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Nowadays, the availability of affordable multi-constellation multi-frequency receivers has broadened access to accurate positioning. The abundance of satellite signals coupled with the implementation of ground- and satellite-based correction services has unlocked the potential for achieving real-time centimetre-level positioning with low-cost instrumentation. Most of the current and future applications cannot exploit well-consolidated satellite positioning techniques such as Network Real Time Kinematic (RTK) and Precise Point Positioning (PPP); the former is inapplicable for large user bases due to the necessity of a two-way communication link between the user and the NRTK service provider, while the latter necessitates long convergence times that are not in keeping with kinematic application. In this context, the hybrid PPP-RTK technique has emerged as a potential solution to meet the demand for real-time, low-cost, accurate, and precise positioning. This paper presents an Internet of Things (IoT) GNSS device developed with low-cost hardware; it leverages a commercial PPP-RTK correction service which delivers corrections via IP. The main target is to obtain both horizontal and vertical decimetre-level accuracies in urban kinematic tests, along with other requisites such as solution availability and the provision of connection ports for interfacing an IoT network. A vehicle-borne kinematic test has been conducted to evaluate the device performance. The results show that (i) the IoT device can deliver horizontal and vertical positioning solutions at decimetre-level accuracy with the targeted solution availability, and (ii) the provided IoT ports are feasible for gathering the position solutions over an internet connection.
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GNSS has become ubiquitous in high-precision applications, although the cost of high-end GNSS receivers remains a major obstacle for many applications. Recent advances in GNSS receiver technology have led to the development of low-cost GNSS receivers, making high-precision positioning available to a wider range of users. One such technique for achieving high-precision positioning is Precise Point Positioning-Real Time Kinematic (PPP-RTK). It is a GNSS processing technique that combines the PPP and RTK approaches to provide high-precision positioning in real time without the need for a base station. In this work, we aim to assess the performance of the low-cost u-blox ZED-F9P GNSS module in PPP-RTK mode using the low-cost u-blox ANN-MB antenna. The experiment was designed to investigate both the time it takes the receiver to resolve the phase ambiguity and to determine the positioning accuracies achievable. Results showed that the u-blox ZED-F9P GNSS module could achieve centimeter-level positioning accuracy in about 60 s in PPP-RTK mode. These results make the PPP-RTK technique a good candidate to fulfill the demand for mass-market accurate and robust navigation since uses satellite-based corrections to provide accurate positioning information without the need for a local base station or network. Furthermore, due to its rapid acquisition capabilities and accurate data georeferencing, the technique has the potential to serve as a valuable method to improve the accuracy of the three-S techniques (GIS, remote sensing, and GPS/GNSS).
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Imagem de Difusão por Ressonância Magnética , Mapeamento Geográfico , Fenômenos Biomecânicos , Tecnologia , TelemetriaRESUMO
Continuous and unplanned urbanization, combined with negative alterations in land use land cover (LULC), leads to a deterioration of the urban thermal environment and results in various adverse ecological effects. The changes in LULC and thermal characteristics have significant implications for the economy, climate patterns, and environmental sustainability. This study focuses on the Province of Naples in Italy, examining LULC changes and the Urban Thermal Field Variance Index (UTFVI) from 1990 to 2022, predicting their distributions for 2030. The main objectives of this research are the investigation of the future seasonal thermal characteristics of the study area by characterizing land surface temperature (LST) through the UTFVI and analyzing LULC dynamics along with their correlation. To achieve this, Landsat 4-5 Thematic Mapper (TM) and Landsat 9 Operational Land Imager (OLI) imagery were utilized. LULC classification was performed using a supervised satellite image classification system, and the predictions were carried out using the cellular automata-artificial neural network (CA-ANN) algorithm. LST was calculated using the radiative transfer equation (RTE), and the same CA-ANN algorithm was employed to predict UTFVI for 2030. To investigate the multi-temporal correlation between LULC and UTFVI, a cross-tabulation technique was employed. The study's findings indicate that between 2022 and 2030, there will be a 9.4% increase in built-up and bare-land areas at the expense of the vegetation class. The strongest UTFVI zone during summer is predicted to remain stable from 2022 to 2030, while winter UTFVI shows substantial fluctuations with a 4.62% decrease in the none UTFVI zone and a corresponding increase in the strongest UTFVI zone for the same period. The results of this study reveal a concerning trend of outward expansion in the built-up area of the Province of Naples, with central northern regions experiencing the highest growth rate, predominantly at the expense of vegetation cover. These predictions emphasize the urgent need for proactive measures to preserve and protect the diminishing vegetation cover, maintaining ecological balance, combating the urban heat island effect, and safeguarding biodiversity in the province.
