Journal of East China Normal University(Natural Science) >
Remote sensing inversion of multi-period winter wheat canopy water content based on a genetic algorithm
Received date: 2021-11-02
Accepted date: 2022-03-17
Online published: 2023-05-25
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.
Suyun NIE , Bin YANG , Wei XIA , Yuan ZHANG . Remote sensing inversion of multi-period winter wheat canopy water content based on a genetic algorithm[J]. Journal of East China Normal University(Natural Science), 2023 , 2023(3) : 71 -81 . DOI: 10.3969/j.issn.1000-5641.2023.03.008
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