Agricultural Drought Indices - US Department of Agriculture

have been adopted because of the availability of the required spectral data from instruments such
as AVHRR and MODIS, which are easily accessible and available for most parts of the world, and
their demonstrated utility for monitoring vegetation conditions.
Normalized Difference Vegetation Index (NDVI)
The Normalized Difference Vegetation Index (NDVI) (Rouse et al. 1974) has been the most widely
used VI for agricultural drought monitoring over the past 20+ years. The NDVI is calculated from
the following equation:
NDVI = (NIR – Red) / (NIR + Red)
where Red and NIR correspond to the visible red and NIR bands, respectively. The NDVI
calculation capitalizes on the differential response of the visible red (decreasing reflectance due to
chlorophyll absorption) and NIR (increasing reflectance from the spongy mesophyll layer)
wavelength regions to healthy green vegetation. Theoretically, NDVI values can range from -1.0 to
+1.0, but globally most observed NDVI values range from near 0.0 for bare surfaces to
approximately 0.9 for densely vegetated locations. The value of NDVI for vegetation monitoring
has been well established, as it has been found to have a strong relationship with biophysical
vegetation parameters such as green biomass and leaf area index (LAI) (Asrar et al. 1989, Baret
and Guyot 1991), as well as precipitation and ET (Ji and Peters 2003). Most satellite-based
remote sensing instruments designed for terrestrial applications include red and NIR bands, which
makes the NDVI calculations easy to apply to data from various instruments. In addition, the
normalization in the NDVI calculation minimizes some inter-observation variations such as varying
illumination and viewing angles and atmospheric conditions producing equivalent index values
over time, which is required for time series analysis and operational monitoring.
One of the first studies to demonstrate the value of NDVI for agricultural drought monitoring was
Tucker et al. (1991), who applied time-series AVHRR NDVI observations to characterize the early
1980s drought across the African Sahel region. Operationally, NDVI has become one of the most
commonly used indices for agricultural drought monitoring throughout the world. Programs such
as the Famine and Early Warning System (FEWS), U.S. Department of Agriculture (USDA)
Foreign Agricultural Service (FAS), and European Drought Observatory (EDO), and individual
countries such as Australia and the United States use the NDVI as a staple for their respective
drought monitoring activities. The majority of these efforts generate NDVI anomaly products (e.g.,
percent or deviation from the historical NDVI mean for a given time and location) instead of the
observed NDVI value to estimate the severity of drought conditions. NDVI has increasingly been
adopted because of the index’s straightforward calculation and demonstrated relationship with
physical vegetation characteristics, and the widespread availability of global NDVI datasets from
AVHRR, MODIS, and MERIS. In addition, it has served as the basis for other VIs that have been
developed, such as the Enhanced Vegetation Index (EVI; Huete et al. 1994), Vegetation Condition
Index (VCI; Kogan 1995a), and Vegetation Drought Response Index (VegDRI; Brown et al. 2008).
In general, the NDVI is universally applicable throughout most of the world, but the index does
have limited utility in some environments, specifically locations with dense vegetation cover (e.g.,
tropical forests) where the NDVI signal has been shown to saturate and become invariant to
vegetation changes at high index values (Gao et al. 2000).
Enhanced Vegetation Index (EVI)
The Enhanced Vegetation Index (Huete et al. 1994), which builds upon the NDVI concept, is
designed to enhance the green vegetation signal over densely vegetated areas and overcome the
saturation effect of the NDVI (Huete et al. 2002). In addition, EVI minimizes atmospheric and soil
background effects on the multi-temporal VI observations to produce a time series of EVI values
that are less influenced by non-vegetation-related variations, which have been shown to influence
multi-temporal NDVI observations by producing unrepresentative VI values in some instances
(Huete et al. 1997). The EVI is calculated from the following equation:
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