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  • The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

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  • Open Access
    Authors: 
    Zahra Dabiri; Daniel Hölbling; Lorena Abad; Dirk Tiede;
    Publisher: Copernicus GmbH

    Abstract. On July 7, 2018, a large landslide occurred at the eastern slope of the Fagraskógarfjall Mountain in Hítardalur valley in West Iceland. The landslide dammed the river, led to the formation of a lake and, consequently, to a change in the river course. The main focus of this research is to develop a knowledge-based expert system using an object-based image analysis (OBIA) approach for identifying morphology changes caused by the Hítardalur landslide. We use synthetic aperture radar (SAR) and optical remote sensing data, in particular from Sentinel-1/2 for detection of the landslide and its effects on the river system. We extracted and classified the landslide area, the landslide-dammed lake, other lakes and the river course using intensity information from S1 and spectral information from S2 in the object-based framework. Future research will focus on further developing this approach to support mapping and monitoring of the spatio-temporal dynamics of surface morphology in an object-based framework by combining SAR and optical data. The results can reveal details on the applicability of different remote sensing data for the spatio-temporal investigation of landslides, landslide-induced river course changes and lake formation and lead to a better understanding of the impact of large landslides on river systems.

  • Open Access English
    Authors: 
    Isabella Toschi; Pablo Rodríguez-Gonzálvez; Fabio Remondino; S. Minto; S. Orlandini; A. Fuller;

    Abstract. This paper discusses a methodology to evaluate the precision and the accuracy of a commercial Mobile Mapping System (MMS) with advanced statistical methods. So far, the metric potentialities of this emerging mapping technology have been studied in few papers, where generally the assumption that errors follow a normal distribution is made. In fact, this hypothesis should be carefully verified in advance, in order to test how well the Gaussian classic statistics can adapt to datasets that are usually affected by asymmetrical gross errors. The workflow adopted in this study relies on a Gaussian assessment, followed by an outlier filtering process. Finally, non-parametric statistical models are applied, in order to achieve a robust estimation of the error dispersion. Among the different MMSs available on the market, the latest solution provided by RIEGL is here tested, i.e. the VMX-450 Mobile Laser Scanning System. The test-area is the historic city centre of Trento (Italy), selected in order to assess the system performance in dealing with a challenging and historic urban scenario. Reference measures are derived from photogrammetric and Terrestrial Laser Scanning (TLS) surveys. All datasets show a large lack of symmetry that leads to the conclusion that the standard normal parameters are not adequate to assess this type of data. The use of non-normal statistics gives thus a more appropriate description of the data and yields results that meet the quoted a-priori errors.

  • Publication . Article . Other literature type . 2016
    Open Access
    Authors: 
    Thomas Blaschke; Stefan Lang; Dirk Tiede; Manos Papadakis; A. Györi;
    Publisher: Copernicus GmbH

    We introduce a prototypical methodological framework for a place-based GIS-RS system for the spatial delineation of place while incorporating spatial analysis and mapping techniques using methods from different fields such as environmental psychology, geography, and computer science. The methodological lynchpin for this to happen - when aiming to delineate <i>place</i> in terms of objects - is object-based image analysis (OBIA).

  • Open Access English
    Authors: 
    Thomas Blaschke; A. Kovács-Győri;
    Publisher: Copernicus Publications

    Abstract. The 2030 Agenda for Sustainable Development is widely appreciated and increasingly known by a wider public. However, less obvious are the enormous coordination and harmonization efforts to reify these goals into 169 targets and 232 indicators. We exemplarily outline a tangible pathway to address SDG11 and one associated indicator 11.7.1 “Average share of the built-up area of cities that is open space for public use for all, by sex, age and persons with disabilities”. We highlight some specific problems for reporting on indicators related to urban green spaces (UGS) and make suggestions for this indicator by illustrating the potential of Earth Observation data and spatial accessibility analysis.

