bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of Patient Satisfaction on the Quality of Physiotherapy Services in the Pandemic Era at the SHC
Authors: Ngguna Rifaidwianto , Erlina Puspitaloka Mahadewi  , Gisely Vionalita  , Handayani Rini
Published: May 2022

The present study about Satisfaction is the perception of a product or service that has metexpectations. The customer satisfaction is the result of the accumulation of consumers or customers in using products or services. The quality of health services is the degree to which the needs of the community or individuals are meet for healthcare in accordance with good professional standardswith the use of resources fairly, efficiently, effectively within the limited capacity of the government and the community, and is carried out safely and satisfies customers in accordance with accepted good norms and ethics. Based on observations made by distributing customer feedback questionnaires at the Sasana Husada Clinic (SHC), Jakarta Indonesia patient satisfaction in outpatient physiotherapy services from January to March 2021. Result for patient satisfactionobtained 76%, of which there were about 24% who were dissatisfied with the physiotherapy servicesprovided at the SHC Jakarta Indonesia. The purpose of this study was to determine the analysis of patientsatisfaction with the quality of physiotherapy services in the covid-19 pandemic era at the SHC. Thestudy used a descriptive observational method with a cross sectional research design. The sample in this study was 62 people with sampling technique using simple random sampling. This research was conducted by filling out a questionnaire by the patient. Data analysis was performed by univariate test analysis. The results of the study indicate that patient satisfaction inside pandemic and based on thequality dimension of reliability 79.61%, patient satisfaction based on the assurance dimension 80.06%, patient satisfaction based on the tangibility quality dimension 81.67%, patient satisfaction based on the empathy quality dimension 78.12%, satisfaction patients based on responsiveness 77.80% and general patient satisfaction 78.06%.
The Development of Health Insurance and Services in Indonesia
Authors: Maylia Ardini Vita , Puspitaloka Mahadewi Erlina
Published: May 2022

The study focus on the development and review of health insurance in Indonesia that is relatively new for most Indonesians because the term health insurance is not sufficient in the general vocabulary. Social health insurance is insurance that must be followed by all or part of the population (an example employees), to involved and contributions are not a nominal value but a percentage of the salary to be paid, and insurance benefits. Commercial health insurance is insurance sold by other insurance companies or institutions. The development of health insurance in Indonesia is very slow compared to the development of health insurance in several neighboring Asean countries (Associaton of South East Asian Nations). Careful research on the slow development of health insurance in Indonesia is still lacking. However, in theory, several importantfactors can be put forward as factors that influence the slow growth of health insurance in Indonesia. In this case, there are health services which, in the process of health services, there will be variations in the implementation of activities from time to time which will produce varying results. One of the efforts to reduce process variation is standardization. The normalization process includes the elaboration, implementation, follow-up, control, evaluation and revision of norms (Indonesia Government Regulations or PPnumber:102/2000). The development of public health services in Indonesia has succeeded in improving health services more evenly. Advances in science and technology have resulted in more and more educated and informed community groups so that they can choose and demand quality health services especially with health insurances coverage
US-RUSSIAN RELATIONS WITHIN THE FRAMEWORK OF FORMING A NEW WORLD ORDER
Authors:   Kazakh Ablai Khan University of International Relations and World Languages, Yerbossynov T. , Absattarov G.R. ,   Kazakh Ablai Khan University of International Relations and World Languages
Published: May 2022

Today, dramatic motives prevail in assessments of the current international political situation. The picture is often painted truly apocalyptic: the world is entering a new era, the main features of which are the dominance of offensive nationalism, the rejection of formal and informal imperatives of behavior in the international arena, the erosion of constraints, dangerous balancing, the increasing uncertainty, the general rejection of the game by the rules and as a result - increased risks and unpredictability.
CITY FOR CHILDREN: CASE-STUDY OF FRIENDSHIP OF THE ALMATY CITY
Authors:   Narxoz University, Beimisheva A.S. , Andirzhanova G.A. ,   Narxoz University, Imanbekova B.I. ,   Narxoz University
Published: May 2022

The study is devoted to the study of the problem of friendliness and comfort of the urban environment for children and in the interests of children. The purpose of the research was to study the environment for comfortable living of children in the largest city in the country. The peculiarity of the study is significant theoretical and practical orientation, due to the many cases selected in different parts of the city.
HUMAN RIGHTS MUST BE THE BASIC BASIS OF KAZAKHSTAN'S LEGAL POLICY
Authors:   Caspian Public University, Zhursimbaev S.K. , Kemali E.C. ,   PhD in law, Enforcement Academy under the Prosecutor General’s Office of the Republic of Kazakhstan, Kosshy, Republik street 16, Akmola region
Published: May 2022

The present article analyses the problem of lawful politics by the state. The author reviews the genesis and interaction between political and legal norms. The article also rises a problem of political and legal consciousness. The core part of the research is dedicated to the interaction and interconnection of the state politics with the law. The author comes to the conclusion on the necessity of execution of lawful politics in the state as a guarantee of justice and intercession, the politics based exclusively on law.
Aerosol size distribution changes in FIREX-AQ biomass burning plumes: the impact of plume concentration on coagulation and OA condensation/evaporation
Authors: June Nicole A. , Hodshire Anna L. , Wiggins Elizabeth B. , Winstead Edward L. , Robinson Claire E. , Thornhill K. Lee , Sanchez Kevin J. , Moore Richard H. , Pagonis Demetrios , Guo Hongyu , Campuzano-Jost Pedro , Jimenez Jose L. , Coggon Matthew M. , Dean-Day Jonathan M. , Bui T. Paul , Peischl Jeff , Yokelson Robert J. , Alvarado Matthew J. , Kreidenweis Sonia M. , Jathar Shantanu H. , Pierce Jeffrey R.
Published: May 2022

