Feasibility of extracting highway vertical profiles from LiDAR data

2018 ◽  
Vol 45 (5) ◽  
pp. 418-421 ◽  
Author(s):  
Suliman A. Gargoum ◽  
Karim El-Basyouny ◽  
Amr Shalkamy ◽  
Maged Gouda
Keyword(s):  
Road Construction ◽  
Surface Model ◽  
Lidar Data ◽  
Gps Data ◽  
Vertical Profiles ◽  
Cloud Data ◽  
The Road ◽  
Road Profile ◽  
Using Data ◽  
Roadway Design

Producing as-built drawings is an important task in any road construction project. In fact, in an ideal situation, these drawings must be updated whenever major maintenance work takes place. Unfortunately, constantly updating those drawings is not always feasible due to the amount of manual work associated with the data collection in traditional surveying practice. The increase in computing power and the advancement in technology has led many transportation agencies to consider utilizing remote sensing techniques to extract roadway design features and prepare as-builts of roads. In this note, a procedure to generate as-built drawings of vertical profiles on highways using light detection and ranging (LiDAR) point cloud data are proposed. The procedure is a multistep procedure where the road centerline of each segment is first defined, after that a best fit alignment of points along the road’s centerline is generated. A digital surface model (DSM) of the LiDAR highway is created and the centerline is relayed onto the DSM before generating the road profile. The proposed method is tested using LiDAR data collected on two highways in the province of Alberta, Canada. The profiles extracted using the proposed method are compared against vertical profiles that were generated for the same segments using data collected in GPS surveys and as-built drawings developed in manual surveys. The results show the feasibility of accurately extracting road profiles from LiDAR data. The average difference in grades estimated using the proposed method and the GPS data ranged from 0.023% to 0.061%. In fact, the proposed method was able to capture details in the road profile that were not detected using GPS data, demonstrating the value of using LiDAR for road profile extraction.

Digital Road Profile Using Kinematic GPS

2009 ◽  
Vol 44 (3) ◽  
pp. 95-101 ◽  
Author(s):  
Ashraf Farah
Keyword(s):  
Road Construction ◽  
Longitudinal Direction ◽  
Mean Value ◽  
Kinematic Gps ◽  
The Road ◽  
Geometrical Characteristics ◽  
Assessment Study ◽  
Road Profile ◽  
Gps System ◽  
Two Stages

Digital Road Profile Using Kinematic GPS A Digital Road Profile (DRP) is a digital representation of road surface topography or terrain in the longitudinal direction. The need for accurate DRP is vital in two stages; before the road construction starts and after the road construction finished where the verification of its geometrical characteristics is essential for engineering safety purposes. Classical surveying techniques are traditionally used for the DRP generation with limitation of high-cost and time-waste. Kinematic DGPS or Real Time Kinematic DGPS positioning can provide accurate enough results for such application. This paper presents an assessment study of using kinematic GPS technique for DRP generation comparing with classical survey in south Egypt. The results shows that, vehicle-GPS system used in combination with post processing kinematic DGPS gave satisfactory accuracy for nearly all points for a distance of nearly 2 km. with max. and min. difference not more than 7.7 cm, a mean value of 0.10 cm and a Root Mean Square RMS value of 4.11 cm.

scholarly journals ROADWAY ROUGHNESS RESEARCH AND CAUSES DETERIORATION ANALYSIS

2017 ◽  
Vol 1 (48) ◽  
pp. 251-257
Author(s):  
D. O. Pavlyuk ◽  
V. P. Tereshchuk ◽  
V. S. Chapovskyi
Keyword(s):  
Detailed Analysis ◽  
Transverse Crack ◽  
Road Construction ◽  
Transverse Cracks ◽  
Research Results ◽  
The Road ◽  
Road Profile ◽  
On The Road ◽  
The City

The article deals with modern directions of domestic and foreign smoothness research coverage on the roads.  The problem of causes changes establishing in smoothness coverage related to the irregularities in the procedure of road construction layers is highlighted. The research results of the trafficway smoothness and its causes deterioration analysis, performed by operation of roads and airfields laboratory at National Transport University on research road area H-18 around the city Buchach is shown.  By the research results the road profile is drawn and the detailed analysis of road topping smoothness changes during road operation is done. Samples at the specific points on the road topping is taken: in one place it is a transverse crack, in another – without noticeable defects. It is established that road profile hollows and transverse cracks caused by black layers uneven thickness along the road.

scholarly journals Point Cloud Data Retrieval from 3D Geospatial Database for Automated Road Median Extraction

