Evaluating an enhanced vegetation condition index (VCI) based on VIUPD for drought monitoring in the continental United States

	Evaluating an enhanced vegetation condition index (VCI) based on VIUPD for drought monitoring in the continental United States
	Jiao, Wenzhe 1; Zhang, Lifu 1; Chang, Qing 1; Fu, Dongjie 1; Cen, Yi 1; Tong, Qingxi 1
刊名	Remote Sensing
	2016
卷号	8 期号:3
关键词	LEAF-AREA INDEX SCATTERING POWER DECOMPOSITION SATELLITE SAR SENSORS MICROWAVE BACKSCATTERING MOISTURE ESTIMATION SOIL-MOISTURE TIME-SERIES X-BAND VEGETATION PARAMETERS
通讯作者	Zhang, Lifu (zhanglf@radi.ac.cn)
英文摘要	Drought is a complex hazard, and it has an impact on agricultural, ecological, and socio-economic systems. The vegetation condition index (VCI), which is derived from remote-sensing data, has been widely used for drought monitoring. However, VCI based on the normalized difference vegetation index (NDVI) does not perform well in certain circumstances. In this study, we examined the utility of the vegetation index based on the universal pattern decomposition method (VIUPD) based VCI for drought monitoring in various climate divisions across the continental United States (CONUS). We compared the VIUPD-derived VCI with the NDVI-derived VCI in various climate divisions and during different sub-periods of the growing season. It was also compared with other remote-sensing-based drought indices, such as the temperature condition index (TCI), precipitation condition index (PCI) and the soil moisture condition index (SMCI). The VIUPD-derived VCI had stronger correlations with long-term in situ drought indices, such as the Palmer Drought Severity Index (PDSI) and the standardized precipitation index (SPI-3, SPI-6, SPI-9, and SPI-12) than did the NDVI-derived VCI, and other indices, such as TCI, PCI and SMCI. The VIUPD has considerable potential for drought monitoring. As VIUPD can make use of the information from all the observation bands, the VIUPD-derived VCI can be regarded as an enhanced VCI. © 2016 by the authors.
学科主题	Remote Sensing
类目[WOS]	Remote Sensing
收录类别	SCI ; EI
语种	英语
WOS记录号	WOS:20161302146046
内容类型	期刊论文
源URL	[http://ir.radi.ac.cn/handle/183411/39224]
专题	遥感与数字地球研究所_SCI/EI期刊论文_期刊论文
作者单位	1. State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academic of Science, Beijing, China 2. University of Chinese Academy of Science, Beijing No. 19A Yuquan Road, Beijing, China 3. Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China
推荐引用方式 GB/T 7714	Jiao, Wenzhe,Zhang, Lifu,Chang, Qing,et al. Evaluating an enhanced vegetation condition index (VCI) based on VIUPD for drought monitoring in the continental United States[J]. Remote Sensing,2016,8(3).
APA	Jiao, Wenzhe,Zhang, Lifu,Chang, Qing,Fu, Dongjie,Cen, Yi,&Tong, Qingxi.(2016).Evaluating an enhanced vegetation condition index (VCI) based on VIUPD for drought monitoring in the continental United States.Remote Sensing,8(3).
MLA	Jiao, Wenzhe,et al."Evaluating an enhanced vegetation condition index (VCI) based on VIUPD for drought monitoring in the continental United States".Remote Sensing 8.3(2016).