Evaluation of the tau-omega model over a dense corn canopy at P- and L-band

Xiaoji Shen, Jeffrey P. Walker, Nan Ye, Xiaoling Wu, Foad Brakhasi, Liujun Zhu, Edward Kim, Yann Kerr, Thomas Jackson

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Abstract

As an emerging technique, P-band (0.3-1 GHz) may improve soil moisture remote sensing compared to L-band (1.4 GHz) Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions, because of its greater moisture retrieval depth resulting from its longer wavelength. Consequently, a number of tower-based experiments were undertaken in VIC, Australia, to understand and quantify potential improvements. The study reported here has extended the evaluation of the tau-omega model to a scenario with a dense corn canopy whose vegetation water content (VWC) reached 20 kg/m2, and compared the soil moisture retrieval performance at P- and L-band. Based on the locally calibrated parameters, the results from both the single-channel algorithm (SCA) and dual-channel algorithm (DCA) approaches presented a clear reduction in vegetation impact at the P-band compared to L-band. While the root-mean-square error (RMSE) for the P-band did not achieve the 0.04- m3m3 target accuracy of SMOS and SMAP, i.e., 0.054 m3m3 for the SCA and 0.074 m3m3 for the DCA, this performance can be regarded as acceptable considering the extremely high VWC. In comparison, the RMSEs at L-band were larger than 0.1 m3m3 for both the SCA and the DCA approaches. Additionally, DCA performed better in correlation coefficient and unbiased RMSE, while SCA performed better in RMSE at the P-band due to the larger bias when using DCA. Moreover, the calibrated vegetation parameters at the P-band were found to apply to broader conditions than those at the L-band, likely due to the reduced vegetation impact.

Original languageEnglish
Article number2504605
Number of pages5
JournalIEEE Geoscience and Remote Sensing Letters
Volume20
DOIs
Publication statusPublished - 15 Sept 2023

Keywords

  • P-band
  • passive microwave
  • roughness
  • soil moisture retrieval
  • vegetation

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