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Journal of Applied Remote Sensing

Novel approach for computing photosynthetically active radiation for productivity modeling using remotely sensed images in the Great Plains, United States
Author(s): Ramesh K. Singh; Shuguang Liu; Larry L. Tieszen; Andrew E. Suyker; Shashi B. Verma
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Paper Abstract

Gross primary production (GPP) is a key indicator of ecosystem performance, and helps in many decision-making processes related to environment. We used the Eddy covariancelight use efficiency (EC-LUE) model for estimating GPP in the Great Plains, United States in order to evaluate the performance of this model. We developed a novel algorithm for computing the photosynthetically active radiation (PAR) based on net radiation. A strong correlation (R2 = 0.94,N = 24) was found between daily PAR and Landsat-based mid-day instantaneous net radiation. Though the Moderate Resolution Spectroradiometer (MODIS) based instantaneous net radiation was in better agreement (R2 = 0.98,N = 24) with the daily measured PAR, there was no statistical significant difference between Landsat based PAR and MODIS based PAR. The EC-LUE model validation also confirms the need to consider biological attributes (C3 versus C4 plants) for potential light use efficiency. A universal potential light use efficiency is unable to capture the spatial variation of GPP. It is necessary to use C3 and C4 based land use/land cover map for using EC-LUE model for estimating spatiotemporal distribution of GPP.

Paper Details

Date Published: 9 March 2012
PDF: 13 pages
J. Appl. Rem. Sens. 6(1) 063522 doi: 10.1117/1.JRS.6.063522
Published in: Journal of Applied Remote Sensing Volume 6, Issue 1
Show Author Affiliations
Ramesh K. Singh, U.S. Geological Survey (United States)
Shuguang Liu, U.S. Geological Survey (United States)
Larry L. Tieszen, U.S. Geological Survey (United States)
Andrew E. Suyker, Univ. of Nebraska-Lincoln (United States)
Shashi B. Verma, Univ. of Nebraska-Lincoln (United States)

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