bluuebunny/crossref_metadata_2025 huggingface dataset:
Diagnostic comparison of Centers for Disease Control and Prevention and International Obesity Task Force criteria for obesity classification in South African children
Authors: Moselakgomo Violet Kankane , Van Staden Marlise
Published: August 2017

Background: This study was designed to estimate overweight and obesity in school children by using contrasting definitions recommended by the Centers for Disease Control and Prevention (CDC) and the International Obesity Task Force (IOTF).Method: The sample size consisted of 1361 learners (n = 678 boys; n = 683 girls) aged 9–13 years who were randomly selected from Mpumalanga and Limpopo provinces of South Africa. A cross-sectional and descriptive design was used to measure the children’s anthropometric characteristics. Based on height and weight measurements, the children’s body mass index (BMI) was calculated and used to classify them as underweight, overweight and obese. Percentage body fat was calculated from the sum of two skinfolds (i.e. triceps and subscapular). Age-specific BMI, percentage body fat and sum of skinfolds were examined for the boys and girls.Results: A higher prevalence of overweight and obesity was found in boys and girls when the CDC BMI categories were used. In contrast, the IOTF BMI classifications indicated a strong prevalence of underweight among the children.Conclusion: In contrast to the IOTF index that yielded a greater occurrence of underweight among South African children, the CDC criteria indicated a higher prevalence of obesity and overweight among the same children. Future large-scale surveillance studies are needed to determine the appropriateness of different definitions in order to establish a more reliable indicator for estimating overweight and obesity in South African children.
Core competencies of radiographers working in rural hospitals of KwaZulu-Natal, South Africa
Authors: Mung'omba Bernard , Botha Annali D.H.
Published: August 2017

Introduction: Rural radiographers require, over and above traditional radiographic expertise, additional competencies which to a certain degree are unique however not limited to rural practice. Previous studies, however, have focused more attention primarily on other rural health professionals such as doctors and nurses leaving a research need in this field. This article focuses on the additional competencies that may be required for rural radiographers.Aim: To investigate and identify additional core competencies required by radiographers working in rural hospitals of KwaZulu-Natal in order to propose a continuous professional development strategy aimed at rural radiographers.Methods: An exploratory sequential design was utilised with qualitative (Phase I) and quantitative (Phase II) strands involving seven participants and 109 respondents, respectively. Only radiographers working in rural KwaZulu-Natal hospitals were included in the study. The four major themes and categories identified in Phase I were used to develop data collection instrument for Phase II of the study.Results: Collectively, the results revealed that there were a number of additional core competencies such as, but not limited to, teamwork, ability to do basic obstetric ultrasound scans, leadership, management and reporting on plain radiographs, all of which are required by rural radiographers. In 2014 when these competencies were checked against a single curriculum, it was found that majority of them were either partially covered or not at all covered.Conclusion: The study provides additional information on context specific core competencies and, therefore, may act as a catalyst to influence the future of radiographers working in rural areas of South Africa.
Using narratives to understand the motivational factors and experience of being a self-initiated academic expatriate in South Africa
Authors: Harry Tinashe T. , Dodd Nicole M. , Chinyamurindi Willie T.
Published: August 2017

Orientation: A growing movement of foreign nationals is settling in South Africa. Given this, there is a need to understand not only those factors influencing foreign nationals to settle in South Africa but also their lived experiences as a basis for individual career development.Research purpose: To investigate the expatriation motivational factors and experiences of selfinitiated academic expatriates in South Africa.Motivation for the study: Calls have been made within the careers literature for more empirical focus on understanding career development using some of the neglected sample groups.Research approach, design and method: The interpretive paradigm was adopted to understand the main purpose of the study. Guided by study objectives, unstructured interviews were conducted using a sample of foreign academics working in South Africa (n = 25).Main findings: Individual stories and narratives highlighted that academics relocated for the following reasons: (1) individual preference, (2) economic meltdown and (3) political conditions. Furthermore, the lived experiences of the expatriates reflected discrimination within the workplace and the community of residences in South Africa.Practical and managerial implications: Research findings indicate that the human resources (HR) function can come up with interventions that positively influence the lived experience and career development of foreign academics working in South Africa.Contribution: The expatriate experience framed in this study provides a picture of the career development processes of neglected sample groups in the extant literature. Such an understanding is key in advancing literature and proposing interventions. All this is important given the global trend on labour and skills movement added to the role South Africa plays in the international arena.
Adult attention-deficit hyperactivity disorder: Why should we pay attention?
Authors: Schoeman Renata , Albertyn Ruth , De Klerk Manie
Published: August 2017

