Journal of East China Normal University(Natural Science) ›› 2023, Vol. 2023 ›› Issue (3): 71-81.doi: 10.3969/j.issn.1000-5641.2023.03.008

• Remote Sensing and Geographic Information System • Previous Articles     Next Articles

Remote sensing inversion of multi-period winter wheat canopy water content based on a genetic algorithm

Suyun NIE1, Bin YANG2, Wei XIA1, Yuan ZHANG1,*()   

  1. 1. Key Laboratory of Geographic Information Science (Ministry of Education), School of Geographic Sciences, East China Normal University, Shanghai 200241, China
    2. Department of Modern Science and Technology, Party School of Liaoning Provincial Party Committee, Shenyang 110004, China
  • Received:2021-11-02 Accepted:2022-03-17 Online:2023-05-25 Published:2023-05-25
  • Contact: Yuan ZHANG


The remote sensing inversion of crop canopy water content is a valuable for assessing drought stress of wheat fields and implementing precision irrigation. This study aimed to quickly obtain the canopy water content during the growth period for winter wheat in North China by using multi-temporal remote sensing images of Landsat-8 OLI and Sentinel-2 MSI from January to May 2017. The regression relationship was constructed with NDWI and measured water content in a wheat field via the mixed pixel decomposition model. The genetic algorithm was then used to inverse the canopy water content. The proposed method demonstrated better performance compared to ground-truth data, with the coefficient of determination (R2) and the root mean square error (RMSE) of 0.567 and 5.6%, respectively. Additionally, the error was reduced by more than 20% when compared to the direct inversion based on NDWI. This study indicates that quantification of different linear mixing ratios of wheat canopy and background soil can effectively eliminate the influence of soil on wheat water content inversion, and is crucial for the application of remote sensing to wheat growth monitoring.

Key words: canopy water content, multi-temporal remote sensing image, pixel dichotomy model, genetic algorithm, winter wheat

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