Abstract. The evolution of organic aerosol (OA) and aerosol size distributions within smoke plumes are uncertain due to the variability in rates of coagulation and OA condensation/evaporation between different smoke plumes and at different locations within a single plume. We use aircraft data from the FIREX-AQ campaign to evaluate differences in evolving aerosol size distributions, OA, and oxygen to carbon ratios (O:C) between and within smoke plumes during the first several hours of aging as a function of smoke concentration. The observations show that the median particle diameter increases faster in smoke of a higher initial OA concentration (>1000 μg m-3) with diameter growth of over 100 nm in 8 hours–despite generally having a net decrease in OA enhancement ratios–than smoke of a lower initial OA concentration (<100 μg m-3), which had net increases in OA. Observations of OA and O:C suggest that evaporation and/or secondary OA formation was greater in less concentrated smoke prior to the first measurement (5–57 minutes after emission). We simulate the size changes due to coagulation and dilution and adjust for OA condensation/evaporation based on the observed changes in OA. We found that coagulation explains the majority of the diameter growth with OA evaporation/condensation having a relatively minor impact. We found that mixing between the core and edges of the plume generally occurred on timescales of hours, slow enough to maintain differences in aging between core-edge, but too fast to ignore the role of mixing for most of our cases.
Water uptake and the gas-particle partitioning of nitrate aerosols
Authors: Do Hoang Duong , Lim Yong Bin , Kim Yong Pyo
Published: May 2022

Abstract. Nitrate uptake into particles is an important feature of thermodynamic equilibriums responsible for the high-concentration particle formation in East Asia. However, key processes including the gas-particle partitioning of HNO3-NO3- and the deliquescence of particles, are not scrutinized in thermodynamic model simulations used in field studies. Using a humidified tandem differential mobility analyzer (HTDMA), we investigated water uptake and gas-particle partitioning of nitrates for inorganic and inorganic-organic aerosols as we simulated thermodynamic models (ISORROPIA-II and E-AIM). For the best-fit to HTDMA measurements, we revised thermodynamic model simulations and conducted linear regressions. Results demonstrated that ammonium nitrate aerosols maintained deliquescence in the entire range of 10–90 % relative humidity (RH) and in the range of 30–70 % RH the aerosol liquid water content (ALWC) and nitrates in ammonium-sulfate-nitrate aerosols simultaneously evaporated. Glyoxal exhibited hygroscopicity and a synergetic effect on ALWC formation with ammonium sulfates. In ammonium-sulfate-nitrate-glyoxal aerosols, more ALWC and nitrates formation above 50 % RH is likely due to the synergetic effect among ammonium, sulfates and nitrates. Considering that 30–80 % RH is haze conditions in East Asia, we propose that pronounced nitrate formation in particles beyond the description of current thermodynamic model simulations includes deliquescent nature of ammonium nitrate aerosols that undergo hysteresis with an unclear efflorescence RH point due to incomplete equilibriums, the evaporation of ALWC, nitrates and ammoniums in sulfate-rich aerosols, and the synergetic effect between organic and inorganic components on ALWC formation at high RH.
Sensitivity of Heinrich-type ice-sheet surge characteristics to boundary forcing perturbations
Authors: Schannwell Clemens , Mikolajewicz Uwe , Ziemen Florian , Kapsch Marie-Luise
Published: May 2022

Abstract. Heinrich-type ice-sheet surges are one of the dominant signals of glacial climate variability. They are characterised as abrupt, quasi-periodic episodes of ice-sheet instabilities during which large amounts of ice are discharged from ice sheets into the ocean. The occurence of ice-sheet surges strongly influences the global climate evolution by altering the ocean circulation through the addition of freshwater and the atmospheric circulation through changes in ice-sheet height. The mechanisms controlling the timing and occurence of Heinrich-type ice-sheet surges remain poorly constrained to this day. Here, we use a coupled ice sheet-solid earth model to identify and quantify the importance of boundary forcing for the surge cycle length of Heinrich-type ice-sheet surges for two prominent ice streams of the Laurentide ice sheet – the land-terminating Mackenzie ice stream and the marine-terminating Hudson ice stream. We show that surface mass balance perturbations have the largest effect on the surge cycle length. Pertubations to the ice surface temperature and geothermal heatflux also influence the surge cycle length, but to a lesser degree. Ocean and sea-level forcing as well as different frequencies of the same forcing have a negligible effect on the surge cycle length. The simulations also highlight that only a certain parameter space exists under which ice-sheet oscillations can be maintained. Transitioning from an oscillatory state to a persistent ice streaming state, can result in an ice volume loss of up to 26 % for the respective ice stream drainage basin under otherwise constant climate conditions. We show that Mackenzie ice stream is susceptible to undergoing such a transition in response to all tested positive climate perturbations. This underlines the potential of the Mackenzie region to have contributed to prominent abrupt climate change events of the last deglaciation.
High-resolution vertical biogeochemical profiles in the hyporheic zone reveal insights into microbial methane cycling
Authors: Michaelis Tamara , Wunderlich Anja , Coskun Ömer K. , Orsi William , Baumann Thomas , Einsiedl Florian
Published: May 2022

