Agricultural Drought Indices - US Department of Agriculture

TCI = 100 (T max – T) / (T max – T min )
where T is the observed BT value for specific period and T min and T max are the historical minimum
and maximum BT values in the AVHRR record.
Global, AVHRR-based TCI gridded data are operationally generated at 4- and 16-km spatial
resolutions as part of a suite of vegetation health data products produced by NOAA’s Center for
Satellite Applications and Research (http://www.star.nesdis.noaa.gov/smcd/emb/vci/VH/
vh_ftp.php). The TCI has been widely applied for drought assessments throughout the world
(Kogan 1995b, Kogan 1997, Unganai and Kogan 1998). The TCI has also been integrated into the
Vegetation Health Index (VHI) (Kogan 1995a) that combines the TCI with the Vegetation Condition
Index (VCI; Kogan 1995a), which is an NDVI-based index calculated in a similar fashion to the TCI
using historical minimum and maximum NDVI boundary limits. The VHI equation is
VHI = α*VCI + (1 – α)*TCI
where α and (1 - α) define the relative contributions of each index. Temperature-based indices
such as TCI and VHI are based on the hypothesis that high land surface temperatures indicate soil
moisture deficits and vegetation stress that can result from drought. Although this assumption
holds true for most parts of the world that are “moisture-limited” environments, higher surface
temperatures can actually be beneficial to vegetation growth in energy-limited environments (i.e.,
higher elevations and latitudes), and caution should be used when applying these types of indices
in these locations (Karnieli et al. 2010).
Normalized Difference Water Index (NDWI)
The Normalized Difference Water Index (NDWI; Gao 1996) capitalizes on the differential response
of the NIR (i.e., high reflectance by inter-cellular spaces of leaves) and the SWIR (i.e., high
absorption by plant water content) spectral regions to healthy green vegetation. The NDWI
calculation takes a similar form to NDVI, using the following equation:
NDWI = (NIR – SWIR) / (NIR + SWIR)
where NIR and SWIR represent the recorded energy in these two spectral regions. As drought
stress increases in vegetation, the reflected NIR radiation decreases because of wilting and
absorption of SWIR radiation decreases due to desiccation, which results in less of a difference in
the reflected energy in these two spectral regions and lower index values. The NDWI value range
is from -1.0 to +1.0, with high values representing healthy vegetation conditions and lower values
representing unhealthy or stressed vegetation.
NDWI has received increasing interest as an agricultural drought monitoring index given the
sensitivity of the SWIR input to plant water content. Gu et al. (2007) investigated the use of NDWI
and NDVI for drought assessment over the U.S. Great Plains and found the NDWI was slightly
more sensitive than NDVI to the initial onset and at the peak severity of drought conditions over
grasslands. A primary limitation of the NDWI is the requirement for SWIR band data in the index
calculation. The SWIR band is included in the AVHRR instrument and global, near-daily global
acquisition of SWIR data was not possible until the launch of the MODIS and MERIS instruments
in 2001 and 2002, respectively. As a result, only a short 10+ year history of NDWI data can be
produced globally Recently, new indices that have built upon the NDWI concept and use SWIR
data inputs have been developed; they include the Normalized Difference Drought Index (NDDI;
Gu et al. 2007) and the Normalized Multi-band Drought Index (NMDI; Wang and Qu 2007).
Composite Approach (Multiple Indicators/Indices)
In efforts to build as comprehensive and flexible a drought early warning system (DEWS) as
possible, it is important to monitor drought across the many sectors mentioned earlier. The use of
a single index will rarely work for all places at all times and for all types of droughts. Most
coordinated monitoring efforts at the national level are going to need to track all types of droughts.
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