TY - JOUR
T1 - Application of chlorophyll-related vegetation indices for remote estimation of maize productivity
AU - Peng, Yi
AU - Gitelson, Anatoly A.
N1 - Funding Information:
This research was supported by NASA NACP grant No. NNX08AI75G and partially by the U.S. Department of Energy: (a) EPSCoR program , Grant No. DE-FG-02-00ER45827 and (b) Office of Science (BER) , Grant No. DE-FG03-00ER62996 . We gratefully acknowledge the support and the use of facilities and equipment provided by the Center for Advanced Land Management Information Technologies (CALMIT) and Carbon Sequestration Program, University of Nebraska-Lincoln. We are sincerely grateful to Donald. C. Rundquist, Shashi B. Verma and Andy E. Suyker for their help and support, and Anthony Lawrence Nguy-Robertson for fruitful discussion and suggestions. We also thank two anonymous reviewers for providing valuable comments to the manuscript.
PY - 2011/9/15
Y1 - 2011/9/15
N2 - Crop gross primary productivity (GPP) is an important characteristic for evaluating crop nitrogen content and yield, as well as the carbon exchange. Based on the close relationship observed between GPP and total chlorophyll content in crops, we applied a model that relies on a product of chlorophyll-related vegetation index and incoming photosynthetically active radiation for remote estimation of GPP in maize. In this study, we tested the performance of this model for maize GPP estimation based on spectral reflectance collected at a close range, 6m above the top of the canopy, over a period of eight years from 2001 through 2008. Fifteen widely used chlorophyll-related vegetation indices were employed for GPP estimation in irrigated and rainfed maize, and accuracy and uncertainties of the models were compared. We also explored the possibility of using a unified algorithm in estimating maize GPP in fields that are different in irrigation, field history and climatic conditions. The results showed that vegetation indices that closely relate to total canopy chlorophyll content and/or green leaf area index were accurate in GPP estimation. Both green and red edge Chlorophyll Indices, MERIS Terrestrial Chlorophyll Index as well as Simple Ratio were the best approximations of the widely variable GPP in maize under different crop managements and climatic conditions. They were able to predict daily GPP reaching 30gC/m2/d with RMSE below 2.75gC/m2/d.
AB - Crop gross primary productivity (GPP) is an important characteristic for evaluating crop nitrogen content and yield, as well as the carbon exchange. Based on the close relationship observed between GPP and total chlorophyll content in crops, we applied a model that relies on a product of chlorophyll-related vegetation index and incoming photosynthetically active radiation for remote estimation of GPP in maize. In this study, we tested the performance of this model for maize GPP estimation based on spectral reflectance collected at a close range, 6m above the top of the canopy, over a period of eight years from 2001 through 2008. Fifteen widely used chlorophyll-related vegetation indices were employed for GPP estimation in irrigated and rainfed maize, and accuracy and uncertainties of the models were compared. We also explored the possibility of using a unified algorithm in estimating maize GPP in fields that are different in irrigation, field history and climatic conditions. The results showed that vegetation indices that closely relate to total canopy chlorophyll content and/or green leaf area index were accurate in GPP estimation. Both green and red edge Chlorophyll Indices, MERIS Terrestrial Chlorophyll Index as well as Simple Ratio were the best approximations of the widely variable GPP in maize under different crop managements and climatic conditions. They were able to predict daily GPP reaching 30gC/m2/d with RMSE below 2.75gC/m2/d.
KW - Chlorophyll content
KW - Gross primary production
KW - Vegetation indices
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U2 - 10.1016/j.agrformet.2011.05.005
DO - 10.1016/j.agrformet.2011.05.005
M3 - Article
AN - SCOPUS:79959587990
SN - 0168-1923
VL - 151
SP - 1267
EP - 1276
JO - Agricultural and Forest Meteorology
JF - Agricultural and Forest Meteorology
IS - 9
ER -