Abstract. Facing the challenges of climate change, policy making relies on sound greenhouse gas (GHG) budgets. Rivers and streams emit large quantities of the potent GHG methane (CH4), but their global impact on atmospheric CH4 concentrations is highly uncertain. In-situ data from the hyporheic zone (HZ), where most CH4 is produced and some of it can be oxidized to CO2, are lacking for an accurate description of CH4 production and consumption in streams. To address this, we recorded high-resolution depth-resolved geochemical profiles at five different locations in the stream bed of river Moosach, Southern Germany. Specifically, we measured pore-water concentrations and stable carbon isotopes (δ13C) of dissolved CH4 as well as relevant electron acceptors for oxidation with a 1 cm vertical depth-resolution. Findings were interpreted with the help of a numerical model, and 16S rRNA gene analyses added information on the microbial community at one of the locations. Our data confirms with pore-water CH4 concentrations of up to 1000 μmol L-1 that large quantities of CH4 are produced in the HZ. Stable isotope measurements of CH4 suggest that hydrogenotrophic methanogenesis represents a dominant pathway for CH4 production in the HZ of river Moosach, while a relatively high abundance of a novel group of methanogenic archaea, the Methanomethyliales (Phylum Verstraetearchaeota), indicate that CH4 production through H2 dependent methylotrophic methanogenesis might also be an important CH4 source. Combined isotopic and modeling results clearly implied CH4 oxidation processes at one of the sampled locations, but due to the steep chemical gradients and the close proximity of the oxygen and nitrate reduction zones no single electron acceptor for this process could be identified. Nevertheless, the numerical modeling results showed not only a potential for aerobic CH4 oxidation, but also for anaerobic oxidation of CH4 coupled to denitrification. In addition, the nitrate-methane transition zone was characterized by an increased relative abundance of microbial groups (Crenothrix, NC10) known to mediate nitrate and nitrite dependent methane oxidation in the hyporheic zone.
Hydrogeological controls on the spatio-temporal variability of surge-induced hydraulic gradients along coastlines: implications for beach surface stability
Authors: Paldor Anner , Stark Nina , Florence Matthew , Raubenheimer Britt , Elgar Steve , Housego Rachel , Frederiks Ryan S. , Michael Holly A.
Published: May 2022

Abstract. Ocean surges pose a global threat for coastal stability. These hazardous events alter flow conditions and pore pressures in flooded beach areas during both inundation and subsequent retreat stages, which can mobilize beach material, potentially enhancing erosion significantly. In this study, the evolution of surge-induced pore-pressure gradients is studied through numerical hydrologic simulations of storm surges. The spatiotemporal variability of critically high gradients is analyzed in 3D. The analysis is based on a threshold value obtained for momentary liquefaction of beach materials under groundwater seepage. Simulations of surge events show that during the run-up stage, head gradients can rise to the calculated critical level landward of the advancing inundation line. During the receding stage, critical gradients were simulated seaward of the retreating inundation line. These gradients reach maximum magnitudes just as sea level returns to pre-surge level, and are most accentuated beneath the still-water shoreline, where the model surface changes slope. The gradients vary along the shore owing to variable beach morphology, with the largest gradients seaward of intermediate-scale (1–3 m elevation) topographic elements (dunes) in the flood zone. These findings suggest that the common practices in monitoring and mitigating surge-induced failures and erosion, which typically focus on the flattest areas of beaches, might need to be revised.
RADAR/INS INTEGRATION FOR POSE ESTIMATION IN GNSS-DENIED ENVIRONMENTS
Authors: Elkholy M. , Elsheikh M. , El-Sheimy N.
Published: May 2022

Abstract. This paper proposes a novel algorithm to use Radar in ego-motion estimation for autonomous navigation applications. This method is based on the analysis of Radar data to remove noise, ghost points, and outliers and keep the accurate features. From the detected features and the knowledge of Radar data rate and the vehicle's average speed, the change in range and azimuth between any two points can be constrained to find the corresponding points. With the help of the corresponding points, the vehicle's ego-motion can be estimated. Then, Radar is integrated with an Inertial Navigation System (INS) and odometer through an extended Kalman filter (EKF) to smooth the Radar solution and aid INS to overcome its large drifts in GNSS denied environments. Two real data were collected from frequency modulated continuous wave (FMCW) Radar sensors and Inertial Measurement Unit (IMU) in suburban areas near the University of Calgary, Canada. The proposed algorithm was tested by introducing simulated GNSS signal outages with different durations. The Root Mean Square Error (RMSE) for the horizontal position was improved by an average of 30.44% and 4.76% if it was compared with RMSE from odometer/INS solution with a percentage error less than 1% of the traveled distance which was 1.59 km and 2 km for the two datasets, respectively.
SLAM AND INS BASED POSITIONAL ACCURACY ASSESSMENT OF NATURAL AND ARTIFICIAL OBJECTS UNDER THE FOREST CANOPY
Authors: Chudá J. , Kadlečík R. , Mokroš M. , Mikita T. , Tuček J. , Chudý F.
Published: May 2022

