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Road condition analysis is an important research topic in many fields (such as intelligent transportation, road safety, road design analysis, and traffic analysis) and depends on road geometry parameters such as longitudinal profile and cross-slope. In this study, the extraction of road geometry parameters by unmanned aerial vehicle (UAV) with LiDAR and by a mobile photogrammetric system (MPS) designed by our research group was investigated. The purpose of this study was to obtain geometric parameters (such as road longitudinal profile and cross-slope) by using digital terrain model (DTM) surfaces derived from point cloud data acquired using UAV-LiDAR and MPS. For this purpose, a framework was developed for the extraction and comparison of longitudinal and cross-sectional profiles. First, the ground filtering approach was used to extract ground points and DTM surfaces generated from an appropriate interpolation algorithm by using ground points. Cross-sectional/longitudinal profiles of the road sections were extracted and compared with reference data. A comparison of the longitudinal profiles obtained from DTMs derived from the MPS and from UAV-LiDAR revealed root mean square error values of 1.8 cm and 2.3 cm, respectively. The average deviation of cross-slopes for both surfaces was 0.19% and 0.18%, respectively. These results show that road geometric parameters can be obtained from DTM surfaces with high accuracy. It can be concluded from the results of this study that MPS can be a favorable alternative for studies on road geometry parameters extraction.

The integration of survey-grade Global Navigation Satellite Systems (GNSS) with photogrammetric measurement studies conducted with an aircraft has the potential to meet the need for the use of grou...

The density, high accuracy, and rapid collection of geographical data for road surface and surrounding objects and the extraction of meaningful information from these data increases its importance in line with technological developments. Artificial intelligence studies and developments in cloud technology have affected the automotive industry as well as every sector and have enabled the development of driverless vehicle technology. In order to safely drive with autonomous vehicles, high definition maps that contain detailed information for road surface and its surrounding objects with high precision at centimeter-level must be used. In this context, in recent years, the development of mobile mapping systems (MMS) consisting of low-cost sensors and the development of algorithms for the evaluation of the data obtained from these systems have become increasingly popular. In this study, it was investigated whether HD maps can be obtained by using low-cost imaging sensors.

A light detection and ranging (lidar) system is one of the most important technologies used for generating digital terrain models (DTMs). The point cloud data obtained by these systems consist of data gathered from ground and nonground features. To create a DTM with high resolution and accuracy, ground and nonground data must be separated. Numerous filtering algorithms have been developed for this purpose. The aim of this study was testing the filtering performance of six different filtering algorithms in four different test areas with different land cover were selected that had topographical features and characteristics. The algorithms were adaptive triangulated irregular network (ATIN), elevation threshold with an expand window (ETEW), maximum local slope (MLS), progressive morphology (PM), iterative polynomial fitting (IPF), and multiscale curvature classification (MCC) algorithms. In the results, all the filters performed well on a smooth surface and produced more errors in complex urban areas and rough terrain with dense vegetation. The IPF filtering algorithm generated the best results for the first three test areas (smooth landscape, urban areas and agricultural areas), while ETEW performed best in the fourth test area (steep areas with dense vegetation and infrastructure).

In this study, a geometric method used to obtain rectified photographs that will form a base for drawings of building facades are examined. Mathematical model is presented by informing briefly about the method evaluated. The subject is exemplified by a test study. In the test study, firstly, the behavior of the related methods on the created artificial image was examined and the applications on the real photographic sets of the models obtained with different types and different cameras were performed. The obtained results were evaluated statistically and various conclusions were drawn and the suggestions were made for those who want to apply the method and want to do the study in this subject. Keywords: Photography, Architectural surveying, Photogrammetry, Image transformation, Rectification

Many problems in the analysis of natural terrain surface shapes and the construction of terrain maps to model them remain unsolved. Almost the whole process of thematic interpretation of aerospace information consists of a step-by-step grouping and further data conversion for the purpose of creating a completely definite, problematically oriented picture of the earth’s surface. In this article, we present application of a new method of drawing 3D visibility networks for pattern recognition and its application on terrain surfaces. For the determination of complexity of 3D surface terrain, we use fractal geometry method. We use algorithm for constructing the visibility network to analyse the topological property of networks used in complex terrain surfaces. Terrain models give a fast overview of a landscape and are often fascinating and overwhelmingly beautiful works by artists who invest all their interest and an immense amount of work and know-how, combined with a developed sense of the portrayed landscape, in creating them. At the end, we present modelling of terrain surfaces with topological properties of the visibility network in 3D space.

