Soil moisture estimation based on triple-frequency multipath error. Issue 15 (3rd August 2021)

• Record Type: Journal Article
• Authors: Zhang, Xianyun; Nie, Shihai; Zhang, Chunkang; Zhang, Jun; Cai, Hong
• Is Part Of: International journal of remote sensing. Volume 42:Issue 15(2021)
• Page Start: 5955
• Page End: 5970
• Publication Date: 2021-08-03
• Subjects: Remote sensing -- Periodicals; Télédétection -- Périodiques; 621.3678
• DOI: 10.1080/01431161.2021.1933246
• Languages: English
• ISSNs: 0143-1161

Abstract

ABSTRACT: Soil moisture (SM) is a critical environmental factor. Therefore, it is of great significance to measure it dynamically and precisely. Studies have proved that Global Positioning System Reflectometry (GPS-R) based on signal-to-noise ratio can realize the monitoring of SM with high-precision, high spatiotemporal resolution, low cost, and under all weather conditions. The transmissions of GPS triple-frequency carrier phase (TRFCP) and triple-frequency pseudorange (TRFP) facilitate obtaining high-quality multipath errors in real-time. Accordingly, to enrich the data sources and methods for SM estimation based on GPS-R, two novel SM estimation methods – the TRFCP multipath error method (TRFCP method) and the TRFP multipath error method (TRFP method) – are proposed. The feasibility of the proposed methods was evaluated by the SM content (SMC) from the Plate Boundary Observatory (PBO) H2 O project. The experimental results demonstrate that the phase delays estimated by the proposed methods both are strongly correlated with the PBO SMC, with Pearson correlation coefficients ( R ) of 0.95 and 0.84, respectively. Furthermore, both methods achieved high estimation accuracy for the SMC.