Abstract. The positional accuracy derived from the outputs of carried integrated devices was evaluated in this study. For data collection, the inertial navigation system (INS) SPAN NovAtel and a handheld mobile laser scanner GeoSLAM ZEB Horizon which uses simultaneous localization and mapping technology (SLAM) were utilized for data collection. The accuracy was assessed on the set of reference objects located under the forest canopy, which were measured via a traditional field survey (the methods of geodesy). In the results of this study the high potential of the devices and the application of data collection methods into forestry practice were pointed out. In our research, when the horizontal position of artificial entities was evaluated the average RMSE of 0.26 m, and the average positional RMSE of the derived natural objects (trees) was 0.09 m, both extracted from SLAM. The horizontal positional accuracy of trajectories with RMSE of 9.93 m (INS) and 0.40 m (SLAM) were accomplished.
A PRIMARY TEST RESULTS OF A HANDHELD MOBILE LASER SCANNER IN EXTRACTION OF TREE PARAMETERS
Authors: Eker R. , Ucar Z. , Aydın A.
Published: May 2022

Abstract. Sustainable forest planning and management require accurate and precise information about the estimation of forest resources. In particular, two tree parameters are very important among the others: diameter-at-breast height (DBH) and height that are used to estimate the volume and biomass of the tree. With the development of Remote Sensing (RS), information about the tree parameters can be acquired in more accurately and precisely with laser scanning technology. In this study, a Handheld Mobile Laser Scanner (HMLS), called TORCH, was tested for extracting tree parameters with 3D Forest software. The TORCH uses the SLAM (Simultaneous Localization and Mapping) algorithm to locate the scanner in an unknown environment and register the obtained 3D point clouds. Estimated DBH and height parameters from HMLS data extracted using 3D Forest software were compared with the field measurements (i.e., reference data). The preliminary results of the study showed that estimated DBH from HMLS data were relatively higher than ground measurement, while estimated height from point clouds data was slightly lower than the reference data. The continuous improvement in mobile laser scanners will improve the success of the devices while acquiring 3D structural information of tree parameters and reducing the cost and time spent in forest inventory.
AN INITIAL ALIGNMENT METHOD OF INERTIAL NAVIGATION SYSTEM FOR THE STATIC STATE
Authors: Liu H.-Y. , Tsai S. , Tsai M.-L. , Chiang K.-W.
Published: May 2022

Abstract. The navigation means the process of determining the position, velocity, and orientation of the moving object such as the land vehicle, aerial vehicle, and even autonomous vehicle. Nowadays, Global Navigation Satellite System (GNSS) is most used for positioning. Nevertheless, the navigation system based on GNSS would be interrupted in the challenging environments. Therefore, the inertial navigation system (INS) has been widely combined with GNSS to overcome this issue. For INS, the core concept is the measurements of Inertial Measurement Unit (IMU). In order to integrate the measurements of IMU with several sensors such as GNSS receivers, odometers, and so on, we should transform the measurements of IMU from body frame to navigation frame. The initial alignment just represents the process of finding the accurate initial rotation matrix between body frame and navigation frame in the beginning of navigation. However, initial misalignment angles would cause large error of INS. Hence, obtaining an accurate initial rotation matrix from body frame to navigation frame is an important issue to get the better navigation performance. In the research, an integrated navigation system is developed to validate the initial alignment algorithm. With the data pre-processing and accurate calibration. the proposed method of initial alignment can get precise initial ration matrix. The errors of roll pitch, and yaw angle are all smaller than 1 degree after initial alignment. Moreover, the time threshold of initial alignment is set by manual traditionally. A method of finding threshold of coarse alignment is proposed in this research.
LIDAR IMMS VS HANDHELD MULTICAMERA SYSTEM: A STRESS-TEST IN A MOUNTAIN TRAILPATH
Authors: Marotta F. , Perfetti L. , Fassi F. , Achille C. , Vassena G. P. M.
Published: May 2022

Abstract. Indoor Mobile Mapping Systems (IMMS) are attracting growing attention, especially when LiDAR sensors are considered, thanks to the possibility to obtain wide range and complete data in those areas where GNSS signal is not available. However, the drift error that accumulates during the acquisition is often inadequate in the absence of quality constraints in case of extensive acquisitions. Concurrently, recent developments regarding multicamera mobile solutions have shown promising results in containing the drift error, but data produced are too noisy and not enough complete in terms of acquisition range. This paper compares a Laser Scanner IMMS and a multicamera system in a stress test concerning the survey of a complex and extended route. The two systems are the Laser Scanner Backpack IMMS Heron MS Twin Color produced by Gexcel and a laboratory prototype of a handheld photogrammetric multicamera named Ant3D. The objectives are to calculate and compare the drift errors and to evaluate the quality of the produced point clouds. Quantitative results demonstrate that the drift error per meter of trajectory for the Heron Backpack is 10 times greater than the one of the multicamera. From a qualitative aspect, Heron Backpack generates 3D data in a wider range, allowing a more complete reconstruction of the environment when compared to the multicamera system one. On the other hand, the encumbrance and manoeuvrability of Ant3D make it more versatile in surveying very narrow spaces.
AUTOMATED MODELLING OF ROAD FOR HIGH-DEFINITION MAPS WITH OPENDRIVE FORMAT UTILIZING MOBILE MAPPING MEASUREMENTS
Authors: Pai H.-Y. , Zeng J.-C. , Tsai M.-L. , Cheng K.-W.
Published: May 2022