The extraction of artificial and natural features using light detection and ranging (Lidar) data is a fundamental task in many fields of research for environmental science. In this study, the possi...

Visual Simultaneous Localization and Mapping (VSLAM) and Visual Odometry (VO) are fundamental problems to be properly tackled for enabling autonomous and effective movements of vehicles/robots supported by vision-based positioning systems. This study presents a publicly shared dataset for SLAM investigations: a dataset collected at the Yildiz Technical University (YTU) in an outdoor area by an acquisition system mounted on a terrestrial vehicle. The acquisition system includes two cameras, an inertial measurement unit, and two GPS receivers. All sensors have been calibrated and synchronized. To prove the effectiveness of the introduced dataset, this study also applies Visual Inertial Odometry (VIO) on the KITTI dataset. Also, this study proposes a new recurrent neural network-based VIO rather than just introducing a new dataset. In addition, the effectiveness of this proposed method is proven by comparing it with the state-of-the-arts ORB-SLAM2 and OKVIS methods. The experimental results show that the YTU dataset is robust enough to be used for benchmarking studies and the proposed deep learning-based VIO is more successful than the other two traditional methods.

The transformations between ITRFXX (International Terrestrial Reference Frame) established for local and regional geodetic networks and ED50 (European Datum 1950) are routinely implemented in practice via several transformation models. In some specific cases, these models, which are widely used in practice, may be insufficient to solve the transformation problem, and thus this causes a significant loss of accuracy for the transformed points coordinates. In this study, firstly the polynomial transformations with general equations (GP) and complex numbers (CNP) were examined as alternative to well-known transformation models for modelling the distortions. In addition, transformation models based on radial basis functions (RBFs), a modern method for estimating multivariable functions, have been examined. The transformation problem has been addressed in two numerical case studies, with real data located in different regions of Turkey.

The development of the Earth Gravitational Model 2008 (EGM2008) model is a significant contribution for modeling the Earth's gravity and geoid. Recently, it can be confidently used versus geometric models following a simple refinement procedure. Several studies show that, EGM2008 can reach the accuracy of regional or local geoid models after modeling the differences between the GPS-leveling geoid heights and EGM2008 derived geoid heights at identified control points. The study focuses on a corrector surface fitting (CSF) approach based on radial basis functions (RBF) as improvement procedure for EGM2008. A detailed mathematical model and solution algorithm of the proposed model is given, and it has been applied in different test areas covering the city borders of Bursa, Konya, Denizli and Gaziantep in Turkey. Accuracy of the improved model was evaluated in scattered check points within test regions. The geoid heights of all check points obtained by GPS-leveling measurements were compared with the geoid heights obtained from improved model. The discrepancies between the calculated and measured geoid heights were analyzed and discussed. O desenvolvimento do modelo Earth Gravitational Model 2008 (EGM2008) é uma contribuição significante para a modelagem do geoide e gravidade da Terra. Atualmente, ele pode ser utilizado com segurança em conjunto com modelos geométricos, seguindo um procedimento simples de refinamento. Vários estudos mostram que o EGM2008 pode alcançar a acurácia dos modelos geoidais regionais ou locais após modelar as diferenças entre as alturas geoidais do GPS-nivelamento e as alturas geoidais derivadas do EGM2008 em pontos de controle apropriadamente selecionados. O estudo centra-se no ajuste de uma superfície de correção (CSF- Corrector Surface Fitting) baseada em funções de base radial (RBF - Radial Basis Functions) como procedimento de melhoria para o EGM2008. Nesse artigo são apresentados o modelo matemático detalhado e o algoritmo de solução do modelo proposto, aplicados em diferentes áreas de teste, abrangendo as fronteiras das cidades de Bursa, Konya, Denizli e Gaziantep, na Turquia. A acurácia do modelo melhorado foi avaliada em pontos de verificação dispersos nas regiões de teste. As alturas do geoide de todos os pontos de verificação obtidos por medições de GPS-nivelamento foram comparados com as alturas geoidais obtidas do modelo melhorado. As discrepâncias entre as alturas geoidais calculadas e medidas foram analisadas e discutidas.