Background: Attention-deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder, with a chronic, costly and debilitating course if untreated. Limited access to diagnosis and treatment for adults with ADHD contributes to the cost of the disorder and the burden of disease.Aim: This study aims to identify the barriers to care for adults with ADHD.Methods: A qualitative analysis of semi-structured interviews with 10 key opinion leaders in the field of adult ADHD in SA was conducted to obtain narratives regarding frustrations experienced when treating adults with ADHD and needs of patients regarding management of ADHD. Qualitative content analysis was completed using Atlas.ti (version 7).Results: Four key themes which emerged from the interviews were ‘lack of recognition of the disorder’, ‘lack of access to diagnosis’, ‘lack of access to treatment’ and ‘a life of perpetual failure’. Core to these themes are the lack of knowledge amongst health care professionals, funders, and society at large.Conclusion: Our findings expand on previous research regarding the need to increase the knowledge base on adult ADHD. A collaborative stakeholder approach is needed to provide research and training for improved diagnosis and treatment for adults with ADHD in the South African context.
The use of infrared thermography for welfare assessment during the application of ear tags to lambs
Authors: Karakuş Murat , Karakuş Ferda
Published: August 2017

Abstract. The aim of this study was to determine the effect of metal-tipped, plastic-tipped, and electronic ear tags on the likelihood of infection using infrared thermography and to evaluate the effect on welfare by examining the behavioral responses of the lambs. Ninety lambs with an average age of 6 months were used in this study. Before the application of the ear tags, infrared images of the right and left ears of the lambs were taken with the thermal camera and the infrared temperatures were recorded. Measurements were repeated on days 1, 4, 10, and 30 after the ear tag application. The mean of infrared ear temperatures on days 0, 1, 4, 10, and 30 were found to be 14.60, 23.20, 23.77, 20.36, and 17.61 °C for the metal-tipped ear tag group; 15.69, 21.50, 20.42, 18.00, and 16.39 °C for the plastic-tipped ear tag group; and 15.17, 29.47, 27.49, 25.93, and 20.61 °C for the electronic ear tag group. The infrared temperatures on days 1, 4, and 10 in the control and experimental groups were significantly different from each other (P < 0.001). The plastic-tipped ear tags caused fewer problems and are preferred to the traditional ear tags with metal tips. The electronic ear tags caused more inflammatory reactions compared to metal- or plastic-tipped ear tags. The infrared thermography method may be used as a useful tool in the early detection of the inflammatory reactions and infections caused by the application of ear tags.
Estimation of nocturnal CO2 and N2O soil emissions using changes in surface boundary layer mass storage
Authors: Grant Richard H. , Omonode Rex A.
Published: August 2017

Abstract. Abstract. Annual emissions of greenhouse and other trace gases requires knowledge of the emissions throughout the year. Unfortunately emissions into the surface boundary layer during stable, calm nocturnal periods are not measureable using most micrometeorological methods due to non-stationarity and uncoupled flow. However, during nocturnal periods with very light winds the concentration of carbon dioxide (CO2) and nitrous oxide (N2O) frequently accumulates near the surface and this mass accumulation can be used to determine emissions. Gas concentrations were measured at four heights (one within and three above canopy) and turbulence was measured at three heights above a mature 2.5 m high maize canopy from 23 July to 10 September 2015. Nocturnal CO2 and N2O fluxes from the canopy were determined using the accumulation of mass within a 6.3 m vertical domain of the nocturnal surface boundary layer. Diffusive fluxes out of the top of this domain were also estimated. Fluxes during near-calm nights (friction velocities
eddy4R 0.2.0: a DevOps model for community-extensible processing and analysis of eddy-covariance data based on R, Git, Docker, and HDF5
Authors: Metzger Stefan , Durden David , Sturtevant Cove , Luo Hongyan , Pingintha-Durden Natchaya , Sachs Torsten , Serafimovich Andrei , Hartmann Jörg , Li Jiahong , Xu Ke , Desai Ankur R.
Published: August 2017

Abstract. Large differences in instrumentation, site setup, data format, and operating system stymie the adoption of a universal computational environment for processing and analyzing eddy-covariance (EC) data. This results in limited software applicability and extensibility in addition to often substantial inconsistencies in flux estimates. Addressing these concerns, this paper presents the systematic development of portable, reproducible, and extensible EC software achieved by adopting a development and systems operation (DevOps) approach. This software development model is used for the creation of the eddy4R family of EC code packages in the open-source R language for statistical computing. These packages are community developed, iterated via the Git distributed version control system, and wrapped into a portable and reproducible Docker filesystem that is independent of the underlying host operating system. The HDF5 hierarchical data format then provides a streamlined mechanism for highly compressed and fully self-documented data ingest and output. The usefulness of the DevOps approach was evaluated for three test applications. First, the resultant EC processing software was used to analyze standard flux tower data from the first EC instruments installed at a National Ecological Observatory (NEON) field site. Second, through an aircraft test application, we demonstrate the modular extensibility of eddy4R to analyze EC data from other platforms. Third, an intercomparison with commercial-grade software showed excellent agreement (R2  =  1.0 for CO2 flux). In conjunction with this study, a Docker image containing the first two eddy4R packages and an executable example workflow, as well as first NEON EC data products are released publicly. We conclude by describing the work remaining to arrive at the automated generation of science-grade EC fluxes and benefits to the science community at large. This software development model is applicable beyond EC and more generally builds the capacity to deploy complex algorithms developed by scientists in an efficient and scalable manner. In addition, modularity permits meeting project milestones while retaining extensibility with time.
PHOTOGRAMMETRIC 3D BUILDING RECONSTRUCTION FROM THERMAL IMAGES
Authors: Maset E. , Fusiello A. , Crosilla F. , Toldo R. , Zorzetto D.
Published: August 2017

