TY - JOUR A1 - Rösch, Moritz A1 - Plank, Simon T1 - Detailed mapping of lava and ash deposits at Indonesian volcanoes by means of VHR PlanetScope change detection JF - Remote Sensing N2 - Mapping of lava flows in unvegetated areas of active volcanoes using optical satellite data is challenging due to spectral similarities of volcanic deposits and the surrounding background. Using very high-resolution PlanetScope data, this study introduces a novel object-oriented classification approach for mapping lava flows in both vegetated and unvegetated areas during several eruptive phases of three Indonesian volcanoes (Karangetang 2018/2019, Agung 2017, Krakatau 2018/2019). For this, change detection analysis based on PlanetScope imagery for mapping loss of vegetation due to volcanic activity (e.g., lava flows) is combined with the analysis of changes in texture and brightness, with hydrological runoff modelling and with analysis of thermal anomalies derived from Sentinel-2 or Landsat-8. Qualitative comparison of the mapped lava flows showed good agreement with multispectral false color time series (Sentinel-2 and Landsat-8). Reports of the Global Volcanism Program support the findings, indicating the developed lava mapping approach produces valuable results for monitoring volcanic hazards. Despite the lack of bands in infrared wavelengths, PlanetScope proves beneficial for the assessment of risk and near-real-time monitoring of active volcanoes due to its high spatial (3 m) and temporal resolution (mapping of all subaerial volcanoes on a daily basis). KW - lava KW - volcanoes KW - PlanetScope KW - change detection KW - object-based image analysis Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-262232 SN - 2072-4292 VL - 14 IS - 5 ER - TY - JOUR A1 - Ghazaryan, Gohar A1 - Rienow, Andreas A1 - Oldenburg, Carsten A1 - Thonfeld, Frank A1 - Trampnau, Birte A1 - Sticksel, Sarah A1 - Jürgens, Carsten T1 - Monitoring of urban sprawl and densification processes in Western Germany in the light of SDG indicator 11.3.1 based on an automated retrospective classification approach JF - Remote Sensing N2 - By 2050, two-third of the world’s population will live in cities. In this study, we develop a framework for analyzing urban growth-related imperviousness in North Rhine-Westphalia (NRW) from the 1980s to date using Landsat data. For the baseline 2017-time step, official geodata was extracted to generate labelled data for ten classes, including three classes representing low, middle, and high level of imperviousness. We used the output of the 2017 classification and information based on radiometric bi-temporal change detection for retrospective classification. Besides spectral bands, we calculated several indices and various temporal composites, which were used as an input for Random Forest classification. The results provide information on three imperviousness classes with accuracies exceeding 75%. According to our results, the imperviousness areas grew continuously from 1985 to 2017, with a high imperviousness area growth of more than 167,000 ha, comprising around 30% increase. The information on the expansion of urban areas was integrated with population dynamics data to estimate the progress towards SDG 11. With the intensity analysis and the integration of population data, the spatial heterogeneity of urban expansion and population growth was analysed, showing that the urban expansion rates considerably excelled population growth rates in some regions in NRW. The study highlights the applicability of earth observation data for accurately quantifying spatio-temporal urban dynamics for sustainable urbanization and targeted planning. KW - impervious surface KW - Landsat time series KW - change detection KW - SDG 11.3.1 KW - population change Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-236671 SN - 2072-4292 VL - 13 IS - 9 ER - TY - JOUR A1 - Rieser, Jakob A1 - Veste, Maik A1 - Thiel, Michael A1 - Schönbrodt-Stitt, Sarah T1 - Coverage and Rainfall Response of Biological Soil Crusts Using Multi-Temporal Sentinel-2 Data in a Central European Temperate Dry Acid Grassland JF - Remote Sensing N2 - Biological soil crusts (BSCs) are thin microbiological vegetation layers that naturally develop in unfavorable higher plant conditions (i.e., low precipitation rates and high temperatures) in global drylands. They consist of poikilohydric organisms