气候变化领域集成服务门户(CCPortal): Development and validation of a new MODIS snow-cover-extent product over China

CCPortal

DOI	10.5194/hess-26-1937-2022
	Development and validation of a new MODIS snow-cover-extent product over China
	Hao, Xiaohua; Huang, Guanghui; Zheng, Zhaojun; Sun, Xingliang; Ji, Wenzheng; Zhao, Hongyu; Wang, Jian; Li, Hongyi; Wang, Xiaoyan
通讯作者	Huang, GH (通讯作者)，Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Heihe Remote Sensing Expt Res Stn, Lanzhou 730000, Peoples R China. ; Huang, GH (通讯作者)，Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Key Lab Remote Sensing Gansu Prov, Lanzhou 730000, Peoples R China. ; Huang, GH (通讯作者)，Lanzhou Univ, Coll Earth & Environm Sci, Lanzhou 730000, Peoples R China.
发表日期	2022
ISSN	1027-5606
EISSN	1607-7938
起始页码	1937
结束页码	1952
卷号	26 期号:8
英文摘要	Based on MOD09GA/MYD09GA surface reflectance data, a new MODIS snow-cover-extent (SCE) product from 2000 to 2020 over China has been produced by the Northwest Institute of Eco-Environment and Resources (NIEER), Chinese Academy of Sciences. The NIEER MODIS SCE product contains two preliminary clear-sky SCE datasets - Terra-MODIS and Aqua-MODIS SCE datasets and a final daily cloud-gap-filled (CGF) SCE dataset. The first two datasets are generated mainly through optimizing snow-cover discriminating rules over land-cover types, and the latter dataset is produced after a series of gapfilling processes such as aggregating the two preliminary datasets, reducing cloud gaps with adjacent information in space and time, and eliminating all gaps with auxiliary data. The validation against 362 China Meteorological Administration (CMA) stations shows that during snow seasons the overall accuracy (OA) values of the three datasets are larger than 93 %, all of the omission error (OE) values are constrained within 9 %, and all of the commission error (CE) values are constrained within 10 %. Bias values of 0.98, 1.02, and 1.03 demonstrate on a whole that there is no significant overestimation nor a significant underestimation. Based on the same ground reference data, we found that the new product accuracies are obviously higher than standard MODIS snow products, especially for Aqua-MODIS and CGF SCE. For example, compared with the CE of 23.78 % that the MYD10A1 product shows, the CE of the new Aqua-MODIS SCE dataset is 6.78 %; the OA of the new CGF SCE dataset is up to 93.15 % versus 89.54 % of MOD10A1F product and 84.36 % of MYD10A1F product. Besides, as expected, snow discrimination in forest areas is also improved significantly. An isolated validation at four forest CMA stations demonstrates that the OA has increased by 3-10 percentage points, the OE has dropped by 1-8 percentage points, and the CE has dropped by 4-21 percentage points. Therefore, our product has virtually provided more reliable snow knowledge over China; thereby, it can better serve for hydrological, climatic, environmental, and other related studies there.
关键词	REMOTE-SENSING DATA ACCURACY ASSESSMENT RIVER-BASIN ALGORITHM FORESTS AREA
语种	英语
WOS研究方向	Geology ; Water Resources
WOS类目	Geosciences, Multidisciplinary ; Water Resources
WOS记录号	WOS:000783502000001
来源期刊	HYDROLOGY AND EARTH SYSTEM SCIENCES
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/254030
作者单位	[Hao, Xiaohua; Huang, Guanghui; Sun, Xingliang; Ji, Wenzheng; Zhao, Hongyu; Wang, Jian; Li, Hongyi] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Heihe Remote Sensing Expt Res Stn, Lanzhou 730000, Peoples R China; [Hao, Xiaohua; Huang, Guanghui; Wang, Jian; Li, Hongyi] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Key Lab Remote Sensing Gansu Prov, Lanzhou 730000, Peoples R China; [Huang, Guanghui; Wang, Xiaoyan] Lanzhou Univ, Coll Earth & Environm Sci, Lanzhou 730000, Peoples R China; [Zheng, Zhaojun] China Meteorol Adm, Natl Satellite Meteorol Ctr, Beijing 100081, Peoples R China; [Zheng, Zhaojun] China Meteorol Adm, Key Lab Radiometr Calibrat & Validat Environm Sat, Beijing 100081, Peoples R China; [Sun, Xingliang] Lanzhou Jiaotong Univ, Engn Lab Natl Geog State Monitoring, Lanzhou 730070, Peoples R China
推荐引用方式 GB/T 7714	Hao, Xiaohua,Huang, Guanghui,Zheng, Zhaojun,et al. Development and validation of a new MODIS snow-cover-extent product over China[J]. 中国科学院西北生态环境资源研究院,2022,26(8).
APA	Hao, Xiaohua.,Huang, Guanghui.,Zheng, Zhaojun.,Sun, Xingliang.,Ji, Wenzheng.,...&Wang, Xiaoyan.(2022).Development and validation of a new MODIS snow-cover-extent product over China.HYDROLOGY AND EARTH SYSTEM SCIENCES,26(8).
MLA	Hao, Xiaohua,et al."Development and validation of a new MODIS snow-cover-extent product over China".HYDROLOGY AND EARTH SYSTEM SCIENCES 26.8(2022).