Abstract. This paper addresses the problem of 3D building reconstruction from thermal infrared (TIR) images. We show that a commercial Computer Vision software can be used to automatically orient sequences of TIR images taken from an Unmanned Aerial Vehicle (UAV) and to generate 3D point clouds, without requiring any GNSS/INS data about position and attitude of the images nor camera calibration parameters. Moreover, we propose a procedure based on Iterative Closest Point (ICP) algorithm to create a model that combines high resolution and geometric accuracy of RGB images with the thermal information deriving from TIR images. The process can be carried out entirely by the aforesaid software in a simple and efficient way.
AUTOMATED INSPECTION OF POWER LINE CORRIDORS TO MEASURE VEGETATION UNDERCUT USING UAV-BASED IMAGES
Authors: Maurer M. , Hofer M. , Fraundorfer F. , Bischof H.
Published: August 2017

Abstract. Power line corridor inspection is a time consuming task that is performed mostly manually. As the development of UAVs made huge progress in recent years, and photogrammetric computer vision systems became well established, it is time to further automate inspection tasks. In this paper we present an automated processing pipeline to inspect vegetation undercuts of power line corridors. For this, the area of inspection is reconstructed, geo-referenced, semantically segmented and inter class distance measurements are calculated. The presented pipeline performs an automated selection of the proper 3D reconstruction method for on the one hand wiry (power line), and on the other hand solid objects (surrounding). The automated selection is realized by performing pixel-wise semantic segmentation of the input images using a Fully Convolutional Neural Network. Due to the geo-referenced semantic 3D reconstructions a documentation of areas where maintenance work has to be performed is inherently included in the distance measurements and can be extracted easily. We evaluate the influence of the semantic segmentation according to the 3D reconstruction and show that the automated semantic separation in wiry and dense objects of the 3D reconstruction routine improves the quality of the vegetation undercut inspection. We show the generalization of the semantic segmentation to datasets acquired using different acquisition routines and to varied seasons in time.
SQUEEZEPOSENET: IMAGE BASED POSE REGRESSION WITH SMALL CONVOLUTIONAL NEURAL NETWORKS FOR REAL TIME UAS NAVIGATION
Authors: Müller M. S. , Urban S. , Jutzi B.
Published: August 2017

Abstract. The number of unmanned aerial vehicles (UAVs) is increasing since low-cost airborne systems are available for a wide range of users. The outdoor navigation of such vehicles is mostly based on global navigation satellite system (GNSS) methods to gain the vehicles trajectory. The drawback of satellite-based navigation are failures caused by occlusions and multi-path interferences. Beside this, local image-based solutions like Simultaneous Localization and Mapping (SLAM) and Visual Odometry (VO) can e.g. be used to support the GNSS solution by closing trajectory gaps but are computationally expensive. However, if the trajectory estimation is interrupted or not available a re-localization is mandatory. In this paper we will provide a novel method for a GNSS-free and fast image-based pose regression in a known area by utilizing a small convolutional neural network (CNN). With on-board processing in mind, we employ a lightweight CNN called SqueezeNet and use transfer learning to adapt the network to pose regression. Our experiments show promising results for GNSS-free and fast localization.
INFORMATION-DRIVEN AUTONOMOUS EXPLORATION FOR A VISION-BASED MAV
Authors: Palazzolo E. , Stachniss C.
Published: August 2017

Abstract. Most micro aerial vehicles (MAV) are flown manually by a pilot. When it comes to autonomous exploration for MAVs equipped with cameras, we need a good exploration strategy for covering an unknown 3D environment in order to build an accurate map of the scene. In particular, the robot must select appropriate viewpoints to acquire informative measurements. In this paper, we present an approach that computes in real-time a smooth flight path with the exploration of a 3D environment using a vision-based MAV. We assume to know a bounding box of the object or building to explore and our approach iteratively computes the next best viewpoints using a utility function that considers the expected information gain of new measurements, the distance between viewpoints, and the smoothness of the flight trajectories. In addition, the algorithm takes into account the elapsed time of the exploration run to safely land the MAV at its starting point after a user specified time. We implemented our algorithm and our experiments suggest that it allows for a precise reconstruction of the 3D environment while guiding the robot smoothly through the scene.
UAV VISUAL AUTOLOCALIZATON BASED ON AUTOMATIC LANDMARK RECOGNITION
Authors: Silva Filho P. , Shiguemori E. H. , Saotome O.
Published: August 2017