2018 ◽  
Author(s):  
Pankaj Kumar ◽  
Paul Lewis ◽  
Conor P. McElhinney
Keyword(s):  
Data Processing ◽  
Point Cloud ◽  
Laser Scanning ◽  
Data Retrieval ◽  
Lidar Data ◽  
Point Cloud Data ◽  
Cloud Data ◽  
The Road ◽  
Efficient Storage ◽  
Geospatial Database

Laser scanning systems make use of Light Detection and Ranging (LiDAR) technology to acquire accurately georeferenced sets of dense 3D point cloud data. The information acquired using these systems produces better knowledge about the terrain objects which are inherently 3D in nature. The LiDAR data acquired from mobile, airborne or terrestrial platforms provides several benefit over conventional sources of data acquisition in terms of accuracy, resolution and attributes. However, the large volume and scale of LiDAR data have inhibited the development of automated feature extraction algorithms due to the extensive computational cost involved in it. Moreover, the heterogeneously distributed point cloud, which represents objects with varying size, point density, holes and complicated structures pose a great challenge for data processing. Currently, geospatial database systems do not provide a robust solution for efficient storage and accessibility of raw data in a way that data processing could be applied based on optimal spatial extent. In this paper, we present Global LiDAR and Imagery Mobile Processing Spatial Environment (GLIMPSE) system that provides a framework for storage, management and integration of 3D LiDAR data acquired from multiple platforms. The system facilitates an efficient accessibility to the raw dataset, which is hierarchically represented in a geographically meaningful way. We utilise the GLIMPSE system to automatically extract road median from Airborne Laser Scanning (ALS) point cloud. In the first part of this paper, we detail an approach to efficiently retrieve the point cloud data from the GLIMPSE system for a particular geographic area based on user requirements. In the second part, we present an algorithm to automatically extract road median from the retrieved LiDAR data. The developed road median extraction algorithm utilises the LiDAR elevation and intensity attributes to distinguish the median from the road surface. We successfully tested our algorithms on two road sections consisting of distinct road median types based on concrete and grass-hedge barriers. The use of GLIMPSE improved the efficiency of the road median extraction in terms of fast accessibility to ALS point cloud data for the required road sections. The developed system and its associated algorithms provide a comprehensive solution to the user's requirement for an efficient storage, integration, retrieval and processing of large volumes of LiDAR point cloud data. These findings and knowledge contribute to a more rapid, cost-effective and comprehensive approach to surveying road networks.

scholarly journals True Orthoimage Generation Using Airborne LiDAR Data with Generative Adversarial Network-Based Deep Learning Model

2021 ◽  
Vol 2021 ◽  
pp. 1-25
Author(s):  
Young Ha Shin ◽  
Dong-Cheon Lee
Keyword(s):  
Deep Learning ◽  
Laser Scanner ◽  
Airborne Lidar ◽  
Surface Model ◽  
Lidar Data ◽  
Generative Adversarial Network ◽  
Cloud Data ◽  
Adversarial Network ◽  
Benchmark Datasets

Orthoimage, which is geometrically equivalent to a map, is one of the important geospatial products. Displacement and occlusion in optical images are caused by perspective projection, camera tilt, and object relief. A digital surface model (DSM) is essential data for generating true orthoimages to correct displacement and to recover occlusion areas. Light detection and ranging (LiDAR) data collected from an airborne laser scanner (ALS) system is a major source of DSM. The traditional methods require sophisticated procedures to produce a true orthoimage. Most methods utilize 3D coordinates of the DSM and multiview images with overlapping areas for orthorectifying displacement and detecting and recovering occlusion areas. LiDAR point cloud data provides not only 3D coordinates but also intensity information reflected from object surfaces in the georeferenced orthoprojected space. This paper proposes true orthoimage generation based on a generative adversarial network (GAN) deep learning (DL) with the Pix2Pix model using intensity and DSM of the LiDAR data. The major advantage of using LiDAR data is that the data is occlusion-free true orthoimage in terms of projection geometry except in the case of low image quality. Intensive experiments were performed using the benchmark datasets provided by the International Society for Photogrammetry and Remote Sensing (ISPRS). The results demonstrate that the proposed approach could have the capability of efficiently generating true orthoimages directly from LiDAR data. However, it is crucial to find appropriate preprocessing to improve the quality of the intensity of the LiDAR data to produce a higher quality of the true orthoimages.