  • Publication . Other literature type . Article . 2018
    Open Access
    Authors: 
    Ulrich Krispel; Henrik Leander Evers; Martin Tamke; R. Viehauser; Dieter W. Fellner;
    Publisher: Copernicus GmbH
    Project: EC | DURAARK (600908)

    Abstract. Recent trends in 3D scanning are aimed at the fusion of range data and color information from images. The combination of these two outputs allows to extract novel semantic information. The workflow presented in this paper allows to detect objects, such as light switches, that are hard to identify from range data only. In order to detect these elements, we developed a method that utilizes range data and color information from high-resolution panoramic images of indoor scenes, taken at the scanners position. A proxy geometry is derived from the point clouds; orthographic views of the scene are automatically identified from the geometry and an image per view is created via projection. We combine methods of computer vision to train a classifier to detect the objects of interest from these orthographic views. Furthermore, these views can be used for automatic texturing of the proxy geometry.

  • Open Access
    Authors: 
    Stephan Schraml; T. Hinterhofer; Martin Pfennigbauer; Michael Hofstätter;
    Publisher: Copernicus GmbH

    Abstract. In this work we propose an effective radiation source localization device employing a RIEGL VUX-1UAV laser scanner and a highly sensitive Hotzone Technologies gamma radiation probe mounted on a RiCOPTER UAV combined with real-time data processing. The on-board processing and radio communication system integrated within the UAV enables instant and continuously updated access to georeferenced 3D lidar point clouds and gamma radiation intensities. Further processing is done fully automated on the ground. We present a novel combination of both the 3D laser data and the gamma readings within an optimization algorithm that can locate the radioactive source in real-time. Furthermore, this technique can be used to estimate an on-ground radiation intensity, which also considers the actual topography as well as radiation barriers like vegetation or buildings. Results from field tests with real radioactive sources show that single sources can be located precisely, even if the source was largely covered. Outcomes are displayed to the person in charge in an intuitive and user-friendly way, e.g. on a tablet. The whole system is designed to operate in real-time and while the UAV is in the air, resulting in a highly flexible and possibly life-saving asset for firstresponders in time-critical scenarios.

  • Open Access
    Authors: 
    C. Briese; C. Briese; M. Pfennigbauer; A. Ullrich; M. Doneus; M. Doneus;
    Publisher: Copernicus GmbH

    Abstract. Airborne laser scanning (ALS) is a widely used technique for the sampling of the earth's surface. Next to the widely used geometric information current systems provide additional information about the signal strength of each echo. In order to utilize this information, radiometric calibration is essential. As a result physical observables that characterise the backscatter characteristic of the sensed surface are available. Due to the active illumination of the surfaces these values are independent of shadows caused by sunlight and due to the simultaneously recorded 3D information a single-channel true orthophoto can be directly estimated from the ALS data. By the combination of ALS data utilizing different laser wavelengths a multi-wavelength orthophoto of the scene can be generated. This contribution presents, next to the practical calibration workflow, the radiometric calibration results of the archaeological study site Carnuntum (Austria). The area has been surveyed at three different ALS wavelengths within a very short period of time. After the radiometric calibration of each single ALS wavelength (532 nm, 1064 nm and 1550 nm) a multi-channel ALS orthophoto is derived. Subsequently, the radiometric calibration results of the single- and multi-wavelength ALS data are studied in respect to present archaeological features. Finally, these results are compared to the radiometric calibration results of an older ALS data acquisition campaign and to results of a systematic air photo interpretation.