Abstract. Deploying an autonomous unmanned aerial vehicle in GPS-denied areas is a highly discussed problem in the scientific community. There are several approaches being developed, but the main strategies yet considered are computer vision based navigation systems. This work presents a new real-time computer-vision position estimator for UAV navigation. The estimator uses images captured during flight to recognize specific, well-known, landmarks in order to estimate the latitude and longitude of the aircraft. The method was tested in a simulated environment, using a dataset of real aerial images obtained in previous flights, with synchronized images, GPS and IMU data. The estimated position in each landmark recognition was compatible with the GPS data, stating that the developed method can be used as an alternative navigation system.
RESEARCH ON THE APPLICATION OF RAPID SURVEYING AND MAPPING FOR LARGE SCARE TOPOGRAPHIC MAP BY UAV AERIAL PHOTOGRAPHY SYSTEM
Authors: Gao Z. , Song Y. , Li C. , Zeng F. , Wang F.
Published: August 2017

Abstract. Rapid acquisition and processing method of large scale topographic map data, which relies on the Unmanned Aerial Vehicle (UAV) low-altitude aerial photogrammetry system, is studied in this paper, elaborating the main work flow. Key technologies of UAV photograph mapping is also studied, developing a rapid mapping system based on electronic plate mapping system, thus changing the traditional mapping mode and greatly improving the efficiency of the mapping. Production test and achievement precision evaluation of Digital Orth photo Map (DOM), Digital Line Graphic (DLG) and other digital production were carried out combined with the city basic topographic map update project, which provides a new techniques for large scale rapid surveying and has obvious technical advantage and good application prospect.
PERFORMANCE EVALUATION OF sUAS EQUIPPED WITH VELODYNE HDL-32E LiDAR SENSOR
Authors: Jozkow G. , Wieczorek P. , Karpina M. , Walicka A. , Borkowski A.
Published: August 2017

Abstract. The Velodyne HDL-32E laser scanner is used more frequently as main mapping sensor in small commercial UASs. However, there is still little information about the actual accuracy of point clouds collected with such UASs. This work evaluates empirically the accuracy of the point cloud collected with such UAS. Accuracy assessment was conducted in four aspects: impact of sensors on theoretical point cloud accuracy, trajectory reconstruction quality, and internal and absolute point cloud accuracies. Theoretical point cloud accuracy was evaluated by calculating 3D position error knowing errors of used sensors. The quality of trajectory reconstruction was assessed by comparing position and attitude differences from forward and reverse EKF solution. Internal and absolute accuracies were evaluated by fitting planes to 8 point cloud samples extracted for planar surfaces. In addition, the absolute accuracy was also determined by calculating point 3D distances between LiDAR UAS and reference TLS point clouds. Test data consisted of point clouds collected in two separate flights performed over the same area. Executed experiments showed that in tested UAS, the trajectory reconstruction, especially attitude, has significant impact on point cloud accuracy. Estimated absolute accuracy of point clouds collected during both test flights was better than 10 cm, thus investigated UAS fits mapping-grade category.
AUTOMATIC FAULT RECOGNITION OF PHOTOVOLTAIC MODULES BASED ON STATISTICAL ANALYSIS OF UAV THERMOGRAPHY
Authors: Kim D. , Youn J. , Kim C.
Published: August 2017

Abstract. As a malfunctioning PV (Photovoltaic) cell has a higher temperature than adjacent normal cells, we can detect it easily with a thermal infrared sensor. However, it will be a time-consuming way to inspect large-scale PV power plants by a hand-held thermal infrared sensor. This paper presents an algorithm for automatically detecting defective PV panels using images captured with a thermal imaging camera from an UAV (unmanned aerial vehicle). The proposed algorithm uses statistical analysis of thermal intensity (surface temperature) characteristics of each PV module to verify the mean intensity and standard deviation of each panel as parameters for fault diagnosis. One of the characteristics of thermal infrared imaging is that the larger the distance between sensor and target, the lower the measured temperature of the object. Consequently, a global detection rule using the mean intensity of all panels in the fault detection algorithm is not applicable. Therefore, a local detection rule based on the mean intensity and standard deviation range was developed to detect defective PV modules from individual array automatically. The performance of the proposed algorithm was tested on three sample images; this verified a detection accuracy of defective panels of 97 % or higher. In addition, as the proposed algorithm can adjust the range of threshold values for judging malfunction at the array level, the local detection rule is considered better suited for highly sensitive fault detection compared to a global detection rule.
A PREALIMINARY STUDY OF SHIP DETECTION FROM UAV IMAGES BASED ON COLOR SPACE CONVERSION AND IMAGE SEGMENTATION
Authors: Klimkowska A. M. , Lee I.
Published: August 2017