The Political Economy of Power: Approaches to the Analysis of Relationships between the State and Business in Russia

2011 ◽  
pp. 19-33
Author(s):  
A. Oleinik
Keyword(s):  
Oil And Gas ◽  
Road Construction ◽  
Oil And Gas Industry ◽  
Retail Trade ◽  
Business Community ◽  
The Political ◽  
Economic Power ◽  
Gas Industry ◽  
The Road ◽  
Ruling Elites

The article deals with the issues of political and economic power as well as their constellation on the market. The theory of public choice and the theory of public contract are confronted with an approach centered on the power triad. If structured in the power triad, interactions among states representatives, businesses with structural advantages and businesses without structural advantages allow capturing administrative rents. The political power of the ruling elites coexists with economic power of certain members of the business community. The situation in the oil and gas industry, the retail trade and the road construction and operation industry in Russia illustrates key moments in the proposed analysis.

ANALISIS PENANGGULANGAN KELONGSORAN TANAH PADA RUAS JALAN GUNUNG TUGEL PATIKRAJA BANYUMAS

2017 ◽  
Vol 14 (1) ◽  
pp. 53
Author(s):  
Arwan Apriyono ◽  
Sumiyanto Sumiyanto ◽  
Nanang Gunawan Wariyatno
Keyword(s):  
Limit Equilibrium ◽  
Retaining Wall ◽  
Limit Equilibrium Method ◽  
Pile Foundations ◽  
Soil Parameters ◽  
The Road ◽  
Realistic Option ◽  
Stable Conditions ◽  
Using Data ◽  
Wall Slope

Gunung Tugel is an area that located Patikraja Region, Southern Banyumas. Thetopography of the area is mostly mountainous with a slope that varies from flat to steep. Thiscondition makes to many areas of this region potentially landslide. In 2015, a landslideoccurred in Jalan Gunung Tugel. The Landslide occurred along 70 meters on the half of theroad and causing traffic Patikraja-Purwokerto disturbed. To repair the damage of the road andavoid further landslides, necessary to analyze slope stability. This study is to analyze landslidereinforcement that occurred at Gunung Tugel and divides into 3 step. The first step is fieldinvestigation to determine the condition of the location and dimensions of landslides. Thesecond step is to know the soil parameters and analyzes data were obtained from the field. Andthe final step is analyzed of the landslide reinforcement by using data obtained from thepreceding step. In this research, will be applied three variations of reinforcement i.e. retainingwall, pile foundation and combine both of pile foundations and retaining wall. Slope stabilityanalysis was conducted using limit equilibrium method. Based on the analysis conducted onthe three variations reinforcement, combine both of pile foundations and retaining wall morerecommended. Application of and combine both of pile foundations and retaining wall is themost realistic option in consideration of ease of implementation at the field. From thecalculations have been done, in order to achieve stable conditions need retaining wall withdimensions of 2 meters high with 2,5 meters of width. DPT is supported by two piles of eachcross-section with 0.3 meters of diameter along 10 meters with 1-meter in space. Abstrak: Gunung Tugel adalah salah satu daerah yang terletak di Kecamatan PatikrajaKabupaten Banyumas bagian selatan. Kondisi topografi daerah tersebut sebagian besar berupapegunungan dengan kemiringan yang bervariasi dari landai sampai curam. Hal inimenyebabkan banyak daerah di wilayah Gunung Tugel yang berpotensi terjadi bencana tanahlongsor. Pada tahun 2015, peristiwa longsor kembali terjadi di ruas Jalan Gunung Tugel.Kelongsoran yang terjadi sepanjang 70 meter pada separuh badan jalan tersebut menyebabkanarus lalu lintas patikraja-purwokerto menjadi terganggu. Untuk memperbaiki kerusakan jalandan mencegah kelongsoran kembali, diperlukan analisis perkuatan tanah terhadap lerengtersebut. Studi analisis penanggulangan kelongsoran jalan yang terjadi di Gunung Tugel inidilakukan dengan tiga tahapan. Tahapan pertama adalah investigasi lapangan untukmengetahui kondisi lokasi dan dimensi longsor serta mengambil sampel tanah di lapangan.Tahap kedua adalah melakukan pengujian parameter tanah dan analisis data yang diperolehdari lapangan. Tahapan yang terakhir adalah analisis penanggulangan longsor denganmenggunakan data yang diperoleh dari tahapan sebelumnya. Pada penelitan ini, akanditerapkan tiga variasi perkuatan lereng yaitu dinding penahan tanah (DPT), turap dan DPTyang dikombinasikan dengan pondasi tiang. Analisis stabilitas lereng dilakukan dengan metodekeseimbangan batas. Berdasarkan hasil analisis yang dilakukan terhadap ketiga variasiperkuatan, DPT dengan kombinasi tiang pancang lebih direkomendasikan. Penerapan DPTyang dikombinasikan dengan minipile merupakan pilihan yang paling realistis denganpertimbangan tingkat kemudahan pelaksanaan di lapangan. Dari perhitungan yang telahdilakukan, untuk mencapai kondisi stabil diperlukan DPT dengan dimensi tinggi 2 meterdengan lebar bawah 2,5 meter. DPT tersebut ditopang oleh dua tiang tiap penampangmelintang dengan diameter 0,3 meter sepanjang 10 meter dengan jarak antar tiang 1 meter.kata kunci: tanah longsor, perkuatan tanah, metode keseimbangan batas

