Development of a GPS Forest Signal Absorption Coefficient Index

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...

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Main Authors: William Wright, Benjamin Wilkinson, Wendell Cropper
Format: Article
Language:English
Published: MDPI AG 2018-04-01
Series:Forests
Subjects:
Online Access:http://www.mdpi.com/1999-4907/9/5/226
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spelling doaj-95848f6d729b4430912f1683e5b3ca202020-11-25T01:09:34ZengMDPI AGForests1999-49072018-04-019522610.3390/f9050226f9050226Development of a GPS Forest Signal Absorption Coefficient IndexWilliam Wright0Benjamin Wilkinson1Wendell Cropper2Department of Geography and Environmental Engineering, United States Military Academy, West Point, NY 10996, USASchool of Forest Resources and Conservation, University of Florida, Gainesville, FL 32611, USASchool of Forest Resources and Conservation, University of Florida, Gainesville, FL 32611, USAIn 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.http://www.mdpi.com/1999-4907/9/5/226canopy closureglobal positioning systemhemispherical sky-oriented photosignal attenuationgeographic information system
collection DOAJ
language English
format Article
sources DOAJ
author William Wright
Benjamin Wilkinson
Wendell Cropper
spellingShingle William Wright
Benjamin Wilkinson
Wendell Cropper
Development of a GPS Forest Signal Absorption Coefficient Index
Forests
canopy closure
global positioning system
hemispherical sky-oriented photo
signal attenuation
geographic information system
author_facet William Wright
Benjamin Wilkinson
Wendell Cropper
author_sort William Wright
title Development of a GPS Forest Signal Absorption Coefficient Index
title_short Development of a GPS Forest Signal Absorption Coefficient Index
title_full Development of a GPS Forest Signal Absorption Coefficient Index
title_fullStr Development of a GPS Forest Signal Absorption Coefficient Index
title_full_unstemmed Development of a GPS Forest Signal Absorption Coefficient Index
title_sort development of a gps forest signal absorption coefficient index
publisher MDPI AG
series Forests
issn 1999-4907
publishDate 2018-04-01
description 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.
topic canopy closure
global positioning system
hemispherical sky-oriented photo
signal attenuation
geographic information system
url http://www.mdpi.com/1999-4907/9/5/226
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