Sensitivity of vegetation indices and gross primary production of tallgrass prairie to severe drought
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Pradeep Wagle, Xiangming Xiao, Margaret Torn, David Cook, Roser Matamala, Marc Fischer, Cui Jin, Jinwei Dong, Chandrashekhar Biradar. (30/9/2014). Sensitivity of vegetation indices and gross primary production of tallgrass prairie to severe drought. Remote Sensing of Environment, 152, pp. 1-14.
Abstract
Drought affects vegetation photosynthesis and growth.Many studies have used the normalized difference vegetation
index (NDVI), which is calculated as the normalized ratio between near infrared and red spectral bands in
satellite images, to evaluate the response of vegetation to drought. In this study, we examined the impacts of
drought on three vegetation indices (NDVI, enhanced vegetation index, EVI, and land surface water index,
LSWI) and CO2 flux from three tallgrass prairie eddy flux tower sites in the U.S. Gross primary production
(GPP) was also modeled using a satellite-based Vegetation Photosynthesis Model (VPM), and the modeled
GPP (GPPVPM) was compared with the GPP (GPPEC) derived from eddy covariance measurements. Precipitation
at two sites in Oklahoma was 30% below the historical mean in both years of the study period (2005–2006),
while the site in Illinois did not experience drought in the 2005–2007 study period. The EVI explained the seasonal
dynamics of GPP better than did NDVI. The LSWI dropped below zero during severe droughts in the growing
season, showing its potential to track drought. The result shows that GPP was more sensitive to drought than
were vegetation indices, and EVI and LSWI were more sensitive than NDVI. We developed a modified function
(Wscalar), calculated as a function of LSWI, to account for the effect of severe droughts on GPP in VPM. The GPPVPM
from the modified VPM accounted for the rapid reduction in GPP during severe droughts and the seasonal
dynamics of GPPVPM agreed reasonably wellwith GPPEC. Our analysis shows that 8-day averaged values (temperature,
vapor-pressure deficit) do not reflect the short-termextreme climate eventswell, suggesting that satellitebased
models may need to be run at daily or hourly scales, especially under unfavorable climatic conditions.
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Author(s) ORCID(s)
Biradar, Chandrashekhar https://orcid.org/0000-0002-9532-9452