ABOUT THE METHOD OF THE OPTIMISATION OF STUDENTS’LEARNING ENGLISH TERMINOLOGY

2020 ◽  
pp. 73-82
Author(s):  
Л.Н. Крячко
Keyword(s):  
Foreign Language ◽  
Teaching Practice ◽  
Road Construction ◽  
National Language ◽  
The Road ◽  
Language Classes ◽  
Technical University ◽  
Training Exercises ◽  
Animal World

Постановка задачи. Изучение предмета «Иностранный язык» в техническом университете предполагает усвоение обучающимися терминологической лексики в соответствии с выбранной специальностью. Опыт преподавания показывает, что студенты испытывают трудности, связанные с запоминанием терминологических единиц и употреблением их в речи. Использование на занятиях по иностранному языку приема обучения терминологической лексике посредством опоры на внутреннюю форму данных лексических единиц позволяет оптимизировать процесс усвоения обучающимися специальных терминов. Результаты. Проведенное исследование дает основание утверждать, что анализ внутренней формы образованных семантическим способом англоязычных терминов специальности «Автомобильные дороги» позволяет выявить деривационно-ассоциативную связь терминологических единиц с лексикой общенационального языка, послужившей основой для вторичной номинации. Данные лексические единицы в большинстве случаев представляют собой хорошо знакомые студентам слова, обозначающие части тела человека и объекты, находящиеся в его близком окружении : одежду, посуду, инструменты, явления природы, представителей животного мира и т.д. Выводы. Ознакомление студентов дорожно-строительной специальности с внутренней формой изучаемых англоязычных терминов, выявление ассоциативных связей терминологических единиц со знакомыми студентам и широкоупотребительными словами общенационального языка, а также выполнение в аудитории специально разработанных тренировочных упражнений помогают снять трудности усвоения обучающимися терминологической лексики и облегчают ее запоминание. Statement of the problem. The study of the “Foreign Language” subject at a technical university involves students’ learning the terminology in accordance with the chosen specialty. The teaching practice shows that students experience the difficulties associated with memorising terminological units and using them in the speech. Applying the method of teaching the terminology based on the internal form of these lexical units at foreign language classes makes it possible to optimise the process of learning special terms by students. Results. The research that has been carried out gives reason to argue that the analysis of the internal form of the English “Automobile roads” specialty terms created in the semantic way makes it possible to reveal the derivational and associative relations of the terminological units with the national language words which served as the basis for the secondary nomination. In most cases, these lexical units are the words that are well known by the students and indicate the parts of man’s body and the objects that are present in man’s immediate environment: clothing, dishes, tools, phenomena of the nature, representatives of the animal world, etc. Conclusion. Introducing the internal form of the studied English terms to the road construction specialty students, identifying the associative relations of the terminological units with the well known to the students and widely used words of the national language, fulfilling the specially developed training exercises in the classroom help the students to overcome the difficulties of learning the terminology and to facilitate its memorization.

Features of the Harvesting and Logging Equipment Market in Russia

2020 ◽  
pp. 132-147
Author(s):  
M.A. Piskunov ◽  
Keyword(s):  
Information Technologies ◽  
Import Substitution ◽  
Road Construction ◽  
Forest Sector ◽  
Specific Information ◽  
Service Network ◽  
Russian Market ◽  
The Road ◽  
Foreign Companies ◽  
Transnational Companies