Abstract. High-definition maps (HD Maps) becomes a trend supporting autonomous vehicles (AVs) which provides accurate auxiliary information about geometries of road, such as center lines of lanes, geometries of roads, traffic signs, etc. It is not restricted by the severe environment, lack of Global Navigation Satellite System (GNSS) signal, or torrential rain, for Avs; furthermore, the standard of HD Maps is defined as tens of centimeters positioning level. However, the production cost of HD Maps is enormous involving human resources and time. The general way of producing HD Maps is to vectorize the roads from point clouds to shapefiles and import them into Geographic Information System (GIS) software to generate HD Maps. In order to simplify this complicated process, this article purposes an algorithm to automated generate high-definition maps from road marks’ data which is extracted from point clouds. The methodology in this article is mainly dived into three steps, extraction of road marks, classify lane lines, and modelling OpenDRIVE files. The achieved 2D and 3D accuracies of proposed algorithm in first fields are about 0.069 m in 2D and 0.107 m, respectively.
HIGH-DEFINITION POINT CLOUD MAP-BASED 3D LiDAR-IMU CALIBRATION FOR SELF-DRIVING APPLICATIONS
Authors: Srinara S. , Chiu Y.-T. , Tsai M.-L. , Chiang K.-W.
Published: May 2022

Abstract. The multi-sensor fusion scheme has become more and more popular these days with its great potential to estimate reliable navigation information for the modern development in automated driving system (ADS) and mobile mapping systems (MMS). Since these systems are combined with numerous navigation sensors, thus their geometric relationship should be precisely known. This study focuses on practical aspects when calibrating LiDAR-IMU mounting parameters (lever-arms and bore-sight angles) in land-based MMS. This calibration model is based on expressing the mounting parameters within the direct georeferencing equation for each epoch time and conditioning a set of INS/GNSS and LiDAR navigation solutions to lie on it. There is no need for a required information about the planar features in the calibration field as part of the unknowns. Such conditions are only benefitable in the residential area where the presence of sufficient planes in form of building is abundant. We present an approach for recovery the mounting parameters by conditioning the high-definition (HD) point cloud map-based LiDAR information and INS/GNSS navigation solutions through the least-squares solutions. The presented results and discussion mainly focus on practical examples with data from land-based MMS. Preliminary results indicate that correct calibration parameters are not only capable to improve the performance of point cloud georeferencing but also dramatically provide reliable performance evaluation of navigation estimation. Moreover, these findings show that the studied method is not only applicable in the featureless environment but also in its practicality to the self-driving applications.
INVESTIGATIONS ON THE EFFECT OF HD PROCESSING IN LAND COVER CLASSIFICATION
Authors: Yalcin I. , Karakas G. , Kocaman S. , Saunier S. , Albinet C.
Published: May 2022

Abstract. The requirement of automated Land Use/Land Cover (LULC) classification has arisen in ecosystem related applications, such as natural hazard assessments, urban and rural area planning, natural resource management, etc. The data source and the classification method used in the production of LULC maps depend on the study area size and the location, and also determined by taking the time and cost into account. Recently, MAXAR Technologies announced a new product, High Definition (HD) with 15 cm resolution, which is obtained by post-processing of images with 30 cm Ground Sampling Distance (GSD). The post-processing employs machine learning methods. On the other side, the effect of HD processing on the image quality, and the usability of such products in various applications are still needed to be investigated. In this study, the influence of HD processing algorithm on LULC classification results was investigated by using 15 cm HD and 30 cm resolution images provided by MAXAR. By using the Random Forest (RF) and Support Vector Machine (SVM) methods in two different study areas, image classification was performed to detect water, vegetation, asphalt road, building, shadow, agriculture and barren land classes. The results show that in HD products, the edges of objects were sharper, whereas the classification noise was higher inside agricultural fields. Considering the overall results, it can be concluded that with the use of HD products in urban areas, improved LULC maps can be obtained.
ACCURACY ANALYSIS OF REAL-TIME OBJECT POSITIONING WITHOUT GCP FOR IMAGES FROM UAV OBLIQUE ULTRA-LONG FOCAL SMALL VIEW FIELD WHISKBROOM CAMERA SYSTEM
Authors: Ye Q. , Zhang X. , Lin Y. , Jian J.
Published: May 2022

