Abstract
In this paper GPS (Global Positioning System)-based methods to measure L-band GPS Signal-to-Noise ratios (SNRs) through different forest canopy conditions are presented. Hemispherical sky-oriented photos (HSOPs) along with GPS receivers are used. Simultaneous GPS observations are collected with one receiver in the open and three inside a forest. Comparing the GPS SNRs observed in the forest to those observed in the open allows for a rapid determination of signal loss. This study includes data from 15 forests and includes two forests with inter-seasonal data. The Signal-to-Noise Ratio Atmospheric Model, Canopy Closure Predictive Model (CCPM), Signal-to-Noise Ratio Forest Index Model (SFIM), and Simplified Signal-to-Noise Ratio Forest Index Model (SSFIM) are presented, along with their corresponding adjusted R2 and Root Mean Square Error (RMSE). As predicted by the CCPM, signals are influenced greatly by the angle of the GPS from the horizon and canopy closure. The results support the use of the CCPM for individual forests but suggest that an initial calibration is needed for a location and time of year due to different absorption characteristics. The results of the SFIM and SSFIM provide an understanding of how different forests attenuate signals and insights into the factors that influence signal absorption.
Highlights
The Global Positioning System (GPS) constellation is primarily used for position, navigation, and timing purposes
Four models are presented and include an atmospheric model, a model optimized using Hemispherical sky-oriented photos (HSOPs), and two models using dummy variables for each forest to generate an absorption index associated with the different forests
The last model we developed incorporated all aspects of the Canopy Closure Predictive Model (CCPM) and included dummy variables associated with each different forest site
Summary
The Global Positioning System (GPS) constellation is primarily used for position, navigation, and timing purposes. The scientific community has used the signals transmitted from. Some GPS signal studies include GPS performance, wireless communication reliability, and the combination of GPS signal-to-noise ratios (SNRs) with light detection and ranging (LiDAR) data to measure signal loss in forests [1,2,3,4,5]. Developing a method to predict with confidence the degree to which GPS signals are affected by forest structure provides useful information on L-band scattering and absorption. This work is important to understanding GPS performance and to scientific studies that employ other microwave signals, such as satellite communications, air-to-ground communications, cellular phones, and synthetic aperture radar (SAR). It is relevant to studies that explore forest growth modeling and use light interception predictions [6,7,8,9,10,11,12]
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