Searching for Determinism in Mobile Gravimetry Data

Abstract. Many of today´s world wide challenges such as climate change, water supply and transport systems in cities or movements of crowds need spatio-temporal data to be examined in detail. Thus the number of examinations in 3D space dealing with geospatial objects moving in space and time or even changing their shapes in time will rapidly increase in the future. Prominent spatio-temporal applications are subsurface reservoir modeling, water supply after seawater desalination and the development of transport systems in mega cities. All of these applications generate large spatio-temporal data sets. However, the modeling, management and analysis of 3D geo-objects with changing shape and attributes in time still is a challenge for geospatial database architectures. In this article we describe the application of concepts for the modeling, management and analysis of 2.5D and 3D spatial plus 1D temporal objects implemented in DB4GeO, our service-oriented geospatial database architecture. An example application with spatio-temporal data of a landfill, near the city of Osnabrück in Germany demonstrates the usage of the concepts. Finally, an outlook on our future research focusing on new applications with big data analysis in three spatial plus one temporal dimension in the United Arab Emirates, especially the Dubai area, is given.

CryoSat-2 altimetry has become a valuable tool for monitoring the water level of lakes. In this study, a concentrated probability density function (PDF) method was proposed for preprocessing CryoSat-2 Geophysical Data Record (GDR) data. CryoSat-2 altimetry water levels were preprocessed and evaluated by in situ gauge data from 12 lakes in China. Results showed that the accuracy of the raw GDR data was limited due to outliers in most of the along-track segments. The outliers were generally significantly lower than the in situ values by several meters, and some by more than 30 m. Outlier detection, therefore, improves upon the accuracy of CryoSat-2 measurements. The concentrated PDF method was able to greatly improve the accuracy of CryoSat-2 measurements. The preprocessed CryoSat-2 measurements were able to observe lake levels with a high accuracy at nine of the twelve lakes, with an absolute mean difference of 0.09 m, an absolute standard deviation difference of 0.04 m, a mean root mean square error of 0.27 m, and a mean correlation coefficient of 0.84. Overall, the accuracy of CryoSat-2-derived lake levels was validated in China. In addition, the accuracy of Database for Hydrological Time Series of Inland Waters (DAHITI) and HYDROWEB water level products was also validated by in situ gauge data.

<p>Satellite altimetry is a technique of measuring height. Originally developed to observe sea level dynamics, altimetry has proven its usefulness in monitoring inland waters. Over the recent years these observations became an important supplement to the classical river gauge records. Due to the improvement of the accuracy of altimetric measurements, river water levels are being used in numerous hydrological projects, aiming to calculate water storage or to predict water levels and river discharges. Despite the improving quality of altimetric data, the accuracy of river stage measurements is still in the decimetre range, an order of magnitude lower than altimetry-based sea level observations. This is due to several factors that can lead to the deterioration of altimeter readings.</p><p>Our study is the first attempt to assess the accuracy of water levels measured by the Sentinel-3A altimetry at virtual stations (intersections of a satellite ground tracks and a river channel, hereinafter abbreviated as VS) located along Polish rivers. Further, this study aims to investigate the influence of the environmental factors on the data accuracy. The study is conducted on six biggest Polish rivers (Vistula, Odra, Warta, Bug, Narew, San) which drain predominantly lowlands, and – based on width – can be classified as small and medium rivers (40–610 m in width).</p><p>In order to assess the accuracy of measurements at virtual sites, we compare water level anomalies of these readings with stages from two adjacent gauges: one downstream and one upstream a VS. In this study we used Sentinel-3A water levels from the Hydroweb database (http://hydroweb.theia-land.fr/ – last access 09.01.2022). The time span of gauge and altimetry data ranges from April 2016 to August 2019. Since the virtual sites are located up to 73 km away from the adjacent gauges (with mean distance of 20.12 km), we decided to calculate the time shift occurring between the analysed stations. Such a unification of times is based on a two-gauge relationship, calculated for each of the satellite measurements.</p><p>We found that the root mean square error ranges from 0.12 to 0.44 m, with mean of 0.22 m. The Nash–Sutcliffe efficiency (NSE) varies between 0.40 and 0.98 (with mean of 0.84) for 67 pairs of time series, out of 68 considered. We found no correlation between the accuracy of Sentinel-3A water levels and the river width, neither for the small nor medium river sections. Likewise, land cover (determined using the Corine Land Cover 2018 data) has not been identified as an environmental factor to constrain the data accuracy. However, we found that complex river channel morphology (i.e. the occurrence of sandbars) and the unfavourable geographical setting of the VS (river channel parallel to satellite ground track or its multiple crossing) occur more often at VS with lower NSE (⩽0.8).</p><p>This study confirms the usability of the Sentinel-3A altimetry over Polish rivers and identifies factors to constrain its accuracy. The research is supported by the National Science Centre, Poland, through the project no. 2020/38/E/ST10/00295. Our results were recently published in <em>Journal of Hydrology</em> (https://doi.org/10.1016/j.jhydrol.2021.127355).</p>