Abstract. Using images from UAV oblique ultra-long focal small view field whiskbroom camera (ULF-SVF-WC) system for object positioning and mapping is more difficult than conventional aerial photogrammetry, for the particularity of oblique ULF-SVF-WC imaging mode. Therefore, the precision and accuracy of its object positioning are also quite different from that of the conventional UAV photography. In this paper, we analysed the accuracy of real-time object positioning without ground control points (GCPs) for images from UAV oblique ULF-SVF-WC System. Firstly, we studied the imaging principles and characteristics of the oblique ULF-SVF-WC system. Then, we established the coordinate transformation relationship from the object point to the image point and constructed a strict imaging model for oblique ULF-SVF-WC image, which was used for real-time single-ray back-projection positioning assisted by DEM. Thirdly, we quantitatively analysed the distribution and variation of the oblique ULF-SVF-WC image single-ray back-projection errors in theory based on error propagation law and simulation data. Finally, we conducted the experiment of real oblique ULF-SVF-WC flight images for the actual positioning accuracy analysis. The experiment results showed that: the influence of system error on positioning generally conforms to the distribution and variation of theoretical precision, that is, the accuracy of scanning direction is much lower than that of the flight direction; while the accuracy of actual single-ray back-projection positioning is evidently lower than that of the theoretical analysis and there are obvious system errors in the positioning residuals. It indicates that the 6 external orientation elements calculated from POS data contains obvious system error whose influence is greater than random error and this should be eliminated in real-time single-ray back-projection for object positioning.
COMPARING ACCURACY OF ULTRA-DENSE LASER SCANNER AND PHOTOGRAMMETRY POINT CLOUDS
Authors: Pirotti F. , Piragnolo M. , Vettore A. , Guarnieri A.
Published: May 2022

Abstract. Massive point clouds have now become a common product from surveys using passive (photogrammetry) or active (laser scanning) technologies. A common question is what is the difference in terms of accuracy and precision of different technologies and processing options. In this work four ultra-dense point-clouds (PCs) from drone surveys are compared. Two PCs were created from imagery using a photogrammetric workflow, with and without ground control points. The laser scanning PCs were created with two drone flights with Riegl MiniVUX-3 lidar sensor, resulting in a point cloud with ~300 million points, and Riegl VUX-120 lidar sensor, leading to a point cloud with ~1 billion points. Relative differences between pairs from permutations of the four PCs are analysed calculating point-to-point distances over nearest neighbours. Eleven clipped PC subsets are used for this task. Ground control points (GCPs) are also used to assess residuals in the two photogrammetric point clouds in order to quantify the improvement from using GCPs vs not using GCPs when processing the images.Results related to comparing the two photogrammetric point clouds with and without GCPs show an improvement of average absolute position error from 0.12 m to 0.05 m and RMSE from 0.03 m to 0.01 m. Point-to-point distances over the PC pairs show that the closest point clouds are the two lidar clouds, with mean absolute distance (MAD), median absolute distance (MdAD) and standard deviation of distances (RMSE) respectively of 0.031 m, 0.025 m, 0.019 m; largest difference is between photogrammetric PC with GCPs, with 0.208 m, 0.206 m and 0.116 m, with the Z component providing most of the difference. Photogrammetry without GCP was more consistent with the lidar point clouds, with MAD of 0.064 m, MdAD of 0.048 m and RMSE value of 0.114 m.
A SHORT-CUT CONNECTIONS-BASED NEURAL NETWORK FOR BUILDING EXTRACTION FROM HIGH RESOLUTION ORTHOIMAGERY
Authors: He Z. , He H. , Li J. , Chapman M. A. , Ding H.
Published: May 2022

Abstract. Extracting building footprints utilizing deep learning-based (DL-based) methods for high-resolution remote sensing images is one of the current research interest areas. However, the extraction results suffer from blurred edges, rounded corners and detail loss in general. Hence, this article presents a detail-oriented deep learning network named eU-Net (enhanced U-Net). The method adopted in this study, imagery send into the pre-module, which consists of the Canny edge detector, Principal Component Analysis (PCA) and the inter-band ratio operations, before feeding them into the network. Then, process skips connections used in the network to reduce the loss of details during edge and corner detection. The encoding and decoding modules, in this network, are redesigned to expand the perceptual field with shortcut connections and stacked layers. Finally, a Dropout module is added in the bottom layer of the network to avoid the over-fitting problem. The experimental results indicate that the methods used in this study outperform other commonly used and state-of-the-art methods of FCN-8s, U-net, DeepLabv3 and Fast SCNN.
AI-BASED 3D DETECTION OF PARKED VEHICLES ON A MOBILE MAPPING PLATFORM USING EDGE COMPUTING
Authors: Meyer J. , Blaser S. , Nebiker S.
Published: May 2022

Abstract. In this paper we present an edge-based hardware and software framework for the 3D detection and mapping of parked vehicles on a mobile mapping platform for the use case of on-street parking statistics. First, we investigate different point cloud-based 3D object detection methods on our extremely dense and noisy depth maps obtained from low-cost RGB-D sensors to find a suitable object detector and determine the optimal preparation of our data. We then retrain the chosen object detector to detect all types of vehicles, rather than standard cars only. Finally, we design and develop a software framework integrating the newly trained object detector. By repeating the parking statistics of our previous work (Nebiker et al., 2021), our software is tested regarding the detection accuracy. With our edge-based framework, we achieve a precision and recall of 100% and 98% respectively on any parking configuration and vehicle type, outperforming all other known work on on-street parking statistics. Furthermore, our software is evaluated in terms of processing speed and volume of generated data. While the processing speed reaches only 1.9 frames per second due to limited computing resources, the amount of data generated is just 0.25 KB per frame.
3D MAPPING OF BURIED PIPES IN MULTI-CHANNEL GPR DATA
Authors: Karle N. , Boldt M. , Thiele A. , Thoennessen U.
Published: May 2022

