The foliage effect on the height time series from permanent GPS stations

Abstract

The effect of deciduous trees growing above antenna height on data collected by permanent Global Positioning System (GPS) stations was investigated. Signal blockage due to foliage and branches was found to have the same effect as an increased elevation cutoff angle, i.e., there was a change in the computed position. Height estimates were affected the most, showing a decrease with tree growth. Empirical Orthogonal Function (EOF) analysis on the height-time series from five test sites and two stations surrounded by trees showed a similar EOF mode of signal. Signal availability, computed as the ratio of the complete to possible set of observations, decreased with increasing tree growth and showed seasonal variation, with the observation ratios being higher during the winter months when the leaves had fallen. A similar seasonal variation was observed in multipath error and signal attenuation due to foliage. The multipath error index MP2 was computed using the TEQC program and found to increase at a significant rate at sites with growing trees. Signal attenuation was analyzed using 1-σ uncertainties from the estimation process of daily GPS data processing. While 1-σ uncertainties did not show any seasonal variations at sites without trees, they were highly dependent on conditions related to the seasonal change of foliage when deciduous trees were near the antenna.

Annual crustal deformation based on GNSS observations between 1996 and 2016

“…The supremacy of diurnal oscillations over other periods is also proven by, for example, Kenyeres and Bruyninx (2004), Calais et al (2006) and Teferle et al (2007). The existence of oscillations caused by anything other than plate movements' environmental effects is also the result of other phenomena such as thermal (Bogusz et al 2011), foliage (Park and Won 2010) and snow (Wang et al 2015) effects.…”

“…To date, seasonal crustal deformation detection on the basis of permanent GNSS stations has been conducted (e.g. Zhang et al 2002;Park and Won 2010;Liu et al 2015;Milyukov et al 2015;Araszkiewicz and Völksen 2016;Alinia et al 2017). Annual signals based on GPS observations were looked at by Bogusz and Figurski (2014), in which the observations from 129 permanent GPS stations from 5 consecutive years were analysed.…”

SARDO: An Automated Search-and-Rescue Drone-Based Solution for Victims Localization

“…Moreover, GNSS signals may be heavily attenuated by debris or rubble, which would likely not completely block the cellular coverage provided by a UAV hovering close enough to the victims UEs. As additional attenuation may be introduced by tree foliage, metal or wooden objects, few centimeters of water, shadowing in urban canyons and so on, GNSS is unreliable for such a mission critical operation [4].…”