Skip to content
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Menu
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Menu
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
agricultural and biological sciences
Sensitivity of vegetation indices and gross primary production of tallgrass prairie to severe drought
Remote Sensing of Environment, Volume 152, Year 2014
Notification
URL copied to clipboard!
Description
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 well with GPPEC. Our analysis shows that 8-day averaged values (temperature, vapor-pressure deficit) do not reflect the short-term extreme climate events well, suggesting that satellite-based models may need to be run at daily or hourly scales, especially under unfavorable climatic conditions. © 2014 Elsevier Inc.
Authors & Co-Authors
Wagle, Pradeep
United States, Norman
The University of Oklahoma
Xiao, Xiangming
United States, Norman
The University of Oklahoma
Torn, Margaret S.
United States, Berkeley
Lawrence Berkeley National Laboratory
Cook, David R.
United States, Lemont
Argonne National Laboratory
Matamala, Roser
United States, Lemont
Argonne National Laboratory
Fischer, Marc L.
United States, Berkeley
Lawrence Berkeley National Laboratory
Jin, Cui
United States, Norman
The University of Oklahoma
Dong, Jinwei
United States, Norman
The University of Oklahoma
Biradar, C. Madivalappa
Jordan, Amman
International Center for Agricultural Research in Dry Areas Icarda
Statistics
Citations: 106
Authors: 9
Affiliations: 4
Identifiers
Doi:
10.1016/j.rse.2014.05.010
ISSN:
00344257
Research Areas
Environmental