Abstract. Ground Penetrating Radar (GPR) allows a non-destructive analysis of the subsurface by using electromagnetic waves. GPR is used in application fields such as archeology and civil engineering, where the detection of buried objects is in demand. Such objects, e.g. pipes, lead to a disturbance of the propagation of the radar signal in the underground. A manual detection of disturbing objects can be both time-consuming and tedious, depending on the number of GPR images to be investigated. Hence, automatic methods should be considered. In this study, an object-oriented image analysis approach for the automatic detection and mapping of buried pipes is presented and evaluated. As dataset, measurements of the multi-channel system Stream C are considered.
SFOC: A NOVEL MULTI-DIRECTIONAL AND MULTI-SCALE STRUCTURAL DESCRIPTOR FOR MULTIMODAL REMOTE SENSING IMAGE MATCHING
Authors: Zhu B. , Zhang J. , Tang T. , Ye Y.
Published: May 2022

Abstract. Accurate matching of multimodal remote sensing (RS) images (e.g., optical, infrared, LiDAR, SAR, and rasterized maps) is still an ongoing challenge because of nonlinear radiometric differences (NRD) between these images. Considering that structural properties are preserved between multimodal images, this paper proposes a robust matching method based on multi-directional and multi-scale structural features, which consist of two critical steps. Firstly, a novel structural descriptor named the Steerable Filters of first- and second-Order Channels (SFOC) is constructed to address severe NRD, which combines the first- and second-order gradient information by using the steerable filters to depict multi-directional and multi-scale structural features of images. Meanwhile, SFOC is further enhanced by performing the dilated Gaussian convolutions with different dilated rates on it, which can capture multi-level context structural features and improve the ability to resist noise. Then, a fast similarity measure, called Fast Normalized Cross-Correlation (Fast-NCCSFOC), is established to detect correspondences by a template matching scheme, which employs the Fast Fourier Transform (FFT) technique and the integral image to improve the matching efficiency. The performance of the proposed SFOC has been evaluated with many different kinds of multimodal RS images, and experimental results show its superior matching performance compared with the state-of-the-art methods.
3D SURFACE RECONSTRUCTION FROM MULTI-VIEW AND MULTI-DATE GOOGLE EARTH SATELLITE IMAGES WITH 3D HOMOGRAPHY-BASED PROJECTIVE RECONSTRUCTION
Authors: Lee M. J. , Park S. Y.
Published: May 2022

Abstract. In this paper, we propose the 3D surface reconstruction scheme using multi-view and multi-date Google Earth (GE) satellite images. Multi-view stereo matching (MVS) scheme is one of the methods for reconstructing dense 3D surface based on multi-view images and corresponding camera pose geometry. If many views are input, MVS can estimate the disparity (depth) by matching pixels. However, the common users are not always possible to obtain both multi-view satellite images and the camera geometry (such as Rational Polynomial Camera) in various earth regions. Instead, the GE provides multi-view and multi-date satellite images of earth regions. Therefore, the goal of the proposed method is to perform a 3D surface reconstruction using the GE satellite image. We suppose that the GE satellite image is a pinhole camera model, and the camera pose geometry is estimated using the perspective projection model (PPM) based structure from the motion (SfM) method. Then the 3D surface is reconstructed and fusion using the MVS method. However, the GE satellite image is a transformed pseudo-orthoimage for integration into the raster image. For this reason, the camera pose geometry is inaccurately computed in the SfM process. Thus, the high-rise structures in the reconstructed 3D surface are distorted (distorted hexahedral 3D space). Importantly, the satellite image is a weak PPM and it can express the orthographic projection model. Therefore, we compute 3D homography for transforming between distorted hexahedral space to orthographic cuboid space. Then, the distorted 3D surface is transformed using a projective reconstruction based on 3D homography. The transformed 3D surface has the correct shape in the orthographic projection model. The advantage of the proposed method is that the 3D surface of various earth regions is reconstructed using simply accessible GE satellite images. And the transformed 3D surface is reconstructed into orthographic projection model space, thus the orthoimage can be generated using projection.
MULTIRESOLUTION PATCH-BASED DENSE RECONSTRUCTION INTEGRATING MULTIVIEW IMAGES AND LASER POINT CLOUD
Authors: Zhang R. , Yi X. , Li H. , Liu L. , Lu G. , Chen Y. , Guo X.
Published: May 2022

Abstract. A dense point cloud with rich and realistic texture is generated from multiview images using dense reconstruction algorithms such as Multi View Stereo (MVS). However, its spatial precision depends on the performance of the matching and dense reconstruction algorithms used. Moreover, outliers are usually unavoidable as mismatching of image features. The lidar point cloud lacks texture but performs better spatial precision because it avoids computational errors. This paper proposes a multiresolution patch-based 3D dense reconstruction method based on integrating multiview images and the laser point cloud. A sparse point cloud is firstly generated with multiview images by Structure from Motion (SfM), and then registered with the laser point cloud to establish the mapping relationship between the laser point cloud and multiview images. The laser point cloud is reprojected to multiview images. The corresponding optimal level of the image pyramid is predicted by the distance distribution of projected pixels, which is used as the starting level for patch optimization during dense reconstruction. The laser point cloud is used as stable seed points for patch growth and expansion, and stored by the dynamic octree structure. Subsequently, the corresponding patches are optimized and expanded with the pyramid image to achieve multiscale and multiresolution dense reconstruction. In addition, the octree’s spatial index structure facilitates parallel computing with highly efficiency. The experimental results show that the proposed method is superior to the traditional MVS technology in terms of model accuracy and completeness, and have broad application prospects in high-precision 3D modeling of large scenes.
THE CHALLENGE OF AUTOMATION FOR LARGE SCALE TOPOGRAPHIC MAPPING OF OIL AND GAS DEPOSITS BASED ON TERRESTRIAL LASER SCANNING DATA
Authors: Altyntsev M. A. , Altyntseva M. A.
Published: May 2022