The purpose of this study is to investigate the efficient method of collecting 3D cloud points of head profile Malaysian. The objective of the research is to analyse the head anthropometric data with having the accuracy of the computations in several typical settings characterized by time-consuming, resolution levels and computed cloud point file sizes with eliminating artefacts. This case study approach is a statistical analysis and comparison of existing manual anthropometric and digital landmark measurements. This research is also dedicated to determining the relative accuracy of anthropometric head profile measurement using a 3D scanner to digitally generate a cloud point 3D file. In addition, the scanned cloud point 3D file is to be measured, and the degree of closeness of the manual anthropometric method to the absolute true value can be calculated. Participants were among Universiti Teknologi Malaysia’s students. They volunteered to share their head profile to collect anthropometric data. The steps of process procedures were conducted by setup a 3D handheld scanner, creating and collecting data from manual anthropometric measurement, scanning and reconstructing head profile, editing scan data and parameters, creating mesh data and transferring data to the software Geomagic, and carrying out data analysis and comparison by using Minitab. Thus, the analysis of variance and the standard deviation is conducted by using Minitab. Three sample objects were specified and analysed, their parameters in the registration process and the relative accuracy of the measurement data. As result, data comparison between the percentage errors of high detail, medium detail and low detail for each set of different fixed time runs. The high detail setting, which gives the average absolute difference, achieves the highest accuracy size (0.02mm) within the given nine-time frames. In comparison, the highest average absolute difference for low detail given 1.04mm, the second was medium detail given 0.97mm and the third was high detail given 0.93mm. Based on the overall data observation, the three sets of detail resolution settings at different fixed times contributed to the measurement with an average absolute difference between 0.02mm and 1.04mm. The accuracy of data can be optimized between the processing time and the typical settings of the resolution. The overall data measurement was analysed and the best time-consuming 3D scanning is shown in the figure, each resolution of a typical setting is between 210 seconds and 240 seconds. The purpose of carrying out this experiment is intending to reduce the scan-time consumption of 3D scanning, to minimize the variability and closer to well-perform anthropometric measurement data that has high accuracy. In conclusion, the accuracy of the 3D scan model is affected by the time processing and the typical settings of the resolution during the head contour scan. Therefore, optimum typical settings of the 3D scanner can help users minimise the impact of time-consuming and quality issues on the final 3D head profile scanning model.

We investigate the power spectra and cross spectra derived from the three components of the vector magnetic field measured on a straight horizontal path above a statistically stationary source. All of these spectra, which can be estimated from the recorded time series, are related to a single two‐dimensional power spectral density via integrals that run in the across‐track direction in the wavenumber domain. Thus the measured spectra must obey a number of strong constraints: for example, the sum of the two power spectral densities of the two horizontal field components equals the power spectral density of the vertical component at every wavenumber and the phase spectrum between the vertical and along‐track components is always π/2. These constraints provide powerful checks on the quality of the measured data; if they are violated, measurement or environmental noise should be suspected. The noise due to errors of orientation has a clear characteristic; both the power and phase spectra of the components differ from those of crustal signals, which makes orientation noise easy to detect and to quantify. The spectra of the crustal signals can be inverted to obtain information about the cross‐track structure of the field. We illustrate these ideas using a high‐altitude Project Magnet profile flown in the southeastern Pacific Ocean.

Becoming-City

Water level forecasting using recorded time series can provide a local modelling capability to facilitate local proactive management practices. To this end, hourly sea water level time series are investigated. The records collected at the Hillarys Boat Harbour, Western Australia, are investigated over the period of 2000 and 2002. Two modelling techniques are employed: low-dimensional dynamic model, known as the deterministic chaos theory, and genetic programming, GP. The phase space, which describes the evolution of the behaviour of a nonlinear system in time, was reconstructed using the delay-embedding theorem suggested by Takens. The presence of chaotic signals in the data was identified by the phase space reconstruction and correlation dimension methods, and also the predictability into the future was calculated by the largest Lyapunov exponent to be 437 h or 18 days into the future. The intercomparison of results of the local prediction and GP models shows that for this site-specific dataset, the local prediction model has a slight edge over GP. However, rather than recommending one technique over another, the paper promotes a pluralistic modelling culture, whereby different techniques should be tested to gain a specific insight from each of the models. This would enable a consensus to be drawn from a set of results rather than ignoring the individual insights provided by each model.

