Modeling the Response of a Wireless Harmonic Sensor in a Multi-Layer Environment for Landslide Monitoring

This paper presents a technique for determining the electrical properties of soil by analyzing signal propagation through a stratified medium. The improvement in the extraction of soil permittivity using a model that accounts for internal reflections within the stratified medium is demonstrated. Additionally, the paper utilizes an experimental approach for isolating the forward and reverse transmission paths of a harmonic signal within a soil structure. The work is part of an effort to extract soil property information using a harmonic sensor to develop an electromechanical model for more effective monitoring of potential landslides.

Authors

Institutions

Publication Details

Published
2025-04-14
DOI
https://doi.org/10.1109/wamicon64429.2025.11004095
Primary Topic
Soil Moisture and Remote Sensing
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Modeling the Response of a Wireless Harmonic Sensor in a Multi-Layer Environment for Landslide Monitoring

T. Weller, Daniel Kwabena Yirenya-Tawiah, Jeff Frolík, Rye Fought et al.
Soil Moisture and Remote Sensing
article

Modeling the Response of a Wireless Harmonic Sensor in a Multi-Layer Environment for Landslide Monitoring

T. Weller, Daniel Kwabena Yirenya-Tawiah, Jeff Frolík, Rye Fought, Elsie Anthonio
article en

Abstract

This paper presents a technique for determining the electrical properties of soil by analyzing signal propagation through a stratified medium. The improvement in the extraction of soil permittivity using a model that accounts for internal reflections within the stratified medium is demonstrated. Additionally, the paper utilizes an experimental approach for isolating the forward and reverse transmission paths of a harmonic signal within a soil structure. The work is part of an effort to extract soil property information using a harmonic sensor to develop an electromechanical model for more effective monitoring of potential landslides.

University of Vermont (US), Oregon State University (US)
U.S. Department of Agriculture, National Institute of Food and Agriculture
Openalex Percentile: Top 91%
Soil Moisture and Remote Sensing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.