Russian forest sector forms an attractive market for harvesting and logging equipment, however the position of Russian manufacturers is extremely weak. A brief overview of the current state of the market is presented with reference to the open sources. Its features are mentioned as compared to the road construction and agricultural machinery sectors. Three transnational companies dominate the Russian market of harvesting and logging equipment: John Deere, Ponsse and Komatsu. Most of the purchased equipment falls on machines for cut-tolength technology, such as harvester and forwarder. The market volume of new machines is estimated at 330–420 forwarders, 165–300 harvesters, about 30–40 feller bunchers and the same number of skidders. There were two waves in the consolidation of the position of foreign companies in Russia. The first was connected with the delivery of equipment and the development of foreign brands in Russia against the background of still high-profile positions of Russian manufacturers in the market. The second is the takeover of enterprises having a service network and reputation by diversified transnational corporations. The main strategies of the leading companies in the current situation are the export of equipment to Russia and the development of a service network. Companies do not turn to another level associated with the opening of production sites or joint ventures for the production of harvesting and logging machines. The Russian market is characterized by the absence of a strong Russian manufacturer of harvesting and logging machines, which is ready to significantly influence or actively participate in the processes of import substitution. The position of such a manufacturer is gradually occupied by the Belarusian Amkodor Holding. The purchase of new harvesting and logging machines can afford major timber companies. The main production sites of harvesting and logging machines are located in Finland, Sweden, USA, and Canada. In order to support forestry machine engineering, in addition to economic measures of stimulation approved in other sectors, it is proposed: to organize the work of scientific forest engineering centers on the base of public-private partnership with the financial support from the major vertically-integrated timber corporate groups; to stimulate the development of Russian sector-specific information technologies for harvesting and logging; to initiate the partnership with companies from the People’s Republic of China to launch the design and production of new-generation harvesting and logging machines.

scholarly journals Using Machine Learning Methods to Identify Particle Types from Doppler Lidar Measurements in Iceland

2021 ◽  
Vol 13 (13) ◽  
pp. 2433
Author(s):  
Shu Yang ◽  
Fengchao Peng ◽  
Sibylle von Löwis ◽  
Guðrún Nína Petersen ◽  
David Christian Finger
Keyword(s):  
Machine Learning ◽  
Weather Conditions ◽  
Dust Storms ◽  
Machine Learning Algorithms ◽  
Lidar Data ◽  
Data Sets ◽  
Doppler Lidar ◽  
Lidar Measurements ◽  
Using Data ◽  
Filter Noise

Doppler lidars are used worldwide for wind monitoring and recently also for the detection of aerosols. Automatic algorithms that classify the lidar signals retrieved from lidar measurements are very useful for the users. In this study, we explore the value of machine learning to classify backscattered signals from Doppler lidars using data from Iceland. We combined supervised and unsupervised machine learning algorithms with conventional lidar data processing methods and trained two models to filter noise signals and classify Doppler lidar observations into different classes, including clouds, aerosols and rain. The results reveal a high accuracy for noise identification and aerosols and clouds classification. However, precipitation detection is underestimated. The method was tested on data sets from two instruments during different weather conditions, including three dust storms during the summer of 2019. Our results reveal that this method can provide an efficient, accurate and real-time classification of lidar measurements. Accordingly, we conclude that machine learning can open new opportunities for lidar data end-users, such as aviation safety operators, to monitor dust in the vicinity of airports.

scholarly journals Drone-Based Remote Sensing for Research on Wind Erosion in Drylands: Possible Applications

2021 ◽  
Vol 13 (2) ◽  
pp. 283
Author(s):  
Junzhe Zhang ◽  
Wei Guo ◽  
Bo Zhou ◽  
Gregory S. Okin
Keyword(s):  
Remote Sensing ◽  
Wind Erosion ◽  
Field Measurements ◽  
Spatially Explicit ◽  
Surface Model ◽  
High Resolution Imagery ◽  
Soil Elevation ◽  
3D Photogrammetry ◽  
Using Data ◽  
Sample Set

With rapid innovations in drone, camera, and 3D photogrammetry, drone-based remote sensing can accurately and efficiently provide ultra-high resolution imagery and digital surface model (DSM) at a landscape scale. Several studies have been conducted using drone-based remote sensing to quantitatively assess the impacts of wind erosion on the vegetation communities and landforms in drylands. In this study, first, five difficulties in conducting wind erosion research through data collection from fieldwork are summarized: insufficient samples, spatial displacement with auxiliary datasets, missing volumetric information, a unidirectional view, and spatially inexplicit input. Then, five possible applications—to provide a reliable and valid sample set, to mitigate the spatial offset, to monitor soil elevation change, to evaluate the directional property of land cover, and to make spatially explicit input for ecological models—of drone-based remote sensing products are suggested. To sum up, drone-based remote sensing has become a useful method to research wind erosion in drylands, and can solve the issues caused by using data collected from fieldwork. For wind erosion research in drylands, we suggest that a drone-based remote sensing product should be used as a complement to field measurements.

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