene- and pixel-level analysis of Landsat cloud coverage and image acquisition probability in South and Southeast Asia
文献类型：期刊论文
| 作者 | Yang, Yin; Li, Peng2 |
| 刊名 | INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
 |
| 出版日期 | 2023-09-01 |
| 卷号 | 123页码:13 |
| 关键词 | Landsat Cloud coverage Image acquisition probability Coarse -and -fine thresholding Scene and pixel -level South and Southeast Asia |
| ISSN号 | 1569-8432 |
| DOI | 10.1016/j.jag.2023.103477 |
| 通讯作者 | Li, Peng(lip@igsnrr.ac.cn) |
| 英文摘要 | Landsat has provided over five-decade Earth's observations including cloud cover (CC). However, scene-wide and/or pixel-level research on CC and image acquisition probability (IAP) still lags much behind. Scene-based analysis is often reported with arbitrary thresholds, while mechanism of cloud probability (CP) dynamics remains poorly investigated. Understanding Landsat cloud climatology is critical for better utilizing historical archives especially in the tropics. Here, South and Southeast Asia (SSEA) was selected to investigate the potential of a coarse-and-fine thresholding (CAFT) method in determining appropriate threshold of CC with all available Landsat-4/5/7/8 Thematic Mapper (TM), Enhanced TM Plus (ETM+), and Operational Land Imager (OLI) scenes (a total of 691,919) during 1984-2022. Then, OLI-based pixel CP was further examined, followed by correlation analysis between CC and climatic variables (i.e., temperature and precipitation). Main conclusions include: (1) the CAFT method holds promising potential in determining the precise CC threshold (24%) in SSEA. (2) Landsat IAP (nearly 40%) and CP (about 36%) show significant monthly, regional, and sensor variations across SSEA. (3) ETM+ performs the best with the highest IAP (>45%), while OLI tends to have larger IAPs in persistently cloudy area. (4) Significant correlation between CP and precipitation or temperature indicates that the roles of climate variables on CC differ geographically in South Asia and Southeast Asia. This study contributes to developing a universal and simple method to determine optimal thresholds for global CC research and understanding the interaction between CC and climate change. |
| WOS关键词 | AVAILABILITY ; SCIENCE ; MISSION ; RECORD ; PLAN |
| 资助项目 | National Natural Science Foundation of China[42371282] ; National Natural Science Foundation of China[41971242] ; Youth Innovation Promotion Association of the Chinese Academy of Sciences[2020055] |
| WOS研究方向 | Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:001165084400001 |
| 出版者 | ELSEVIER |
| 资助机构 | National Natural Science Foundation of China ; Youth Innovation Promotion Association of the Chinese Academy of Sciences |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/202818]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Li, Peng |
| 作者单位 | 1.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yang, Yin,Li, Peng. Scene- and pixel-level analysis of Landsat cloud coverage and image acquisition probability in South and Southeast Asia[J]. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,2023,123:13. |
| APA | Yang, Yin,&Li, Peng.(2023).Scene- and pixel-level analysis of Landsat cloud coverage and image acquisition probability in South and Southeast Asia.INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,123,13. |
| MLA | Yang, Yin,et al."Scene- and pixel-level analysis of Landsat cloud coverage and image acquisition probability in South and Southeast Asia".INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 123(2023):13. |
入库方式： OAI收割
来源：地理科学与资源研究所
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