Traffic problems continue to deteriorate because of increasing population in urban areas that rely on many modes of transportation, the transportation infrastructure has achieved considerable strides in the last several decades. This has led to an increase in congestion control difficulties, which directly affect citizens through air pollution, fuel consumption, traffic law breaches, noise pollution, accidents, and loss of time. Traffic prediction is an essential aspect of an intelligent transportation system in smart cities because it helps reduce overall traffic congestion. This article aims to design and enforce a traffic prediction scheme that is efficient and accurate in forecasting traffic flow. Available traffic flow prediction methods are still unsuitable for real-world applications. This fact motivated us to work on a traffic flow forecasting issue using Vision Transformers (VTs). In this work, VTs were used in conjunction with Convolutional neural networks (CNN) to predict traffic congestion in urban spaces on a city-wide scale. In our proposed architecture, a traffic image is fed to a CNN, which generates feature maps. These feature maps are then fed to the VT, which employs the dual techniques of tokenization and projection. Tokenization is used to convert features into tokens containing Vision information, which are then sent to projection, where they are transformed into feature maps and ultimately delivered to LSTM. The experimental results demonstrate that the vision transformer prediction method based on Spatio-temporal characteristics is an excellent way of predicting traffic flow, particularly during anomalous traffic situations. The proposed technology surpasses traditional methods in terms of precision, accuracy and recall and aids in energy conservation. Through rerouting, the proposed work will benefit travellers and reduce fuel use.

Dynamic pricing techniques for Intelligent Transportation System in smart cities: A systematic review

Rajshahi is the fourth largest city of Bangladesh having a population of around 8 lakhs with a high urbanization rate of 32.93%. The transportation system of Rajshahi is comprising of motorized transport (bus, mini-bus, truck, car, auto-rickshaw, auto-tempo, motorcycle, etc.) and nonmotorized transports (viz. rickshaw, rickshaw van, bicycle, pushcart, etc.). The rapidly increasing population along with the diversified land-use patterns generating considerable transport demands on the transportation system and the higher number of transport vehicles causes numerous problems in the city such as traffic congestion, road accidents, less effective and inefficient traffic movement, inadequate traffic management, environmental pollution, sound pollution and so on. The number of private vehicles is increasing day by day because there is no public transport system with an effective public transport network within the city. As a result, major shares of the roads are occupied by the small vehicles make complexities for efficient traffic movement. According to a recent analysis of RCC (Rajshahi City Corporation) the annual average growth rate of these traffics is motorized (8.50%), auto-rickshaw (12.30%), motorcycle (12.60%), truck (5.30%) and car (5.70%). So, the upcoming future of the transport sector in Rajshahi city is going to face an uncertain challenge through the increasing population and rapidly growing motorized traffics which will affect the efficiency and effectiveness of the transport systems. In view of the worsening traffic congestion and deterioration inaccessibility, level of service, safety, and operational efficiency, it is time to introduce the Bus Rapid Transit (BRT). In this paper, an attempt has been made to provide an overview of the public transportation system of Rajshahi city and five major BRT routes have been proposed for ever-increasing public transport demand towards alleviation of congestion level and achieving a sustainable urban public transport system.