capable of adjusting their metabolic activities depending on the water availability. However, they, and with them, their ecosystem functions, are endangered by climate change and land-use intensification. Remote sensing (RS)-based studies estimated the BSC cover in global drylands through various multispectral indices, and few of them correlated the BSCs’ activity response to rainfall. However, the allocation of BSCs is not limited to drylands only as there are areas beyond where smaller patches have developed under intense human impact and frequent disturbance. Yet, those areas were not addressed in RS-based studies, raising the question of whether the methods developed in extensive drylands can be transferred easily. Our temperate climate study area, the ‘Lieberoser Heide’ in northeastern Germany, is home to the country’s largest BSC-covered area. We applied a Random Forest (RF) classification model incorporating multispectral Sentinel-2 (S2) data, indices derived from them, and topographic information to spatiotemporally map the BSC cover for the first time in Central Europe. We further monitored the BSC response to rainfall events over a period of around five years (June 2015 to end of December 2020). Therefore, we combined datasets of gridded NDVI as a measure of photosynthetic activity with daily precipitation data and conducted a change detection analysis. With an overall accuracy of 98.9%, our classification proved satisfactory. Detected changes in BSC activity between dry and wet conditions were found to be significant. Our study emphasizes a high transferability of established methods from extensive drylands to BSC-covered areas in the temperate climate. Therefore, we consider our study to provide essential impulses so that RS-based biocrust mapping in the future will be applied beyond the global drylands. KW - biocrusts activity KW - random forest classification KW - rainfall response KW - Sentinel-2 multispectral indices KW - change detection KW - Lieberoser Heide Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-245006 SN - 2072-4292 VL - 13 IS - 16 ER - TY - THES A1 - Schauer Marin Rodrigues, Johannes T1 - Detecting Changes and Finding Collisions in 3D Point Clouds : Data Structures and Algorithms for Post-Processing Large Datasets T1 - Erkennen von Änderungen und Finden von Kollisionen in 3D Punktwolken N2 - Affordable prices for 3D laser range finders and mature software solutions for registering multiple point clouds in a common coordinate system paved the way for new areas of application for 3D point clouds. Nowadays we see 3D laser scanners being used not only by digital surveying experts but also by law enforcement officials, construction workers or archaeologists. Whether the purpose is digitizing factory production lines, preserving historic sites as digital heritage or recording environments for gaming or virtual reality applications -- it is hard to imagine a scenario in which the final point cloud must also contain the points of "moving" objects like factory workers, pedestrians, cars or flocks of birds. For most post-processing tasks, moving objects are undesirable not least because moving objects will appear in scans multiple times or are distorted due to their motion relative to the scanner rotation. The main contributions of this work are two postprocessing steps for already registered 3D point clouds. The first method is a new change detection approach based on a voxel grid which allows partitioning the input points into static and dynamic points using explicit change detection and subsequently remove the latter for a "cleaned" point cloud. The second method uses this cleaned point cloud as input for detecting collisions between points of the environment point cloud and a point cloud of a model that is moved through the scene. Our approach on explicit change detection is compared to the state of the art using multiple datasets including the popular KITTI dataset. We show how our solution achieves similar or better F1-scores than an existing solution while at the same time being faster. To detect collisions we do not produce a mesh but approximate the raw point cloud data by spheres or cylindrical volumes. We show how our data structures allow efficient nearest neighbor queries that make our CPU-only approach comparable to a massively-parallel algorithm running on a GPU. The utilized