Hochschule für Architektur, Bau und Geomatik FHNW

Dauerhafte URI für den Bereichhttps://irf.fhnw.ch/handle/11654/6

Listen

Filter

2020 - 202429

Einstellungen

Anfangsdatum: 2020Institut: search.filters.institut.Institut Geomatik

Bereich: Suchergebnisse

Gerade angezeigt 1 - 10 von 29
  • Vorschaubild
    Publikation
    (Near) real-time snow water equivalent observation using GNSS refractometry and RTKLIB
    (MDPI, 2022) Steiner, Ladina; Studemann, Géraldine Laurence; Grimm, David; Marty, Christoph; Leinss, Silvan
    Global navigation satellite system (GNSS) refractometry enables automated and continuous in situ snow water equivalent (SWE) observations. Such accurate and reliable in situ data are needed for calibration and validation of remote sensing data and could enhance snow hydrological monitoring and modeling. In contrast to previous studies which relied on post-processing with the highly sophisticated Bernese GNSS processing software, the feasibility of in situ SWE determination in post-processing and (near) real time using the open-source GNSS processing software RTKLIB and GNSS refractometry based on the biased coordinate Up component is investigated here. Available GNSS observations from a fixed, high-end GNSS refractometry snow monitoring setup in the Swiss Alps are reprocessed for the season 2016/17 to investigate the applicability of RTKLIB in post-processing. A fixed, low-cost setup provides continuous SWE estimates in near real time at a low cost for the complete 2021/22 season. Additionally, a mobile, (near) real-time and low-cost setup was designed and evaluated in March 2020. The fixed and mobile multi-frequency GNSS setups demonstrate the feasibility of (near) real-time SWE estimation using GNSS refractometry. Compared to state-of-the-art manual SWE observations, a mean relative bias below 5% is achieved for (near) real-time and post-processed SWE estimation using RTKLIB
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Open urban and forest datasets from a high-performance mobile mapping backpack. A contribution for advancing the creation of digital city twins
    (International Society of Photogrammetry and Remote Sensing, 2021) Blaser, Stefan; Meyer, Jonas; Nebiker, Stephan
    With this contribution, we describe and publish two high-quality street-level datasets, captured with a portable high-performance Mobile Mapping System (MMS). The datasets will be freely available for scientific use. Both datasets, from a city centre and a forest represent area-wide street-level reality captures which can be used e.g. for establishing cloud-based frameworks for infrastructure management as well as for smart city and forestry applications. The quality of these data sets has been thoroughly evaluated and demonstrated. For example, georeferencing accuracies in the centimetre range using these datasets in combination with image-based georeferencing have been achieved. Both high-quality multi sensor system street-level datasets are suitable for evaluating and improving methods for multiple tasks related to high-precision 3D reality capture and the creation of digital twins. Potential applications range from localization and georeferencing, dense image matching and 3D reconstruction to combined methods such as simultaneous localization and mapping and structure-from-motion as well as classification and scene interpretation. Our dataset is available online at: https://www.fhnw.ch/habg/bimage-datasets
    04B - Beitrag Konferenzschrift
  • Vorschaubild
    Publikation
    AI-based 3D detection of parked vehicles on a mobile mapping platform using edge computing
    (2022) Meyer, Jonas; Blaser, Stefan; Nebiker, Stephan
    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.
    04B - Beitrag Konferenzschrift
  • Vorschaubild
    Publikation
    Image-based orientation determination of mobile sensor platforms
    (International Society of Photogrammetry and Remote Sensing, 2021) Hasler, Oliver; Nebiker, Stephan
    Abstract. Estimating the pose of a mobile robotic platform is a challenging task, especially when the pose needs to be estimated in a global or local reference frame and when the estimation has to be performed while the platform is moving. While the position of a platform can be measured directly via modern tachymetry or with the help of a global positioning service GNSS, the absolute platform orientation is harder to derive. Most often, only the relative orientation is estimated with the help of a sensor mounted on the robotic platform such as an IMU, with one or multiple cameras, with a laser scanner or with a combination of any of those. Then, a sensor fusion of the relative orientation and the absolute position is performed. In this work, an additional approach is presented: first, an image-based relative pose estimation with frames from a panoramic camera using a state-of-the-art visual odometry implementation is performed. Secondly, the position of the platform in a reference system is estimated using motorized tachymetry. Lastly, the absolute orientation is calculated using a visual marker, which is placed in the space, where the robotic platform is moving. The marker can be detected in the camera frame and since the position of this marker is known in the reference system, the absolute pose can be estimated. To improve the absolute pose estimation, a sensor fusion is conducted. Results with a Lego model train as a mobile platform show, that the trajectory of the absolute pose calculated independently with four different markers have a deviation < 0.66 degrees 50% of the time and that the average difference is < 1.17 degrees. The implementation is based on the popular Robotic Operating System ROS.