Abstract. Ship detection is an inherent process supporting tasks such as fishery management, ship search, marine traffic monitoring and control, and helps in the prevention of illegal activities. So far, sea and shore monitoring has been carried out by ship patrols and aircrafts along with sea vessel detection from data from space-borne platforms. Recently an increase interest in applying images delivered by UAV for marine application due to their advantages such as high spatial resolution, independence on time acquisition can be noticed. While investigating state of the art methods used for ship detection from different platforms using optical images, we found a significant problem with occurrence of a ship wake. This phenomena may prohibit correct detection of ship location and results in overestimating the ship size as the ship and its wake are often considered as being part of the same object in image or wakes are distinguished as a separate ship due to their possible similar brightness compared with sea vessel. In order to reduce the impact of ship wakes we investigated the behavior of images in different color spaces to provide data with little or almost no trace of ship wake. We took into consideration following color spaces: HSV, YCbCr, NTSC, XYZ and L*a*b and investigated each channel from new images. Finally we decided to use 2nd channel of L*a*b space where the ship wakes occurrence were significantly reduced. Object of interest were detected through the use of image segmentation. Applied method uses edge detection based on the gradient magnitude calculation. Afterwards several characteristics such as centroids, major and minor axis, size and orientation were calculated for later use to remove false positives and thus improve accuracy of the proposed method.
ASSESSING THE UTILITY OF UAV-BORNE HYPERSPECTRAL IMAGE AND PHOTOGRAMMETRY DERIVED 3D DATA FOR WETLAND SPECIES DISTRIBUTION QUICK MAPPING
Authors: Li Q. S. , Wong F. K. K. , Fung T.
Published: August 2017

Abstract. Lightweight unmanned aerial vehicle (UAV) loaded with novel sensors offers a low cost and minimum risk solution for data acquisition in complex environment. This study assessed the performance of UAV-based hyperspectral image and digital surface model (DSM) derived from photogrammetric point clouds for 13 species classification in wetland area of Hong Kong. Multiple feature reduction methods and different classifiers were compared. The best result was obtained when transformed components from minimum noise fraction (MNF) and DSM were combined in support vector machine (SVM) classifier. Wavelength regions at chlorophyll absorption green peak, red, red edge and Oxygen absorption at near infrared were identified for better species discrimination. In addition, input of DSM data reduces overestimation of low plant species and misclassification due to the shadow effect and inter-species morphological variation. This study establishes a framework for quick survey and update on wetland environment using UAV system. The findings indicate that the utility of UAV-borne hyperspectral and derived tree height information provides a solid foundation for further researches such as biological invasion monitoring and bio-parameters modelling in wetland.
VISION BASED OBSTACLE DETECTION IN UAV IMAGING
Authors: Badrloo S. , Varshosaz M.
Published: August 2017

Abstract. Detecting and preventing incidence with obstacles is crucial in UAV navigation and control. Most of the common obstacle detection techniques are currently sensor-based. Small UAVs are not able to carry obstacle detection sensors such as radar; therefore, vision-based methods are considered, which can be divided into stereo-based and mono-based techniques. Mono-based methods are classified into two groups: Foreground-background separation, and brain-inspired methods. Brain-inspired methods are highly efficient in obstacle detection; hence, this research aims to detect obstacles using brain-inspired techniques, which try to enlarge the obstacle by approaching it. A recent research in this field, has concentrated on matching the SIFT points along with, SIFT size-ratio factor and area-ratio of convex hulls in two consecutive frames to detect obstacles. This method is not able to distinguish between near and far obstacles or the obstacles in complex environment, and is sensitive to wrong matched points. In order to solve the above mentioned problems, this research calculates the dist-ratio of matched points. Then, each and every point is investigated for Distinguishing between far and close obstacles. The results demonstrated the high efficiency of the proposed method in complex environments.
3D MODEL GENERATION FROM UAV: HISTORICAL MOSQUE (MASJID LAMA NILAI)
Authors: Mohd Nasir N. H. , Tahar K. N.
Published: August 2017

Abstract. Preserving cultural heritage and historic sites is an important issue. These sites are subjected to erosion and vandalism, and, as long-lived artifacts, they have gone through many phases of construction, damage and repair. It is important to keep an accurate record of these sites using the 3-D model building technology as they currently are, so that preservationists can track changes, foresee structural problems, and allow a wider audience to “virtually” see and tour these sites. Due to the complexity of these sites, building 3-D models is time consuming and difficult, usually involving much manual effort. This study discusses new methods that can reduce the time to build a model using the Unmanned Aerial Vehicle method. This study aims to develop a 3D model of a historical mosque using UAV photogrammetry. In order to achieve this, the data acquisition set of Masjid Lama Nilai, Negeri Sembilan was captured by using an Unmanned Aerial Vehicle. In addition, accuracy assessment between the actual and measured values is made. Besides that, a comparison between the rendering 3D model and texturing 3D model is also carried out through this study.
LAND COVER CLASSIFICATION USING A UAV-BORNE SPECTROMETER
Authors: Natesan S. , Benari G. , Armenakis C. , Lee R.
Published: August 2017

Abstract. Small fixed wing and rotor-copter unmanned aerial vehicles (UAV) are being used for low altitude remote sensing for thematic land classification and precision agriculture applications. Various sensors operating in the non-visible spectrum such as multispectral, hyperspectral and thermal sensors can be used as payloads. This work presents a preliminary study on the use of unmanned aerial vehicle equipped with a compact spectrometer for land cover type characterization. When calibrated, the measured spectra by the UAV spectrometer can be processed and compared reference data to generate georeferenced reflection spectra enabling the identification, classification and characterization of land cover elements. For this case study we used a DJI Flamewheel F550 hexacopter and the FLAME-NIR spectrometer for hyperspectral measurements. The calibration of the spectrometer is described as well the approach to determine its spatial footprint. The spectrometer spectral exposure labeled ground point can be used to determine the land cover classification. Preliminary results of a case-study are presented.
3D MODELING OF INDUSTRIAL HERITAGE BUILDING USING COTSs SYSTEM: TEST, LIMITS AND PERFORMANCES
Authors: Piras M. , Di Pietra V. , Visintini D.
Published: August 2017

