Skip all navigation and jump to content Jump to site navigation
NASA Logo - Goddard Space Flight Center

+ NASA Homepage

    
Goddard Space Flight Center
About MODIS News Data Tools /images2 Science Team Science Team Science Team

   + Home
ABOUT MODIS
MODIS Publications Link
MODIS Presentations Link
MODIS Biographies Link
MODIS Science Team Meetings Link
 

 

 

Ma, GN; Huang, JX; Wu, WB; Fan, JL; Zou, JQ; Wu, SJ (2013). Assimilation of MODIS-LAI into the WOFOST model for forecasting regional winter wheat yield. MATHEMATICAL AND COMPUTER MODELLING, 58(4-Mar), 634-643.

Abstract
Crop growth models have been applied successfully in forecasting crop yield at a local scale, while satellite remote sensing has the advantage of retrieving regional crop parameters. The new assimilation method of integrating the crop growth model with remote sensing has presented great potential in regional crop yield assessment. In this study, the Moderate Resolution Imaging Spectrometer (MODIS) leaf area index (LAI) data product was assimilated into the World Food Studies (WOFOST) crop growth model. Using the Extended Fourier Amplitude Sensitivity Test (EFAST) global sensitivity analysis approach, several local and regional crop parameters were identified to be recalibrated. The Shuffled Complex Evolution (SCE) optimization algorithm was used to estimate the emergence date, initial biomass and initial available soil water by minimizing the differences between the corrected MODIS-LAI and simulated LAI. Results indicated that the accuracy of water-limited crop yield was improved significantly after the assimilation. The root mean square error (RMSE) reduced from 983 kg/ha to 474 kg/ha and 667 kg/ha respectively in two different optimization schemes. (C) 2011 Elsevier Ltd. All rights reserved.

DOI:
10.1016/j.mcm.2011.10.038

ISSN:

FirstGov logo Privacy Policy and Important Notices NASA logo

Curator: Brandon Maccherone
NASA Official: Shannell Frazier

NASA Home Page Goddard Space Flight Center Home Page