    04B - Beitrag Konferenzschrift
  • Vorschaubild
    Publikation
    Gaining overview with transient focus+context maps
    (Taylor & Francis, 2021) Hollenstein, Daria; Bleisch, Susanne
    Gaining an overview of large spatial data sets presents a challenge common to various domains. 'Overviewing' spatial data involves viewing different areas of focus and context at different scales and requires access to detail from zoomed-out views. Standard pan and zoom interfaces provide limited support with this. Motivated by the application scenario of flood risk monitoring, we extend pan and zoom affordances with a combination of focus+context techniques and multiple maps to support 'overviewing' spatial data with a graph-like information structure. A combination of transient overlays to preview context-on-demand as well as detail-on-demand with the option to decouple additional maps enables fast navigation through the graph-like information space. User-created and -positioned, resizable multiple maps allow for simultaneous exploration of distant regions at flexible scales. The seamless integration of these concepts and the versatility of its components allow for continuously adaptable, user-defined layouts that support various analysis situations. We present a prototype implementation of this interaction model and illustrate its working in application to a hydrometric network, but we believe the model could be transferred to graph-like data in other domains.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Digital twinning of the built environment. An interdisciplinary topic for innovation in didactics
    (Copernicus, 2020) Wahbeh, Wissam; Kunz, Dominique; Hofmann, Joachim; Bereuter, Pia
    The concept of a Digital Twin (DT) takes an increasingly important role in the construction industry and related research fields. It is a concept associated with Industry 4.0; however, the scientific literature does not provide a unique and clear definition of this concept. This paper aims to analyse the definitions of the digital twin to clarify this concept in the related fields of architecture, engineering and construction (AEC). Moreover, this work proposes and employs the concept of a Digital Twin as an objective for a project-based learning approach in a didactical setting. As an interdisciplinary approach, this work demonstrates the potential impact on the traditional didactical frameworks in the educational domain of construction and its value as an opportunity to introduce interdisciplinary expertise to all students in these fields. This work presents a use case applying the concept at the School of Architecture, Civil Engineering and Geomatics of FHNW.
    04B - Beitrag Konferenzschrift
  • Vorschaubild
    Publikation
    Toward flexible visual analytics augmented through smooth display transitions
    (Elsevier, 2021) Tominski, Christian; Andrienko, Gennady; Andrienko, Natalia; Bleisch, Susanne; Fabrikant, Sara Irina; Mayr, Eva; Miksch, Silvia; Pohl, Margit; Skupin, André
    Visualizing big and complex multivariate data is challenging. To address this challenge, we propose flexible visual analytics (FVA) with the aim to mitigate visual complexity and interaction complexity challenges in visual analytics, while maintaining the strengths of multiple perspectives on the studied data. At the heart of our proposed approach are transitions that fluidly transform data between user-relevant views to offer various perspectives and insights into the data. While smooth display transitions have been already proposed, there has not yet been an interdisciplinary discussion to systematically conceptualize and formalize these ideas. As a call to further action, we argue that future research is necessary to develop a conceptual framework for flexible visual analytics. We discuss preliminary ideas for prioritizing multi-aspect visual representations and multi-aspect transitions between them, and consider the display user for whom such depictions are produced and made available for visual analytics. With this contribution we aim to further facilitate visual analytics on complex data sets for varying data exploration tasks and purposes based on different user characteristics and data use contexts.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Exploratory bivariate and multivariate geovisualizations of a social vulnerability index
    (North American Cartographic Information Society, 2020) Strode, Georgianna; Mesev, Victor; Bleisch, Susanne; Ziewitz, Kathryn; Reed, Fennis; Morgan, John Derek