Abstract. The role of UAV systems in applied geomatics is continuously increasing in several applications as inspection, surveying and geospatial data. This evolution is mainly due to two factors: new technologies and new algorithms for data processing. About technologies, from some years ago there is a very wide use of commercial UAV even COTSs (Commercial On-The-Shelf) systems. Moreover, these UAVs allow to easily acquire oblique images, giving the possibility to overcome the limitations of the nadir approach related to the field of view and occlusions. In order to test potential and issue of COTSs systems, the Italian Society of Photogrammetry and Topography (SIFET) has organised the SBM2017, which is a benchmark where all people can participate in a shared experience. This benchmark, called “Photogrammetry with oblique images from UAV: potentialities and challenges”, permits to collect considerations from the users, highlight the potential of these systems, define the critical aspects and the technological challenges and compare distinct approaches and software. The case study is the “Fornace Penna” in Scicli (Ragusa, Italy), an inaccessible monument of industrial architecture from the early 1900s. The datasets (images and video) have been acquired from three different UAVs system: Parrot Bebop 2, DJI Phantom 4 and Flytop Flynovex. The aim of this benchmark is to generate the 3D model of the “Fornace Penna”, making an analysis considering different software, imaging geometry and processing strategies. This paper describes the surveying strategies, the methodologies and five different photogrammetric obtained results (sensor calibration, external orientation, dense point cloud and two orthophotos), using separately – the single images and the frames extracted from the video – acquired with the DJI system.
UAV PHOTOGRAMMETRIC SOLUTION USING A RASPBERRY PI CAMERA MODULE AND SMART DEVICES: TEST AND RESULTS
Authors: Piras M. , Grasso N. , Abdul Jabbar A.
Published: August 2017

Abstract. Nowadays, smart technologies are an important part of our action and life, both in indoor and outdoor environment. There are several smart devices very friendly to be setting, where they can be integrated and embedded with other sensors, having a very low cost. Raspberry allows to install an internal camera called Raspberry Pi Camera Module, both in RGB band and NIR band. The advantage of this system is the limited cost (
MULTISENSOR EQUIPPED UAV/UGV FOR AUTOMATED EXPLORATION
Authors: Batzdorfer S. , Bobbe M. , Becker M. , Harms H. , Bestmann U.
Published: August 2017

Abstract. The usage of unmanned systems for exploring disaster scenarios has become more and more important in recent times as a supporting system for action forces. These systems have to offer a well-balanced relationship between the quality of support and additional workload. Therefore within the joint research project ANKommEn – german acronym for Automated Navigation and Communication for Exploration – a system for exploration of disaster scenarios is build-up using multiple UAV und UGV controlled via a central ground station. The ground station serves as user interface for defining missions and tasks conducted by the unmanned systems, equipped with different environmental sensors like cameras – RGB as well as IR – or LiDAR. Depending on the exploration task results, in form of pictures, 2D stitched orthophoto or LiDAR point clouds will be transmitted via datalinks and displayed online at the ground station or will be processed in short-term after a mission, e.g. 3D photogrammetry. For mission planning and its execution, UAV/UGV monitoring and georeferencing of environmental sensor data, reliable positioning and attitude information is required. This is gathered using an integrated GNSS/IMU positioning system. In order to increase availability of positioning information in GNSS challenging scenarios, a GNSS-Multiconstellation based approach is used, amongst others. The present paper focuses on the overall system design including the ground station and sensor setups on the UAVs and UGVs, the underlying positioning techniques as well as 2D and 3D exploration based on a RGB camera mounted on board the UAV and its evaluation based on real world field tests.
A DISTRIBUTED ONLINE 3D-LIDAR MAPPING SYSTEM
Authors: Schmiemann J. , Harms H. , Schattenberg J. , Becker M. , Batzdorfer S. , Frerichs L.
Published: August 2017

Abstract. In this paper we are presenting work done within the joint development project ANKommEn. It deals with the development of a highly automated robotic system for fast data acquisition in civil disaster scenarios. One of the main requirements is a versatile system, hence the concept embraces a machine cluster consisting of multiple fundamentally different robotic platforms. To cover a large variety of potential deployment scenarios, neither the absolute amount of participants, nor the precise individual layout of each platform shall be restricted within the conceptual design. Thus leading to a variety of special requirements, like onboard and online data processing capabilities for each individual participant and efficient data exchange structures, allowing reliable random data exchange between individual robots. We are demonstrating the functionality and performance by means of a distributed mapping system evaluated with real world data in a challenging urban and rural indoor/outdoor scenarios.
QUALITY ASSESSMENT OF COMBINED IMU/GNSS DATA FOR DIRECT GEOREFERENCING IN THE CONTEXT OF UAV-BASED MAPPING
Authors: Stöcker C. , Nex F. , Koeva M. , Gerke M.
Published: August 2017