WOS: 000319280300001, Turkey occupies a critical segment in the Alpine-Himalayan orogenic belt that is characterized by many active fault lines. Numerous earthquakes of varying magnitudes have occurred on these fault lines over the years. A significant portion of these earthquakes have been recorded along the Fethiye Burdur Fault Zone (FBFZ). Unfortunately, the latest earthquakes that happened on the FBFZ led to a large loss of human life and extensive economic losses. Southwest Anatolia, including the FBFZ, is monitored by 44 Global Navigation Satellite System (GNSS) stations, comprised of 16 permanent and 28 campaign stations. Measurements have been conducted by combining observations from 2003 to 2006 (Erdogan et al. in J. Earthq. Eng. 12(2):109-118, 2008) with new observations from 2009 and 2010. The combined processes have yielded an updated velocity field of the region. In addition, the effects of the post 2007 earthquakes on the GNSS stations were also investigated. The strain analysis based on the observations made between 2003 and 2010 display high consistency with the earthquakes that occurred in the region. Also, it was observed that the strain analysis is in accordance with the North-South opening created as a result of the African plate being submerged under the Anatolian plate in the southern of the island of Crete., Turkish Scientific and Technical Research Agency (TUBITAK) project [108Y298], This research is supported by the Turkish Scientific and Technical Research Agency (TUBITAK) project no: 108Y298.

This study examines the degree of precision of precise point positioning system currently implemented in the Bernese GPS software 5.0 by zero differenced observations. The relationship between the accuracy of PPP and observation duration has been investigated using GPS data from a subset of IGS tracking stations observed over 7 days in different periods of year 2007. In the beginning, short reviews about PPP algorithm principle are given. Then, the results of several processing scenarios are presented and their respective precisions and convergence results are analyzed. Finally, with default parameters, accuracy assessments of PPP solutions are discussed. Investigation results have shown that PPP provides cm-level precision quite easily by using appropriate processing parameters within a few hours of observation. A faster convergence can be available for the north component in any case. The east component requires a convergence period more than two times longer than the north component. The east component provides a better precision than the height component after 2–3 h. For the shorter periods of observation, it is impossible to perform a reliable and accurate positioning with PPP due to the unresolved ambiguity. The repeatability and the precision ratio of the positioning are very low and unreliable for observations of a 5-min period. The mean values of RMS errors are about 0.25–0.30 m for north and east, and 0.5 m for up components. A great improvement can be achieved within a 30-min period, where mean RMS errors of 0.09 cm, 0.04 m and 0.11 m, respectively, in north, east and up were obtained. This precision could be improved up to three to five times by using, respectively, 2–8 h observations. It is possible to obtain at mm to cm-level precision at the end of the 12 h observation for all the coordinate components. Finally, 24 h data processing produced 0.0031, 0.0058 and 0.0088 m RMS errors for the north, east and up components in sequence. For all these cases, north components are more precise than up and east.

Preserving forests and their value to us is indispensable to human life. When making forest preservation plans and managing forests efficiently, it is necessary to use three dimensional (3D) models of the forest regions. Apart from the traditional and photogrammetric methods used for producing these maps, the LIght Detection and Ranging (LIDAR) measurement technique with its various advantages has been used in recent years. This paper explains the principle of the operation of the LIDAR measurement system and discusses the determination of digital elevation models (DEM) of forest areas and their usage in 3D models. This test study aims to convert the scattered distributed 3D datasets obtained from airborne LIDAR technology to a digital elevation model with a regular grid format. One of the most significant aspects of this process, the interpolation method, which affects the quality of the final product when generating the digital elevation model, is examined with respect to data density and distribution, grid size interval and terrain type.

We know that position accuracies from relative and static Global Positioning System (GPS) measurements are degraded by a variety of physical, hardware and software effects. As a result, users often take special precautions to minimise these effects and, hopefully, improve their accuracies when planning and making measurements. In this study, the effects of the baseline length (BL) and observation duration (OD) on vertical and horizontal positioning errors for relative, static GPS measurements were experimentally evaluated. In making this evaluation, 5 min to 24 hours GPS data, collected over a 15 day period, from the Southern California Integrated GPS Network (SCIGN), were analyzed. The root mean square (RMS) of the differences between the true and measured vertical (up/ellipsoidal height) and horizontal (north and east/latitude and longitude) positions of the included stations were computed and then used to create empirical error equations dependent upon the BL and OD. Considerations for the numb...