    In the United States, the Centers for Disease Control and Prevention (CDC) is the national agency that conducts and supports public health research and practice. Among the CDC’s many achievements is the development of a social vulnerability index (SVI) to aid planners and emergency responders when identifying vulnerable segments of the population, especially during natural hazard events. The index includes an overall social vulnerability ranking as well as four individual themes: socioeconomic, household composition & disability, ethnicity & language, and housing & transportation. This makes the SVI dataset multivariate, but it is typically viewed via maps that show one theme at a time. This paper explores a suite of cartographic techniques that can represent the SVI beyond the univariate view. Specifically, we recommend three techniques: (1) bivariate mapping to illustrate overall vulnerability and population density, (2) multivariate mapping using cartographic glyphs to disaggregate levels of the four vulnerability themes, and (3) visual analytics using Euler diagrams to depict overlap between the vulnerability themes. The CDC’s SVI, and by extension, vulnerability indices in other countries, can be viewed in a variety of cartographic forms that illustrate the location of vulnerable groups of society. Viewing data from various perspectives can facilitate the understanding and analysis of the growing amount and complexity of data.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Criticality creates a functional platform for network transitions between internal and external processing modes in the human brain
    (Frontiers Research Foundation, 2021) Kim, Minkyung; Kim, Hyoungkyu; Huang, Zirui; Mashour, George A.; Jordan, Denis; Ilg, Rüdiger; Lee, UnCheol
    Continuous switching between internal and external modes in the brain appears important for generating models of the self and the world. However, how the brain transitions between these two modes remains unknown. We propose that a large synchronization fluctuation of brain networks, emerging only near criticality (i.e., a balanced state between order and disorder), spontaneously creates temporal windows with distinct preferences for integrating the network’s internal information or for processing external stimuli. Using a computational model, electroencephalography (EEG) analysis, and functional magnetic resonance imaging (fMRI) analysis during alterations of consciousness in humans, we report that synchronized and incoherent networks, respectively, bias toward internal and external information with specific network configurations. In the brain network model and EEG-based network, the network preferences are the most prominent at criticality and in conscious states associated with the bandwidth 4−12 Hz, with alternating functional network configurations. However, these network configurations are selectively disrupted in different states of consciousness such as general anesthesia, psychedelic states, minimally conscious states, and unresponsive wakefulness syndrome. The network preference for internal information integration is only significant in conscious states and psychedelic states, but not in other unconscious states, suggesting the importance of internal information integration in maintaining consciousness. The fMRI co-activation pattern analysis shows that functional networks that are sensitive to external stimuli–such as default mode, dorsal attentional, and frontoparietal networks–are activated in incoherent states, while insensitive networks, such as global activation and deactivation networks, are dominated in highly synchronized states. We suggest that criticality produces a functional platform for the brain’s capability for continuous switching between two modes, which is crucial for the emergence of consciousness.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Dynamic patterns of global brain communication differentiate conscious from unconscious patients after severe brain injury
    (Frontiers Research Foundation, 2021) Golkowski, Daniel; Willnecker, Rebecca; Rösler, Jennifer; Ranft, Andreas; Schneider, Gerhard; Jordan, Denis; Ilg, Rüdiger
    The neurophysiology of the subjective sensation of being conscious is elusive; therefore, it remains controversial how consciousness can be recognized in patients who are not responsive but seemingly awake. During general anesthesia, a model for the transition between consciousness and unconsciousness, specific covariance matrices between the activity of brain regions that we call patterns of global brain communication reliably disappear when people lose consciousness. This functional magnetic imaging study investigates how patterns of global brain communication relate to consciousness and unconsciousness in a heterogeneous sample during general anesthesia and after brain injury. First, we describe specific patterns of global brain communication during wakefulness that disappear during propofol and sevoflurane general anesthesia. Second, we search for these patterns in a cohort of unresponsive wakeful patients and unmatched healthy controls in order to evaluate their potential use in clinical practice. We found that patterns of global brain communication characterized by high covariance in sensory and motor areas or low overall covariance and their dynamic change were strictly associated with intact consciousness in this cohort. In addition, we show that the occurrence of these two patterns is significantly related to activity within the frontoparietal network of the brain, a network known to play a crucial role in conscious perception. We propose that this approach potentially recognizes consciousness in the clinical routine setting.
    01A - Beitrag in wissenschaftlicher Zeitschrift