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Estimation of Crop Gross Primary Production (GPP): Do Scaled (MODIS) Vegetation Indices Improve Performance? - 2Satellite remote sensing estimates of Gross Primary Production (GPP) have routinely been made using spectral Vegetation Indices (VIs) over the past two decades. The Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), the green band Wide Dynamic Range Vegetation Index (WDRVIgreen), and the green band Chlorophyll Index (CIgreen) have been employed to estimate GPP under the assumption that GPP is proportional to the product of VI and photosynthetically active radiation (PAR) (where VI is one of four VIs: NDVI, EVI, WDRVIgreen, or CIgreen). However, the empirical regressions between VI*PAR and GPP measured locally at flux towers do not pass through the origin (i.e., the zero X-Y value for regressions). Therefore they are somewhat difficult to interpret and apply. This study investigates (1) what are the scaling factors and offsets (i.e., regression slopes and intercepts) between the fraction of PAR absorbed by chlorophyll of a canopy (fAPARchl) and the VIs, and (2) whether the scaled VIs developed in (1) can eliminate the deficiency and improve the accuracy of GPP estimates. Three AmeriFlux maize and soybean fields were selected for this study, two of which are irrigated and one is rainfed. The four VIs and fAPARchl of the fields were computed with the MODerate resolution Imaging Spectroradiometer (MODIS) satellite images. The GPP estimation performance for the scaled VIs was compared to results obtained with the original VIs and evaluated with standard statistics: the coefficient of determination (R2), the root mean square error (RMSE), and the coefficient of variation (CV). Overall, the scaled EVI obtained the best performance. The performance of the scaled NDVI, EVI and WDRVIgreen was improved across sites, crop types and soil/background wetness conditions. The scaled CIgreen did not improve results, compared to the original CIgreen. The scaled green band indices (WDRVIgreen, CIgreen) did not exhibit superior performance to either the scaled EVI or NDVI in estimating crop daily GPP at these agricultural fields. The scaled VIs are more physiologically meaningful than original un-scaled VIs, but scaling factors and offsets may vary across crop types and surface conditions.
Document ID
20150000292
Acquisition Source
Goddard Space Flight Center
Document Type
Preprint (Draft being sent to journal)
Authors
Zhang, Qingyuan
(Universities Space Research Association Columbia, MD, United States)
Cheng, Yen-Ben
(Sigma Space Corp. Lanham, MD, United States)
Lyapustin, Alexei I.
(Sigma Space Corp. Lanham, MD, United States)
Wang, Yujie
(Maryland Univ. Baltimore County Baltimore, MD, United States)
Zhang, Xiaoyang
(South Dakota State Univ. Brookings, SD, United States)
Suyker, Andrew
(Nebraska Univ. Lincoln, NE, United States)
Verma, Shashi
(Nebraska Univ. Lincoln, NE, United States)
Shuai, Yanmin
(Earth Resources Technology, Inc. Laruel, MD, United States)
Middleton, Elizabeth M.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Date Acquired
January 8, 2015
Publication Date
January 1, 2015
Publication Information
Publisher: Elsevier
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
GSFC-E-DAA-TN17781
Report Number: GSFC-E-DAA-TN17781
Funding Number(s)
CONTRACT_GRANT: NNX10AT36A
CONTRACT_GRANT: NNG11HP16A
CONTRACT_GRANT: NNG09HP18C
Distribution Limits
Public
Copyright
Public Use Permitted.
Keywords
Vegetation Index
Daily GPP
MODIS
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