Knowledge of Global Navigation Satellite System (GNSS) antenna phase center variations plays a key role in precise positioning. Proper modeling is achieved by accessing antenna phase center corrections, which are determined in the calibration process. For most receiver antenna types, the International GNSS Service provides such corrections for two GPS and GLONASS carrier signals. In the case of Galileo, access to phase center corrections is difficult; only antennas calibrated in the anechoic chambers have available corrections for Galileo frequencies. Hence, in many of the studies, GPS-dedicated corrections are used for these Galileo frequencies. Differential analysis was conducted in this study to evaluate the impact of such change. In total, 25 stations belonging to the EUREF Permanent Network and equipped with individual calibrated antennas were the subject of this research. The results for both the absolute and relative positioning methods are clear: using GPS L2 corrections for Galileo E5a frequency causes a bias in the estimated height of almost 8 mm. For the horizontal component, a significant difference can be noticed for only one type of antenna.
In this study, we compared two sets of antenna phase center corrections for groups of the same type of antenna mounted at the continuously operating global navigation satellite system (GNSS) reference stations. The first set involved type mean models provided by the International GNSS Service (release igs08), while the second set involved individual models developed by Geo++. Our goal was to check which set gave better results in the case of height estimation. The paper presents the differences between models and their impact on resulting height. Analyses showed that, in terms of the stability of the determined height, as well as its variability caused by increasing the facade mask, both models gave very similar results. Finally, we present a method for how to estimate the impact of differences in phase center corrections on height changes.
This research presents the analysis of using different weighting functions for the GPS and Galileo observations in Precise Point Positioning (PPP) performance for globally located stations for one week in 2021. Eight different weighting functions of observations dependent on the elevation angle have been selected. It was shown that the use of different weighting functions has no impact on the horizontal component but has a visible impact on the vertical component, the tropospheric delay and the convergence time. Depending on the solutions, i.e., GPS-only, Galileo-only or GPS+Galileo, various weighting functions turned out to the best. The obtained results confirm that the Galileo solution has comparable accuracy to the GPS solution. Also, with the Galileo solution, the best results were obtained for functions with a smaller dependence on the elevation angle than for GPS, since Galileo observations at lower elevation angles have better performance than GPS observations. Finally, a new weighting approach was proposed, using two different weighting functions from the best GPS-only and Galileo-only for GPS+Galileo solution. This approach improves the results by 5% for convergence time and 30% for the troposphere delay when compared to using the same function.
An increase in temperature causes higher evaporation of water from water bodies; consequently, the water content in the atmosphere also increases. The precipitable water (PW), as the water content in the atmospheric air column, is therefore an important parameter to consider when studying climate change. The aim of this study was to analyse multi-annual precipitable water data derived from a dense Global Navigational Satellite Systems (GNSS) network. Twelve years of observations from over a hundred ASG-EUPOS stations were used to estimate changes in precipitation water values over Poland. The data were validated by comparison with the available radio-sounding data. The analysis of the GPS-based PW values showed an upward trend in the PW value of 0.078 mm/year. The spatio-temporal distribution of the mean PW values and their fluctuations over the years were studied and visualised in the form of maps. The results are congruent with the fact that Poland lies on the border of influence of both continental and oceanic climates. Our results are also consistent with other climate research concerning this region.
Historical gardens are a significant part of the cultural heritage. Exploration of such gardens is an important element of education. A particular challenge is to increase the accessibility of these facilities for the people with visual impairments (PVI). Among the aids enabling PVI visiting the gardens are tactile maps. The currently used tactile maps focus mainly on orientation and mobility. They do not allow exploration of gardens as a spatial composition, taking into account their cultural values. Therefore, the aim of our study was to develop the rules for content selection of tactile maps presenting those features of gardens that decide about their value, and to formalize these rules using the Unified Modeling Language (UML). In this research we analyzed features of 15 gardens in the five garden design styles: Baroque, Renaissance, English, Romantic, and Japanese. In result, we have proposed the way of mapping of the five garden design styles in a form useful for PVI. We have defined the procedure of content selection, as well as the catalogues of elements to be mapped at different levels of details, distinguishing repetitive and unique elements of each style. Finally, we have defined the easy-to-use list of content elements of tactile maps in the five design styles. Our solutions are described in a formalized way that allows their unambiguous understanding and universal application. The proposed solutions contribute to increasing the accessibility of gardens to PVI and allow them to learn about the values of cultural heritage of such places.
Among numerous publications about the SARS-CoV-2, many articles present research from the geographic point of view. The cartographic research method used in this area of science can be successfully applied to analyze the spatiotemporal characteristics of the pandemic using limited data and can be useful for a quick and preliminary assessment of the spread of infections. In this paper, research on the spatial differentiation of the structure and homogeneity of the system in which SARS-CoV-2 occurs, as well as spatial concentration of people infected was undertaken. The phenomena were investigated in a period of two infection waves in Germany: in spring and autumn 2020. We applied the potential model, entropy, centrographic method, and Lorenz curve in spatial analysis. The potentials model made it possible to distinguish core regions with a high level of the growth of new infections, along with areas of their impact, and regions with a low level of generation of new infections. The entropy showed the spatial distribution of differentiation of the studied system and the change of these characteristics between spring and autumn. The concentration method allowed for spatial and numerical demonstration of the concentration of infected population in a given area. We wanted to show that it is possible to draw meaningful conclusions about the pandemic characteristics using only basic data about infections, along with proper cartographic methods. The results can be used to designate the zones of the greatest threats, and thus, the areas where the most intense actions should be taken.
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