Estimating crop yield using a satellite-based light use efficiency model. (January 2016)

• Record Type: Journal Article
• Authors: Yuan, Wenping; Chen, Yang; Xia, Jiangzhou; Dong, Wenjie; Magliulo, Vincenzo; Moors, Eddy; Olesen, Jørgen Eivind; Zhang, Haicheng
• Is Part Of: Ecological indicators. Volume 60(2016)
• Page Start: 702
• Page End: 709
• Publication Date: 2016-01
• Subjects: Light use efficiency -- EC-LUE -- Gross primary production -- Crop yield; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2015.08.013
• Languages: English
• ISSNs: 1470-160X

Abstract

Highlights: Satellite-based LUE model simulates GPP well at 36 cropland sites globally. Constant parameters can be used in the LUE model for simulating crops' GPP. There are large errors for simulating yield using LUE model and harvest index. LUE model needs new harvest index and carbon allocation for crop yield estimations. Abstract: Satellite-based techniques that provide temporally and spatially continuous information over vegetated surfaces have become increasingly important in monitoring the global agriculture yield. In this study, we examine the performance of a light use efficiency model (EC-LUE) for simulating the gross primary production (GPP) and yield of crops. The EC-LUE model can explain on average approximately 90% of the variability in GPP for 36 FLUXNET sites globally. The results indicate that a universal set of parameters, independent of crop species (except for C4 crops), can be adopted in the EC-LUE model for simulating crops' GPP. At both irrigated and rainfed sites, the EC-LUE model exhibits a similar level of performance. However, large errors are found when simulating yield based on crop harvest index. This analysis highlights the need to improve the representation of the harvest index and carbon allocation for improving crop yield estimations from satellite-based methods.