Estimation of Winter Wheat Biomass and Yield by Combining the AquaCrop Model and Field Hyperspectral Data

Title
Estimation of Winter Wheat Biomass and Yield by Combining the AquaCrop Model and Field Hyperspectral Data
Publication Date
2016
Author(s)
Jin, Xiuliang
Kumar, Lalit
( author )
OrcID: https://orcid.org/0000-0002-9205-756X
Email: lkumar@une.edu.au
UNE Id une-id:lkumar
Li, Zhenhai
Xu, Xingang
Yang, Guijun
Wang, Jihua
Type of document
Journal Article
Language
en
Entity Type
Publication
Publisher
MDPI AG
Place of publication
Switzerland
DOI
10.3390/rs8120972
UNE publication id
une:20347
Abstract
Knowledge of spatial and temporal variations in crop growth is important for crop management and stable crop production for the food security of a country. A combination of crop growth models and remote sensing data is a useful method for monitoring crop growth status and estimating crop yield. The objective of this study was to use spectral-based biomass values generated from spectral indices to calibrate the AquaCrop model using the particle swarm optimization (PSO) algorithm to improve biomass and yield estimations. Spectral reflectance and concurrent biomass and yield were measured at the Xiaotangshan experimental site in Beijing, China, during four winter wheat-growing seasons. The results showed that all of the measured spectral indices were correlated with biomass to varying degrees. The normalized difference matter index (NDMI) was the best spectral index for estimating biomass, with the coefficient of determination (R²), root mean square error (RMSE), and relative RMSE (RRMSE) values of 0.77, 1.80 ton/ha, and 25.75%, respectively. The data assimilation method (R² = 0.83, RMSE = 1.65 ton/ha, and RRMSE = 23.60%) achieved the most accurate biomass estimations compared with the spectral index method. The estimated yield was in good agreement with the measured yield (R² = 0.82, RMSE = 0.55 ton/ha, and RRMSE = 8.77%). This study offers a new method for agricultural resource management through consistent assessments of winter wheat biomass and yield based on the AquaCrop model and remote sensing data.
Link
Citation
Remote Sensing, 8(12), p. 1-15
ISSN
2072-4292
Start page
1
End page
15

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