  • Open Access English
    Authors: 
    Omid Ghorbanzadeh; Dirk Tiede; Zahra Dabiri; Martin Sudmanns; Stefan Lang;
    Project: FWF | Geographic Information Sc... (W 1237)

    Abstract. There is a growing use of Earth observation (EO) data for support planning in humanitarian crisis response. Information about number and dynamics of displaced population in camps is essential to humanitarian organizations for decision-making and action planning. Dwelling extraction and categorisation is a challenging task, due to the problems in separating different dwellings under different conditions, with wide range of sizes, colour and complex spatial patterns. Nowadays, so-called deep learning techniques such as deep convolutional neural network (CNN) are used for understanding image content and object recognition. Although recent developments in the field of computer vision have introduced CNN networks as a practical tool also in the field of remote sensing, the training step of these techniques is rather time-consuming and samples for the training process are rarely transferable to other application fields. These techniques also have not been fully explored for mapping camps. Our study analyses the potential of a CNN network for dwelling extraction to be embedded as initial step in a comprehensive object-based image analysis (OBIA) workflow. The results were compared to a semi-automated, i.e. combined knowledge-/sample-based, OBIA classification. The Minawao refugee camp in Cameroon served as a case study due to its well-organised, clearly distinguishable dwelling structure. We use manually delineated objects as initial input for the training samples, while the CNN network is structured with two convolution layers and one max pooling.

  • Open Access
    Authors: 
    Andrea Masiero; Harris Perakis; Jelena Gabela; Charles K. Toth; Vassilis Gikas; Guenther Retscher; Salil Goel; Allison Kealy; Zoltan Koppanyi; W. Blaszczak-Bak; +2 more
    Publisher: Copernicus GmbH

    Abstract. The increasing demand for reliable indoor navigation systems is leading the research community to investigate various approaches to obtain effective solutions usable with mobile devices. Among the recently proposed strategies, Ultra-Wide Band (UWB) positioning systems are worth to be mentioned because of their good performance in a wide range of operating conditions. However, such performance can be significantly degraded by large UWB range errors; mostly, due to non-line-of-sight (NLOS) measurements. This paper considers the integration of UWB with vision to support navigation and mapping applications. In particular, this work compares positioning results obtained with a simultaneous localization and mapping (SLAM) algorithm, exploiting a standard and a Time-of-Flight (ToF) camera, with those obtained with UWB, and then with the integration of UWB and vision. For the latter, a deep learning-based recognition approach was developed to detect UWB devices in camera frames. Such information is both introduced in the navigation algorithm and used to detect NLOS UWB measurements. The integration of this information allowed a 20% positioning error reduction in this case study.

  • Open Access English
    Authors: 
    Viktor Kaufmann; Gernot Seier; Wolfgang Sulzer; Matthias Wecht; Qian Liu; Gerhard Lauk; Michael Maurer;
    Publisher: Copernicus Publications

    Abstract. Rock glaciers are creep phenomena of mountain permafrost. Typically, these landforms look like lava flows from a bird’s eye view. Active rock glaciers move downslope with flow velocities in the range of few centimeters to several meters per year. Thus, large masses of rock and ice can be gradually transported down-valley. In this paper we present a comparative study analyzing surface change for Tschadinhorn rock glacier, a relatively fast moving rock glacier located in the Hohe Tauern Range of the Austrian Alps. Aerial photographs (1954–2017) of both metric (conventional) and non-metric (UAV-based) aerial surveys were compared to derive multi-annual to annual flow vector fields and surface height change. For each time interval given we computed a single representative value for flow velocity and, if applicable, also for area-wide surface height change, i.e. volume change. The velocity graph obtained represents the temporal evolution of the kinematics of the rock glacier with good discrimination. Volume change was difficult to quantify since temporal changes were rather small and close to insignificance. The precision and accuracy of the results obtained were numerically quantified. Our study showed that for the Tschadinhorn rock glacier UAV-based aerial surveys can substitute conventional aerial surveys as carried out by national mapping agencies, such as the Austrian Federal Office of Metrology and Surveying (BEV). Thus, UAV-based aerial surveys can help to bridge the data gap between regular aerial surveys. The high accuracy of the UAV-derived results would even allow intra-annual change detection of flow velocity.

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