Abstract. Within the past years, the development of high-quality Inertial Measurement Units (IMU) and GNSS technology and dedicated RTK (Real Time Kinematic) and PPK (Post-Processing Kinematic) solutions for UAVs promise accurate measurements of the exterior orientation (EO) parameters which allow to georeference the images. Whereas the positive impact of known precise GNSS coordinates of camera positions is already well studied, the influence of the angular observations have not been studied in depth so far. Challenges include accuracies of GNSS/IMU observations, excessive angular motion and time synchronization problems during the flight. Thus, this study assesses the final geometric accuracy using direct georeferencing with high-quality post-processed IMU/GNSS and PPK corrections. A comparison of different data processing scenarios including indirect georeferencing, integrated solutions as well as direct georeferencing provides guidance on the workability of UAV mapping approaches that require a high level of positional accuracy. In the current research the results show, that the use of the post-processed APX-15 GNSS and IMU data was particularly beneficial to enhance the image orientation quality. Horizontal accuracies within the pixel level (2.8 cm) could be achieved. However, it was also shown, that the angular EO parameters are still too inaccurate to be assigned with a high weight during the image orientation process. Furthermore, detailed investigations of the EO parameters unveil that systematic sensor misalignments and offsets of the image block can be reduced by the introduction of four GCPs. In this regard, the use of PPK corrections reduces the time consuming field work to measure high quantities of GCPs and makes large-scale UAV mapping a more feasible solution for practitioners that require high geometric accuracies.
POINT CLOUD ANALYSIS FOR UAV-BORNE LASER SCANNING WITH HORIZONTALLY AND VERTICALLY ORIENTED LINE SCANNERS – CONCEPT AND FIRST RESULTS
Authors: Weinmann M. , Müller M. S. , Hillemann M. , Reydel N. , Hinz S. , Jutzi B.
Published: August 2017

Abstract. In this paper, we focus on UAV-borne laser scanning with the objective of densely sampling object surfaces in the local surrounding of the UAV. In this regard, using a line scanner which scans along the vertical direction and perpendicular to the flight direction results in a point cloud with low point density if the UAV moves fast. Using a line scanner which scans along the horizontal direction only delivers data corresponding to the altitude of the UAV and thus a low scene coverage. For these reasons, we present a concept and a system for UAV-borne laser scanning using multiple line scanners. Our system consists of a quadcopter equipped with horizontally and vertically oriented line scanners. We demonstrate the capabilities of our system by presenting first results obtained for a flight within an outdoor scene. Thereby, we use a downsampling of the original point cloud and different neighborhood types to extract fundamental geometric features which in turn can be used for scene interpretation with respect to linear, planar or volumetric structures.
COMPARISON OF A FIXED-WING AND MULTI-ROTOR UAV FOR ENVIRONMENTAL MAPPING APPLICATIONS: A CASE STUDY
Authors: Boon M. A. , Drijfhout A. P. , Tesfamichael S.
Published: August 2017

Abstract. The advent and evolution of Unmanned Aerial Vehicles (UAVs) and photogrammetric techniques has provided the possibility for on-demand high-resolution environmental mapping. Orthoimages and three dimensional products such as Digital Surface Models (DSMs) are derived from the UAV imagery which is amongst the most important spatial information tools for environmental planning. The two main types of UAVs in the commercial market are fixed-wing and multi-rotor. Both have their advantages and disadvantages including their suitability for certain applications. Fixed-wing UAVs normally have longer flight endurance capabilities while multi-rotors can provide for stable image capturing and easy vertical take-off and landing. Therefore, the objective of this study is to assess the performance of a fixed-wing versus a multi-rotor UAV for environmental mapping applications by conducting a specific case study. The aerial mapping of the Cors-Air model aircraft field which includes a wetland ecosystem was undertaken on the same day with a Skywalker fixed-wing UAV and a Raven X8 multi-rotor UAV equipped with similar sensor specifications (digital RGB camera) under the same weather conditions. We compared the derived datasets by applying the DTMs for basic environmental mapping purposes such as slope and contour mapping including utilising the orthoimages for identification of anthropogenic disturbances. The ground spatial resolution obtained was slightly higher for the multi-rotor probably due to a slower flight speed and more images. The results in terms of the overall precision of the data was noticeably less accurate for the fixed-wing. In contrast, orthoimages derived from the two systems showed small variations. The multi-rotor imagery provided better representation of vegetation although the fixed-wing data was sufficient for the identification of environmental factors such as anthropogenic disturbances. Differences were observed utilising the respective DTMs for the mapping of the wetland slope and contour mapping including the representation of hydrological features within the wetland. Factors such as cost, maintenance and flight time is in favour of the Skywalker fixed-wing. The multi-rotor on the other hand is more favourable in terms of data accuracy including for precision environmental planning purposes although the quality of the data of the fixed-wing is satisfactory for most environmental mapping applications.
TOWARDS A MORE EFFICIENT DETECTION OF EARTHQUAKE INDUCED FAÇADE DAMAGES USING OBLIQUE UAV IMAGERY
Authors: Duarte D. , Nex F. , Kerle N. , Vosselman G.
Published: August 2017

