气候变化领域集成服务门户(CCPortal): Spatial-Temporal Distribution of the Freeze-Thaw Cycle of the Largest Lake (Qinghai Lake) in China Based on Machine Learning and MODIS from 2000 to 2020

CCPortal

DOI	10.3390/rs13091695
	Spatial-Temporal Distribution of the Freeze-Thaw Cycle of the Largest Lake (Qinghai Lake) in China Based on Machine Learning and MODIS from 2000 to 2020
	Han, Weixiao; Huang, Chunlin; Gu, Juan; Hou, Jinliang; Zhang, Ying
通讯作者	Han, WX (通讯作者)，Chinese Acad Sci, Key Lab Remote Sensing Gansu Prov, Heihe Remote Sensing Expt Res Stn, Northwest Inst Ecoenvironm & Resources, Lanzhou 730000, Peoples R China.
发表日期	2021
EISSN	2072-4292
卷号	13 期号:9
英文摘要	The lake ice phenology variations are vital for the land-surface-water cycle. Qinghai Lake is experiencing amplified warming under climate change. Based on the MODIS imagery, the spatio-temporal dynamics of the ice phenology of Qinghai Lake were analyzed using machine learning during the 2000/2001 to 2019/2020 ice season, and cloud gap-filling procedures were applied to reconstruct the result. The results showed that the overall accuracy of the water-ice classification by random forest and cloud gap-filling procedures was 98.36% and 92.56%, respectively. The annual spatial distribution of the freeze-up and break-up dates ranged primarily from DOY 330 to 397 and from DOY 70 to 116. Meanwhile, the decrease rates of freeze-up duration (DFU), full ice cover duration (DFI), and ice cover duration (DI) were 0.37, 0.34, and 0.13 days/yr., respectively, and the duration was shortened by 7.4, 6.8, and 2.6 days over the past 20 years. The increased rate of break-up duration (DBU) was 0.58 days/yr. and the duration was lengthened by 11.6 days. Furthermore, the increase in temperature resulted in an increase in precipitation after two years; the increase in precipitation resulted in the increase in DBU and decrease in DFU in corresponding years, and decreased DI and DFI after one year.
关键词	SENTINEL-2 SURFACE REFLECTANCE SNOW COVER PRODUCTS ICE COVER RANDOM FOREST TIBETAN PLATEAU CLIMATE-CHANGE GLOBAL LAKE WATER ALGORITHM PHENOLOGY
英文关键词	machine learning; Qinghai Lake; MODIS; Google Earth Engine; ice phenology
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:000650737800001
来源期刊	REMOTE SENSING
来源机构	中国科学院西北生态环境资源研究院
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/253845
作者单位	[Han, Weixiao; Huang, Chunlin; Hou, Jinliang; Zhang, Ying] Chinese Acad Sci, Key Lab Remote Sensing Gansu Prov, Heihe Remote Sensing Expt Res Stn, Northwest Inst Ecoenvironm & Resources, Lanzhou 730000, Peoples R China; [Han, Weixiao] Univ Chinese Acad Sci, Beijing 100049, Peoples R China; [Gu, Juan] Lanzhou Univ, Key Lab Western Chinas Environm Syst, Minist Educ, Lanzhou 730000, Peoples R China
推荐引用方式 GB/T 7714	Han, Weixiao,Huang, Chunlin,Gu, Juan,et al. Spatial-Temporal Distribution of the Freeze-Thaw Cycle of the Largest Lake (Qinghai Lake) in China Based on Machine Learning and MODIS from 2000 to 2020[J]. 中国科学院西北生态环境资源研究院,2021,13(9).
APA	Han, Weixiao,Huang, Chunlin,Gu, Juan,Hou, Jinliang,&Zhang, Ying.(2021).Spatial-Temporal Distribution of the Freeze-Thaw Cycle of the Largest Lake (Qinghai Lake) in China Based on Machine Learning and MODIS from 2000 to 2020.REMOTE SENSING,13(9).
MLA	Han, Weixiao,et al."Spatial-Temporal Distribution of the Freeze-Thaw Cycle of the Largest Lake (Qinghai Lake) in China Based on Machine Learning and MODIS from 2000 to 2020".REMOTE SENSING 13.9(2021).