Abstract. Terrestrial laser scanning (TLS) is a modern method of spatial data acquisition. The most common application of this method is large scale topographic mapping. Point clouds obtained with laser scanning contain all necessary data for producing topographic maps and plans. One of the territories, where TLS is particularly important, is oil and gas deposits. Built-up areas of oil and gas deposits are represented with complicated industrial objects. On the one hand, introduction of TLS method for surveying of these areas significantly speeds up field surveying works. On the other hand, dense point clouds of built-up areas slow down the process of mapping due to the necessity to filter extra data. To hasten the process of mapping special algorithms of feature extraction from point cloud and techniques of compiling plan and maps are being developed. Nonetheless, majority of developed algorithms can work fine for point clouds of high uniform density where the number of objects is not large. For built-up areas developed algorithms can be not applicable. The basic steps of compiling a topographic plan are described. It is discussed which object types can be automatically extracted and vectorized in built-up areas of oil and gas deposits. The examples of manual point cloud vectorization are given.
MIXED REALITY VISUALIZATION OF POINT CLOUDS FOR SUPPORTING TERRESTRIAL LASER SCANNING
Authors: Ohno K. , Date H. , Kanai S.
Published: May 2022

Abstract. 3D point clouds from terrestrial laser scanners (TLS) are used in a variety of fields and applications. To acquire high-quality point clouds that have enough point density, small scanning errors, and no lack of points in important regions, appropriate scan planning, including determination of scanner positions and scan conditions, is required. Currently, planning is supported by knowledge and experience of skilled workers, and it is difficult to ensure the quality of acquired point clouds. In this study, we propose a system for visualization of point clouds to support the acquisition of high-quality point clouds using TLS. The system allows the user to see and check the quality of scanned TLS point clouds and unscanned regions intuitively by superimposing the point clouds onto the real world using a mixed reality (MR) device. In addition, the system supports finding the next best scanner position for additional laser scans based on predicted scan quality visualization to acquire higher-quality points or fill the unscanned regions.
A BUILDING CHANGE DETECTION METHOD BASED ON A SINGLE ALS POINT CLOUD AND A HRS IMAGE
Authors: Yang Z. , Chai J. X. , Zhang Y. S. , Mei S. H.
Published: May 2022

Abstract. For common remote sensing image change detection based on different time phases, it is difficult to solve the problem of surface tilt caused by the different shooting angle and time, which makes it difficult to complete the accurate registration. Some scholars utilized three-dimensional data for change detection to avoid registration problem, however, it costs very high for using 3D data to detect changes. Aim at this problem, this paper proposes a method of combining a single phase of ALS (Airborne Laser Scanning) data and HRS (High Resolution Satellite) image. It is composed of the following four steps: (1) Extracting the shadow area of the new-phase optical image, and superimposing it with the classified old-time point cloud data, and then the disappeared building area and the approximate building area are obtained according to the associated relationship between the shadow area and buildings. (2) Determining the unchanged building areas as positive samples, and taking the remaining area and vegetation area after removing the approximate buildings from the image as negative samples, and then GrabCut algorithm is used to segment new-phase HRS images to obtain building areas. (3) Comparing between building areas obtained in the previous step and the registered old-time ALS data to obtain a new building area with noise. (4) Denoising the results of the previous step to obtain the final new building area. Two datasets are used to verify the method. The detection accuracy of the disappeared buildings is over 85%, and the detection accuracy of the newly added buildings is over 70%.
UNCERTAINTY REPRESENTATION AND QUANTIFICATION OF 3D BUILDING MODELS
Authors: Zou Q. , Sester M.
Published: May 2022

Abstract. The quality of environmental perception is of great interest for localization tasks in autonomous systems. Maps, generated from the sensed information, are often used as additional spatial references in these applications. The quantification of the map uncertainties gives an insight into how reliable and complete the map is, avoiding the potential systematic deviation in pose estimation. Mapping 3D buildings in urban areas using Light detection and ranging (LiDAR) point clouds is a challenging task as it is often subject to uncertain error sources in the real world such as sensor noise and occlusions, which should be well represented in the 3D models for the downstream localization tasks. In this paper, we propose a method to model 3D building façades in complex urban scenes with uncertainty quantification, where the uncertainties of windows and façades are indicated in a probabilistic fashion. The potential locations of the missing objects (here: windows) are inferred by the available data and layout patterns with the Monte Carlo (MC) sampling approach. The proposed 3D building model and uncertainty measures are evaluated using the real-world LiDAR point clouds collected by Riegl Mobile Mapping System. The experimental results show that our uncertainty representation conveys the quality information of the estimated locations and shapes for the modelled map objects.