Abstract. Urban search and rescue (USaR) teams require a fast and thorough building damage assessment, to focus their rescue efforts accordingly. Unmanned aerial vehicles (UAV) are able to capture relevant data in a short time frame and survey otherwise inaccessible areas after a disaster, and have thus been identified as useful when coupled with RGB cameras for façade damage detection. Existing literature focuses on the extraction of 3D and/or image features as cues for damage. However, little attention has been given to the efficiency of the proposed methods which hinders its use in an urban search and rescue context. The framework proposed in this paper aims at a more efficient façade damage detection using UAV multi-view imagery. This was achieved directing all damage classification computations only to the image regions containing the façades, hence discarding the irrelevant areas of the acquired images and consequently reducing the time needed for such task. To accomplish this, a three-step approach is proposed: i) building extraction from the sparse point cloud computed from the nadir images collected in an initial flight; ii) use of the latter as proxy for façade location in the oblique images captured in subsequent flights, and iii) selection of the façade image regions to be fed to a damage classification routine. The results show that the proposed framework successfully reduces the extracted façade image regions to be assessed for damage 6 fold, hence increasing the efficiency of subsequent damage detection routines. The framework was tested on a set of UAV multi-view images over a neighborhood of the city of L’Aquila, Italy, affected in 2009 by an earthquake.
Study on organic matter fractions in the surface microlayer in the Baltic Sea by spectrophotometric and spectrofluorometric methods
Authors: Drozdowska Violetta , Wrobel Iwona , Markuszewski Piotr , Makuch Przemysław , Raczkowska Anna , Kowalczuk Piotr
Published: August 2017

Abstract. The fluorescence and absorption measurements of the samples collected from a surface microlayer (SML) and a subsurface layer (SS), at a depth of 1 m, were studied during three research cruises in the Baltic Sea along with hydrophysical studies and meteorological observations. Several absorption (E2 : E3,  S,  SR) and fluorescence (fluorescence intensities at Coble classified peaks: A,  C,  M,  T the ratio M + T∕A + C,  HIX (humification index)) indices of colored and fluorescent dissolved organic matter (CDOM and FDOM) helped to describe the changes in molecular size and weight as well as in composition of organic matter. The investigation allowed the assessment of a decrease in the contribution of two terrestrial components (A and C) with increasing salinity ( ∼  1.64 and  ∼  1.89 % in the SML and  ∼  0.78 and  ∼  0.71 % in the SS, respectively) and an increase in components produced in situ (M and T) with salinity ( ∼  0.52 and  ∼  2.83 % in the SML and  ∼  0.98 and  ∼  1.87 % in the SS, respectively). Hence, a component T reveals the biggest relative changes along the transect from the Vistula River outlet to Gdansk Deep, in both the SML and SS, although an increase was higher in the SML than in the SS ( ∼  18.5 and  ∼  12.3 %, respectively). The ratio E2 : E3 points to greater changes in the molecular weight of CDOM affected by a higher rate of photobleaching in the SML. The HIX index reflects a more advanced stage of humification and condensation processes in the SS. Finally, the results reveal a higher rate of degradation processes occurring in the SML than in the SS. Thus, the specific physical properties of surface active organic molecules (surfactants) may modify, in a specific way, the solar light spectrum entering the sea and a penetration depth of the solar radiation. Research on the influence of surfactants on the physical processes linked to the sea surface becomes an important task, especially in coastal waters and in the vicinity of the river mouths.
CARTAS DO MÉXICO. UM OLHAR ANTROPOLÓGICO SOBRE INTERCULTURALIDADE
Authors: Landa Mariano Báez
Published: August 2017

RESUMOEste trabalho enfoca a relação entre a antropologia audiovisual e acomunicação intercultural, para desenvolver pesquisas sobre tecnologiasdigitais e comunicação intercultural, aplicando etnografias audiovisuaisparticipativas para estimular a produção de jovens pertencentes a segmentos que não são visíveis na sociedade mexicana.Palavras - chave: Antropologia audiovisual. Tecnologias digitais.Comunicación intercultural. Etnografias audiovisuais participativas.
ROTAÇÃO DE PERSPECTIVA: REFLEXÃO SOBRE ENSINO DE ANTROPOLOGIA PARA PROFESSORES INDÍGENAS
Authors: Giraldin Odair
Published: August 2017

RESUMOApresento aqui uma reflexão sobre a prática do antropólogo enquantopesquisador e também como professor, abordando a delicada situação deensinar Antropologia e seus princípios centrais como relativismo, alteridadee o trabalho de campo com observação participante para professoresindígenas de diversos povos Macro-Jê do Brasil Central.Palavras-chave: Ensino. Antropologia. Metodologia.