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The new generation of Android smartphones is equipped with GNSS chips capable of tracking multi-frequency and multi-constellation data. In this work, we evaluate the positioning performance and analyze the quality of observations collected by three recent smartphones, namely Xiaomi Mi 8, Xiaomi Mi 9, and Huawei P30 pro that take advantage of such chips. The analysis of the GNSS observation quality implies that the commonly employed elevation-dependent function is not optimal for smartphone GNSS observation weighting and suggests an application of the C/N0-dependent one. Regarding smartphone code signals on L5 and E5a frequency bands, we found that they are characterized with noticeably lower noise as compared to E1 and L1 ones. The single point positioning results confirm an improvement in the performance when the weights are a function of the C/N0-rather than those dependent on the satellite elevation and that a smartphone positioning with E5a code observations significantly outperforms that with E1 signals. The latter is expressed by a drop of the horizontal RMS from 8.44 m to 3.17 m for Galileo E1 and E5a solutions of Xiaomi Mi 9 P30, respectively. The best positioning accuracy of multi-GNSS single-frequency (L1/E1/B1/G1) solution was obtained by Huawei P30 with a horizontal RMS of 3.24 m. Xiaomi Mi 8 and Xiaomi Mi 9 show a horizontal RMS error of 4.14 m and 4.90 m, respectively.
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In August 2016, Milena (E14) and Doresa (E18) satellites started to broadcast ephemeris in navigation message for testing purposes. If these satellites could be used, an improvement in the position accuracy would be achieved. A small error in the ephemeris would impact the accuracy of positioning up to ±2.5 m, thus orbit error must be assessed. The ephemeris quality was evaluated by calculating the SISEorbit (in orbit Signal In Space Error) using six different ephemeris validity time thresholds (14,400 s, 10,800 s, 7200 s, 3600 s, 1800 s, and 900 s). Two different periods of 2018 were analyzed by using IGS products: DOYs 52-71 and DOYs 172-191. For the first period, two different types of ephemeris were used: those received in IGS YEL2 station and the BRDM ones. Milena (E14) and Doresa (E18) satellites show a higher SISEorbit than the others. If validity time is reduced, the SISEorbit RMS of Milena (E14) and Doresa (E18) greatly decreases differently from the other satellites, for which the improvement, although present, is small. Milena (E14) and Doresa (E18) reach a SISEorbit RMS of about 1 m (comparable to that of the other Galileo satellites reach with the nominal validity time) when validity time of 1800 s is used. Therefore, using this threshold, the two satellites could be used to improve single point positioning accuracy.
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The integration of Global Navigation Satellite Systems (GNSS) with Inertial Navigation Systems (INS) has been very actively researched for many years due to the complementary nature of the two systems. In particular, during the last few years the integration with micro-electromechanical system (MEMS) inertial measurement units (IMUs) has been investigated. In fact, recent advances in MEMS technology have made possible the development of a new generation of low cost inertial sensors characterized by small size and light weight, which represents an attractive option for mass-market applications such as vehicular and pedestrian navigation. However, whereas there has been much interest in the integration of GPS with a MEMS-based INS, few research studies have been conducted on expanding this application to the revitalized GLONASS system. This paper looks at the benefits of adding GLONASS to existing GPS/INS(MEMS) systems using loose and tight integration strategies. The relative benefits of various constraints are also assessed. Results show that when satellite visibility is poor (approximately 50% solution availability) the benefits of GLONASS are only seen with tight integration algorithms. For more benign environments, a loosely coupled GPS/GLONASS/INS system offers performance comparable to that of a tightly coupled GPS/INS system, but with reduced complexity and development time.
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The Environmental Protection Agency of the Campania region in Italy (ARPAC) manages a groundwater quality monitoring network. For almost all the polluted waters, the key parameter driving the classification is the concentration of nitrate; hence, the Campania region, in coherence with the EU regulations, outlined the vulnerable areas and undertook remediation policies. The best groundwater quality is recorded for carbonate aquifers of the Apennine chain; on the contrary, the Tyrrhenian coastal plains are affected by severe contamination, with a locally very contaminated groundwater of the shallow and also the deeper aquifers. The study is especially focused on a large coastal plain of Campania region, where nitrate concentration sometimes exceeds 200 mg/L. The study, based on almost 200 sampling points for the whole region during the period 2003-2015 (approx two samples per year), verified the effectiveness of the groundwater monitoring network, the present distribution of nitrate in groundwater, and the evolution of nitrate trends at different scales: regional, groundwater body, and single well, using spatial and time series statistical approaches. Significant variations in contamination evolution within the study area have been observed and the correlation with land use has been highlighted.
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Água Subterrânea/química , Nitratos/análise , Poluentes Químicos da Água/análise , Poluição da Água/análise , Qualidade da Água , Abastecimento de Água , Monitoramento Ambiental/métodos , União Europeia , Regulamentação Governamental , Humanos , Itália , Óxidos de NitrogênioRESUMO
A novel electrophoretic alpha-lactalbumin (alpha-la) variant was detected in the Italian water buffalo breed. The isoelectric point of the variant, labelled A, was lower than the most frequent variant B. It presented an allelic frequency of 0.5% compared with the 97.1% of the BB allele. From Liquid Chromatography-Electrospray Ionization/Mass spectrometry, the molecular mass of the two alpha-la A and B variants were measured as 14,235.1+/-0.8 and 14,236.1+/-0.9 Da, respectively. The two proteins were sequenced and differentiated from one another by a single amino acid substitution, Asn45(B)-->Asp45(A). As this amino acid substitution altered the N-glycosylation sequence consensus Asn45-X-Ser46 it may be deduced that the protein glycosylation level of the alpha-la A would decrease.