Integrating GPS, GIS and photogrammetry techniques to predict sig | 40247
Journal of Geology & Geophysics

Journal of Geology & Geophysics
Open Access

ISSN: 2381-8719

+44 1478 350008

Integrating GPS, GIS and photogrammetry techniques to predict signal loss in varying forest environments

2nd International Convention on Geosciences and Remote Sensing

November 08-09, 2017 | Las Vegas, USA

William C Wright

United States Military Academy, USA

Posters & Accepted Abstracts: J Geol Geophys

Abstract :

The reception of microwave signals are degraded by reflection, absorption and scattering due to propagation through vegetation. As such, there is interest in better understanding how the many different technologies militaries depend on for operations may be influence when operating in forests or jungles at a large geographic scale. This study presents the relationship between forest parameters obtained using, both traditional mensuration techniques and terrestrial-based hemispherical sky-oriented photos to Global Positioning System (GPS) signal-to-noise ratios (SNR). Hemispherical sky-oriented photos can be used to rapidly estimate leaf area index and canopy closure values in a particular window of interest under forest canopy using ArcGIS. This study also uses GIS to generate static and animated maps of GPS satellites as they move through the sky along with their corresponding SNRs. Using ordinary least squares linear regression modeling, a canopy closure predictive model is presented. Additionally, a generalized forest index model is presented using observations from 15 different geographic locations. Finally, a seasonal variation study at a single study site is discussed. The resulting models predict signal attenuation while using only the minimum number of statistically significant parameters taken from sky-oriented photos and GPS receivers allowing for simple and rapid replication.