In this paper the procedure and methodology of vibration testing on a Gazelle helicopter are presented with the aim to define efficiency of vibration damping at the structure-pilot seat connection. A particular attention is paid to the theoretical basis of helicopter vibrations, definition of working frequency, regime and profile of flight during the test. The results of the vibration measurement are shown in the frequency domain. Introduction Nowadays, possibility of defining loads and vibrations is one of the most important requests in the design and modification of processes on helicopters. The loads occuring on the main rotor during flight are the basic source of vibrations on the helicopter. Possibilities to satisfy international standards in the area of structural and human vibrations are based on continuous and adequate measurement and analysis of the vibration levels on all elements of helicopters. This paper shows the procedures of vibration measuring and analyzing in order to define efficiency of vibration damping using a modern acquisition system NetdB 12 and its software dBFA Suite. Theoretical analysis of vibration sources on the helicopter main rotor The helicopter rotor operates in a complex aerodynamic flow field. The aerodynamic loads on the rotor blade vary considerably as it moves around the rotor disc, and in steady flight these loads are periodic. A particular attention is paid to a theoretical basis of vibration sources on a helicopter. A complex aerodynamic field in the plane of the helicopter main rotor during different profiles of flight is shown and explained. This part of the paper gives the equations of force and moments on the main rotor with the aim to define basic working frequencies. Sources of vibrations and the determination of working frequencies on the gazelle helicopter The sources of vibrations on the Gazelle helicopter (main rotor, tail rotor and engine) are described as well as the vibration transfer from the sources to the structure through the helicopter transmission and the structure as a receiver of vibrations. The working frequencies of the Gazelle helicopter are defined and the causes for avoiding the low vibration frequency range are explained. Methodology and procedure of vibration testing on the gazelle helicopter The procedure of vibration testing has a few steps (pre-test, test and post test step), given in Fig. 5. After the determination of working frequencies and the testing point, the next step is selecting test equipment and installment of the accelerometers and other probes. After these preparations, the last step in the pre-test procedure is choosing the flight profiles in which the vibrations are measured. The results of testing and analysis of vibration damping at the structure - pilot seat connecting point The testing results are collected in the test phase. The results of the vibration measurement are shown in the time and frequency domain for the chosen flight conditions of the Gazelle helicopter. The results are given for two profiles of flight (for acceleration and for the left and right turn). The analysis must give an answer about the efficiency of vibration damping at the structure - pilot seat connecting point. The conclusions must not be ambiguous and must give enough elements for making a decision about subsequent actions. Vibration levels of in the acceleration phase For this phase of flight, all helicopter flight parameters are recorded and given as a function of time (velocity, altitude, drift of commands, loads und angular velocity) while the vibrations are given in the frequency domain. The vibrations at the tested connecting point are analyzed in the function of velocity, followed by the conclusions and comments about the level of vibrations in the phase of acceleration. Level of vibrations during the left and the right turn For this profile of flight, the frequency spectrum for both turns is given and the fundamental difference in that spectrum is explained. The analysis of these two turns reveals the increase of the vibration level at the test point at a particular frequency. Conclusion The illustrated methodology and the procedures of measuring and analyzing the low-frequency vibration range on the Gazelle helicopter can be applied for all types of aircraft which are in operational use in the Serbian Air Forces. The shown procedure can be used for measuring and analyzing vibrations on all elements of helicopter systems, aiming at meeting international standards, continuous system developing, modifying technical systems and detecting potential failure elements in the systems in operational service. .

Non-stationarity time series are very common in physical, biological and in real-world systems in general, ranging from geophysics, econometrics or electroencephalography to logistics. Identifying, detecting and adapting learning algorithms to non-stationary environments is a fundamental task in many data mining scenarios; however it is often a major challenge for current methodologies. Data analysis in the context of time-varying statistical moments is a very active research direction in machine learning and in computational statistics; but theoretical insights into latent causes of non-stationarity in empirical data are very scarce. In this study, we evaluate the capacity of the trajectory classification error statistic in order to detect a significant variation in the underlying dynamics of data collected in multiple stages. We analysed qualitatively the conditions leading to observable changes in non-stationary data generated by Duffing non-linear oscillators; which are ubiquitous models of complex classification problems. Analyses are further benchmarked in a dataset consisting of atmospheric pollutants time series.

The article considers the issues of spatial unevenness of the structure of mobility of city residents. The purpose of the study is to increase the accuracy of forecasting the parameters of the transport system based on data analysis and differentiation of corre-spondence of city residents using machine learning methods. The study puts forward a hypothesis that the structure of transport demand is distributed unevenly across the city and depends on the costs of implementing correspondence. To study the corre-spondence of city residents, the article uses a transport macromodel of the city of Tyumen. An analysis of the conditions for the formation of costs for the implementa-tion of correspondence, which are recorded in the macromodel, is provided. To ana-lyze the correspondence and assess the impact of the parameters of the city's transport system using machine learning, clustering of correspondence was carried out, which are grouped into 5 clusters. The results of data processing in the transport model showed that the distance and travel time have the greatest impact on the share of travel on individual and public transport. For two clusters, with an increase in distance and travel time, the share of trips on public transport decreases, for the other two, on the contrary, it increases. In this case, the general form of the dependence for all corre-spondences is described by the parabola equation. The formation of 5 correspondence clusters is due to the different levels of transport services, which are determined by the level of development of the street and road network, public transport and its infra-structure, taking into account the actual division of the city into 4 parts by the river, the Trans-Siberian Railway and Fedyuninsky Street. The further direction of research is related to determining the most significant factors for each cluster and increasing the arbitrariness of working with transport macromodels due to the development of digital twins of urban transport.

Intelligent measurement methods in technical diagnosis and quality assurance - a comparison

Considering the influence of artificial environmental noise to study cough time–frequency features