A GNSS-IR soil moisture inversion method based on the SSA assisted ELM

Chengwei Huang; Lilong Liu; Maijin Lin; Qingwen Huang; Haohang Bi

doi:10.1117/12.3059035

2 January 2025 A GNSS-IR soil moisture inversion method based on the SSA assisted ELM

Chengwei Huang, Lilong Liu, Maijin Lin, Qingwen Huang, Haohang Bi

Author Affiliations +

Proceedings Volume 13514, International Conference on Remote Sensing and Digital Earth (RSDE 2024); 135140B (2025) https://doi.org/10.1117/12.3059035
Event: 2024 International Conference on Remote Sensing and Digital Earth, 2024, Chengdu, China

Abstract

Global Navigation Satellite System Interferometric Reflection (GNSS-IR) has become a current research focus. Soil Moisture (SM) monitoring can be achieved using associated technologies, which have significant application potential. To further improve the prediction accuracy of inversion SM, this paper proposes a SSA-ELM model to retrieve SM. This model utilizes the feature parameters extracted from signal-to-noise ratio (SNR) observations as inputs for the model. Then, solve the hyperparameters of the ELM model by SSA. Finally, the performance of this model is compared with that of the BP Neural Network (BPNN) and ELM model. The Experimental results demonstrate that: the SM inversion for the PRN32 satellite in the SSA-ELM model has a determination coefficient of 0.932, RMSE of 0.024, and MAE of 0.019, all are the optimal values in the experiment. The inversion results are more stable and can better reflect the changes of SM, demonstrating the reliability of this model.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Chengwei Huang, Lilong Liu, Maijin Lin, Qingwen Huang, and Haohang Bi "A GNSS-IR soil moisture inversion method based on the SSA assisted ELM", Proc. SPIE 13514, International Conference on Remote Sensing and Digital Earth (RSDE 2024), 135140B (2 January 2025); https://doi.org/10.1117/12.3059035

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