Estimating crop yield using a satellite-based light use efficiency model
•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 yie...
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Published in | Ecological indicators Vol. 60; no. C; pp. 702 - 709 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Netherlands
Elsevier Ltd
01.01.2016
Elsevier |
Subjects | |
Online Access | Get full text |
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Summary: | •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.
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. |
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Bibliography: | http://dx.doi.org/10.1016/j.ecolind.2015.08.013 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 USDOE |
ISSN: | 1470-160X 1872-7034 |
DOI: | 10.1016/j.ecolind.2015.08.013 |