气候变化领域集成服务门户(CCPortal): Multi-resolution satellite images bathymetry inversion of Bangda Co in the western Tibetan Plateau

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DOI	10.1080/01431161.2021.1970271
	Multi-resolution satellite images bathymetry inversion of Bangda Co in the western Tibetan Plateau
	Guo, Hengliang; Yang, Hong; Qiao, Baojin; Wang, Mengfei; Zhu, Liping
通讯作者	Qiao, BJ (通讯作者)
发表日期	2021
ISSN	0143-1161
EISSN	1366-5901
起始页码	8077
结束页码	8098
卷号	42 期号:21
英文摘要	Water depth is important information for lake research. However, it is difficult to obtain the depth distribution of a whole lake. The method of remote-sensing inversion by combining bathymetric data has been proved to be feasible. In order to improve the inversion accuracy, it is very crucial to research the optimal inversion model and the most suitable depth for modelling, and the most appropriate satellite images for the study area. In this study, we used the three kinds of multispectral image data (Sentinel-2, GF-1, and Landsat-8) to establish models by combining bathymetric data in Bangda Co, which is located in the northwestern Tibetan Plateau. We verified the two empirical models (Stumpf model and Lyzenga model) with the three bands of blue, green, and red in 0-30 m water depth. We created a multi-factor combination model (S-L model) to compare with a BP neural network model using three images in five different water depth ranges (0-10, 0-15, 0-20, 0-25, and 0-30 m). The results indicated that the S-L model with mean absolute error (MAE) of 3.09-4.70 m, which the accuracy was slightly better than that of the two empirical models (3.35-5.03 and 3.23-4.94 m). The MAE of the BP model over the five depth ranges was 0.71-2.41 m for Landsat-8, 1.02-3.53 m for GF-1, and 1.15-3.68 m for Sentinel-2, which was higher than the S-L model. For the five ranges of three images by using the BP model, both the accuracy of Sentinel-2 and GF-1 in the range of 0-15 m was higher, but Landsat-8 was the highest at 0-20 m among five ranges; the mean relative errors (MRE) were 19.5%, 18.7%, 13.1%, and the root-mean-square error (RMSE) were 1.82, 1.72, and 1.86 m, respectively. The best applicability of the three images was Landsat-8, followed by GF-1 and Sentinel-2 in this study. The results suggested that the freely available Sentinel-2, GF-1 and Landsat-8 images could be used to estimate water storage for a shallow lake by combining bathymetric data on the Tibetan Plateau.
关键词	WATER DEPTH NEURAL-NETWORK LAKES PROGNOSTICATION
语种	英语
WOS研究方向	Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:000704190200001
来源期刊	INTERNATIONAL JOURNAL OF REMOTE SENSING
来源机构	中国科学院青藏高原研究所
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/260182
推荐引用方式 GB/T 7714	Guo, Hengliang,Yang, Hong,Qiao, Baojin,et al. Multi-resolution satellite images bathymetry inversion of Bangda Co in the western Tibetan Plateau[J]. 中国科学院青藏高原研究所,2021,42(21).
APA	Guo, Hengliang,Yang, Hong,Qiao, Baojin,Wang, Mengfei,&Zhu, Liping.(2021).Multi-resolution satellite images bathymetry inversion of Bangda Co in the western Tibetan Plateau.INTERNATIONAL JOURNAL OF REMOTE SENSING,42(21).
MLA	Guo, Hengliang,et al."Multi-resolution satellite images bathymetry inversion of Bangda Co in the western Tibetan Plateau".INTERNATIONAL JOURNAL OF REMOTE SENSING 42.21(2021).