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Related Experiment Video

Updated: Aug 8, 2025

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar

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Published on: May 1, 2018

Multilayer Model in Soil Moisture Content Retrieval Using GNSS Interferometric Reflectometry.

Jie Li¹, Xuebao Hong¹, Feng Wang¹

¹Electronic Information Engineering, Beihang University, Beijing 100191, China.

Sensors (Basel, Switzerland)

|February 28, 2023

Summary

This summary is machine-generated.

A new Global Navigation Satellite System-Interferometric Reflectometry (GNSS-IR) model measures soil moisture content (SMC) at various depths. This stratified approach improves accuracy over traditional single-layer soil moisture monitoring.

Keywords:

Hilbert transform global navigation satellite system–interferometric reflectometry multilayer reverse osmosis model sink model soil moisture content

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Manufacturing Simple and Inexpensive Soil Surface Temperature and Gravimetric Water Content Sensors

Manufacturing Simple and Inexpensive Soil Surface Temperature and Gravimetric Water Content Sensors

Published on: December 21, 2019

Area of Science:

Geophysics
Remote Sensing
Soil Science

Background:

Global Navigation Satellite System-Interferometric Reflectometry (GNSS-IR) is established for soil moisture content (SMC) monitoring.
Conventional GNSS-IR models treat soil as a single layer, averaging SMC from 1-10 cm depth.
Non-uniform soil moisture distribution necessitates depth-specific measurement techniques.

Purpose of the Study:

To develop and validate a soil moisture-stratified measurement model for GNSS-IR.
To enable accurate retrieval of SMC at different soil depths.
To overcome limitations of conventional single-layer soil moisture assessment.

Main Methods:

Utilized a simulation platform for developing a stratified SMC measurement model.
Analyzed GNSS signals reflected from various soil layers.
Employed total transmission of vertically linearly polarized electromagnetic waves.
Applied the Hilbert transform to extract interference signal envelopes and enhance notch visibility.

Main Results:

The proposed multilayer SMC measurement model demonstrated high accuracy.
Correlation between predetermined and retrieved SMC values approached 0.92.
The Hilbert transform effectively reduced ambient noise interference in the signal envelope.

Conclusions:

The SMC-stratified GNSS-IR model accurately measures soil moisture at different depths.
This advanced technique addresses the limitations of conventional methods for heterogeneous soil moisture profiles.
The study validates the potential of GNSS-IR for detailed subsurface hydrological monitoring.