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GEOPHYSICAL RESEARCH LETTERS, VOL. 34, L06407, doi:10.1029/2006GL029127, 2007

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A five-year analysis of MODIS NDVI and NDWI for grassland
drought assessment over the central Great Plains of the United States
Yingxin Gu,1 Jesslyn F. Brown,1 James P. Verdin,2 and Brian Wardlow3
Received 18 December 2006; revised 16 February 2007; accepted 28 February 2007;published 27 March 2007.

[ 1 ] A five-year (2001 – 2005) history of moderate
resolution imaging spectroradiometer (MODIS)
normalized difference vegetation index (NDVI) and
normalized difference water index (NDWI) data was
analyzed for grassland drought assessment within the
central United States, specifically for the Flint Hills of
Kansas and Oklahoma. Initial results show strongrelationships among NDVI, NDWI, and drought
conditions. During the summer over the Tallgrass Prairie
National Preserve, the average NDVI and NDWI were
consistently lower (NDVI < 0.5 and NDWI < 0.3) under
drought conditions than under non-drought conditions
(NDVI>0.6 and NDWI>0.4). NDWI values exhibited a
quicker response to drought conditions than NDVI.
Analysis revealed that combininginformation from
visible, near infrared, and short wave infrared channels
improved sensitivity to drought severity. The proposed
normalized difference drought index (NDDI) had a stronger
response to summer drought conditions than a simple
difference between NDVI and NDWI, and is therefore a
more sensitive indicator of drought in grasslands than NDVI
alone. Citation: Gu, Y., J. F. Brown, J. P. Verdin,and B. Wardlow
(2007), A five-year analysis of MODIS NDVI and NDWI for
grassland drought assessment over the central Great Plains of the
United States, Geophys. Res. Lett., 34, L06407, doi:10.1029/
2006GL029127.

1. Introduction
[2] Drought is one of the most costly natural disasters in
the United States [Federal Emergency Management Agency,
1995; Wilhite, 2000]. Traditionally, droughtmonitoring has
been based on weather station observations, which lack the
continuous spatial coverage needed to characterize and
monitor the detailed spatial pattern of drought conditions.
Since the 1970’s, hundreds of studies have used satellite
land observation data to monitor a variety of dynamic land
surface processes [e.g., Anderson et al., 1976; Reed et
al.,1994; Yang et al., 1998;Peters et al., 2002]. Satellite
remote sensing provides a synoptic view of the land and a
spatial context for measuring drought impacts.
[3] The normalized difference vegetation index (NDVI),
which is the normalized reflectance difference between the
1
Science Applications International Corporation, US Geological Survey
Center for Earth Resources Observation and Science, Sioux Falls, SouthDakota, USA.
2
US Geological Survey Center for Earth Resources Observation and
Science, Sioux Falls, South Dakota, USA.
3
National Drought Mitigation Center, University of Nebraska at
Lincoln, Nebraska, USA.

Copyright 2007 by the American Geophysical Union.
0094-8276/07/2006GL029127$05.00

near infrared (NIR) and visible red bands [Rouse et al.,
1974; Tucker, 1979] is used extensivelyin ecosystem
monitoring. The NDVI measures the changes in chlorophyll
content (via absorption of visible red radiation) and in
spongy mesophyll (via reflected NIR radiation) within the
vegetation canopy. As a result, higher NDVI values usually
represent greater vigor and photosynthetic capacity (or
greenness) of vegetation canopy [Tucker, 1979; Chen and
Brutsaert, 1998]. NDVI’s role indrought monitoring and
assessment has been described several times during the last
decade [Kogan, 1991; Kogan, 1995; Yang et al., 1998;
McVicar and Bierwirth, 2001; Ji and Peters, 2003; Wan et
al., 2004]. Most of these efforts were based on NDVI
calculated from data collected by the Advanced Very High
Resolution Radiometer (AVHRR) sensor. NDVI has been
calculated from AVHRR data for more than...