Evaluating an Enhanced Vegetation Condition Index (VCI) Based on VIUPD for Drought Monitoring in the Continental United States

Abstract

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.

Long‐term spatial and temporal variations of vegetative drought based on vegetation condition index in China

“…To characterize the spatial-temporal distribution of vegetative drought changes from 1981 to 2015, droughts were divided into four gradesnormal, slight, moderate, and severe-based on the literature concerning aridity classification standards (Guan et al 2008, Yan et al 2012, Sha et al 2013, Dutta et al 2015, Jiao et al 2016. The corresponding grades of the VCI values are shown in Table 1.…”

“…The VCI is sensitive to drought and can reduce or eliminate the impact that geographical location, ecological systems, and soil conditions have on the NDVI, making it an ideal indicator for large-scale drought monitoring (Kogan 1990, 1995a, b, Liu and Kogan 1996. Thus, the VCI has been extensively applied to drought monitoring and analysis (Domenikiotis et al 2004, 2005, Deng et al 2013, and its reliability has been verified by many studies; even the daily drought monitoring by the National Oceanic and Atmospheric Administration (NOAA) and the satellite remote sensing drought monitoring services of the China national satellite meteorological center are based on the VCI (Kogan 1997, Seiler et al 1998, Guo and Guan 2007, Dutta et al 2015, Jiao et al 2016. The goal of this paper is to analyze the spatial-temporal variations of droughts in China.…”

“…, Jiao et al. ). The goal of this paper is to analyze the spatial–temporal variations of droughts in China.…”

Multisource Data‐Based Integrated Agricultural Drought Monitoring in the Huai River Basin, China

“…Due to population growth and expansion of agricultural, energy, and industrial sectors, the demand for water resources has increased many fold and water scarcity has been occurring almost every year in many parts of the world (e.g., Mishra & Singh, ). Thus, droughts have been arousing increasing concerns and their monitoring and warning have been attracting a lot of attention in recent years (e.g., Bazrafshan, Nadi, & Ghorbani, ; Hao et al, ; Jiao et al, ; Zhao et al, ).…”

Monitoring drought vulnerability using multispectral indices observed from sequential remote sensing (Case Study: Tuy Phong, Binh Thuan, Vietnam)

“…VCI is generated by NDVI time series analysis that measures percent change of the difference of current NDVI and range of historical NDVI values. VCI can be applied individually in advance to monitor impact of drought on vegetation health (Peters et al 2002;Jiao et al 2016), but it is insufficient because VCI only reflects impact of moisture condition. Therefore, TCI, which indicates the influence of thermal condition, was proposed.…”