The purpose of this study is the solution of the transformation problem between the GPS networks and old geodetic networks based on the national coordinate system alternatively by a 3-dimensional robust polynomial transformation (3D.R.P.T). This study focuses on and probes 3D similarity (3D.S.T), 3D polynomial transformation with least squares estimate as equal-weighted (L.S.3D.P.T), 3D polynomial transformation based on weight with the inverse of the distances of common points to the centre of gravity (W.L.S.3D.P.T) and robust estimate approaches that are re-weighted and are based on iterative solution. A detailed mathematical model and solution algorithm of the proposed model is given, and it has been applied in a test area covering the city borders of Istanbul for which its results were studied and compared to other three methods.

Most commonly used method for the determination of geoid is the evaluation of GPS (Global Positioning System) and levelling measurements together. Despite the fact that geometric levelling (GL) is in general easy and practicable, it is a measurement method that is hard and uneconomic to apply particularly in mountainous, hilly and rugged areas. This study aims the use of precise trigonometric levelling (PTL) method instead of GL for the determination of precise geoid heights. The method has been probed into in consideration of the accuracy, practicability, measurement and evaluation criteria, and has been compared with GL measurement results. In addition, geoid profiles that have been determined both (GPS_GL) and (GPS_PTL) measurements have been compared with TG-99A (Turkish Geoid-1999A) and IGNA (Istanbul GPS Network) geoid models to explore their consistency.

In geodetic networks, observations are measured repetitively, and the mean values of these observations are used for network adjustment, outlier detection, deformation analysis, etc. These repetitive observations are independent, and if one of them has outlier, the effect of the outlier decreases depending on the computed mean value. Also, the mean operator—a kind of least-squares estimation—smears the effects of the outlier over other observations. In this case, the detectability and reliability rates of the outlier detection method decrease. Moreover, the undetectable outliers spoil both of the estimated parameters and their standard deviations, causing incorrect results. To form a univariate sample, the same quantity must be measured at least twice for geodetic networks. The univariate case is simpler than the multivariate case, and if the repetitive observations may be analyzed as a univariate case, more reliable results can be obtained for outlier detection. In this study, the univariate anal...

Applicability of Terrestrial Laser Scanners/Scanning (TLS) in deformation measurement in dams is an active area of study. With the advance of modern technology, accuracy of measurements is much improved by developments in design of terrestrial laser scanners. Currently, this technology is used in large and complex engineering structures such as dams. Although TLS is a high cost technology, it is particularly used in monitoring of dam deformations, due to its speed in obtaining thousands of data points, ability to visualize the scanned object and its environment with high accuracy and ability to take long-range measurements. In order to determine the effect of change in water reservoir levels on body of the dam, TLS are used to take deformation measurements in different time intervals, where the water level was at maximum, minimum and medium levels. This paper provides an overview of terrestrial laser scanning technology for deformation monitoring. The concrete arch dam in Antalya Oymapinar, Turkey was used for case study. Four different scannings were performed in this dam in order to verify the replicability of TLS results on same water levels and equivalent conditions. Digital Surface Models reflecting dam surface have been created. Results obtained from surface model differences were examined using surface matching method. A aplicação dos Scanners Laser Terrestres/Digitalização (SLT) para a medição de deformações em barragens representa uma área ativa de estudo. Com o avanço das tecnologias modernas, a exatidão da medição melhorou muito graças aos desenvolvimentos na conceção dos scanners laser terrestres. Atualmente, esta tecnologia é utilizada em grandes e complexas estruturas de engenharia tais como as barragens. Embora, os SLT sejam uma tecnologia de custo elevado, são particularmente utilizados na monitorização de deformações de barragens, devido à velocidade na obtenção de centenas de pontos de dados, à capacidade para visualizar o objeto digitalizado e o seu ambiente com elevada exatidão e capacidade para medições de longo alcance. Com a finalidade de determinar o efeito das alterações dos níveis de um reservatório de água no corpo de uma barragem, os SLT são utilizados para tirar as medições das deformações em diferentes intervalos de tempo, quando o nível da água se encontra em níveis máximos, mínimos ou médios. Este documento apresenta uma visão geral da tecnologia de digitalização laser terrestre para a medição de deformações. A barragem situada em Antalya Oymapinar, na Turquia, foi utilizada para o estudo de caso. Foram realizadas quatro digitalizações diferentes nessa barragem, a fim de verificar a reprodutibilidade dos resultados dos SLT nos mesmos níveis de água e em condições idênticas. Os Modelos Digitais de Superfície que refletiram a superfície da barragem foram criados. Os resultados obtidos a partir das diferenças do modelo de superfície foram examinados utilizando o método de correspondência de superfície.