Improving Spring Maize Yield Estimation at Field Scale by Assimilating Time-Series HJ-1 CCD Data into the WOFOST Model Using a New Method with Fast Algorithms

Improving Spring Maize Yield Estimation at Field Scale by Assimilating Time-Series HJ-1 CCD Data into the WOFOST Model Using a New Method with Fast Algorithms

Field crop yield prediction is crucial to grain storage, agricultural field management, and national agricultural decision-making. Currently, crop models are widely used for crop yield prediction. However, they are hampered by the uncertainty or similarity of input parameters when extrapolated to fi...

Full description

Bibliographic Details
Main Authors: Zhiqiang Cheng, Jihua Meng, Yiming Wang
Format: Article
Language:English
Published: MDPI AG 2016-04-01
Series:Remote Sensing
Subjects:
yield simulation
prediction accuracy
spatial heterogeneity
WOFOST model
fast assimilation algorithms
remote sensing
Online Access:http://www.mdpi.com/2072-4292/8/4/303

Internet

http://www.mdpi.com/2072-4292/8/4/303

Similar Items