algorithms and data structures are discussed in detail. All our software is freely available for download under the terms of the GNU General Public license. Most of the datasets used in this thesis are freely available as well. We provide shell scripts that allow one to directly reproduce the quantitative results shown in this thesis for easy verification of our findings. N2 - Kostengünstige Laserscanner und ausgereifte Softwarelösungen um mehrere Punktwolken in einem gemeinsamen Koordinatensystem zu registrieren, ermöglichen neue Einsatzzwecke für 3D Punktwolken. Heutzutage werden 3D Laserscanner nicht nur von Expert*innen auf dem Gebiet der Vermessung genutzt sondern auch von Polizist*innen, Bauarbeiter*innen oder Archäolog*innen. Unabhängig davon ob der Einsatzzweck die Digitalisierung von Fabrikanlagen, der Erhalt von historischen Stätten als digitaler Nachlass oder die Erfassung einer Umgebung für Virtual Reality Anwendungen ist - es ist schwer ein Szenario zu finden in welchem die finale Punktwolke auch Punkte von sich bewegenden Objekten enthalten soll, wie zum Beispiel Fabrikarbeiter*innen, Passant*innen, Autos oder einen Schwarm Vögel. In den meisten Bearbeitungsschritten sind bewegte Objekte unerwünscht und das nicht nur weil sie in mehrmals im gleichen Scan vorkommen oder auf Grund ihrer Bewegung relativ zur Scanner Rotation verzerrt gemessen werden. Der Hauptbeitrag dieser Arbeit sind zwei Nachverarbeitungsschritte für registrierte 3D Punktwolken. Die erste Methode ist ein neuer Ansatz zur Änderungserkennung basierend auf einem Voxelgitter, welche es erlaubt die Eingabepunktwolke in statische und dynamische Punkte zu segmentieren. Die zweite Methode nutzt die gesäuberte Punktwolke als Eingabe um Kollisionen zwischen Punkten der Umgebung mit der Punktwolke eines Modells welches durch die Szene bewegt wird zu erkennen. Unser Vorgehen für explizite Änderungserkennung wird mit dem aktuellen Stand der Technik unter Verwendung verschiedener Datensätze verglichen, inklusive dem populären KITTI Datensatz. Wir zeigen, dass unsere Lösung ähnliche oder bessere F1-Werte als existierende Lösungen erreicht und gleichzeitig schneller ist. Um Kollisionen zu finden erstellen wir kein Polygonnetz sondern approximieren die Punkte mit Kugeln oder zylindrischen Volumen. Wir zeigen wie unsere Datenstrukturen effiziente Nächste-Nachbarn-Suche erlaubt, die unsere CPU Lösung mit einer massiv-parallelen Lösung für die GPU vergleichbar macht. Die benutzten Algorithmen und Datenstrukturen werden im Detail diskutiert. Die komplette Software ist frei verfügbar unter den Bedingungen der GNU General Public license. Die meisten unserer Datensätze die in dieser Arbeit verwendet wurden stehen ebenfalls zum freien Download zur Verfügung. Wir publizieren ebenfalls all unsere Shell-Skripte mit denen die quantitativen Ergebnisse die in dieser Arbeit gezeigt werden reproduziert und verifiziert werden können. T3 - Forschungsberichte in der Robotik = Research Notes in Robotics - 20 KW - Punktwolke KW - Änderungserkennung KW - 3d point clouds KW - collision detection KW - change detection KW - k-d tree KW - Dreidimensionale Bildverarbeitung Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-214285 SN - 978-3-945459-32-4 ER - TY - JOUR A1 - Berti, Stefan A1 - Vossel, Gerhard A1 - Gamer, Matthias T1 - The orienting response in healthy aging: Novelty P3 indicates no general decline but reduced efficacy for fast stimulation rates JF - Frontiers in Psychology N2 - Automatic orienting to unexpected changes in the environment is a pre-requisite for adaptive behavior. One prominent mechanism of automatic attentional control is the Orienting Response (OR). Despite the fundamental significance of the OR in everyday life, only little is known about how the OR is affected by healthy aging. We tested this question in two age groups (19–38 and 55–72 years) and measured skin-conductance responses (SCRs) and event-related brain potentials (ERPs) to novels (i.e., short environmental sounds presented only once in the experiment; 10% of the trials) compared to standard sounds (600 Hz sinusoidal tones with 200 ms duration; 90% of the trials). Novel and standard stimuli were presented in four conditions differing in the inter-stimulus interval (ISI) with a mean ISI of either 10, 3, 1, or 0.5 s (blocked presentation). In both age groups, pronounced SCRs were elicited by novels in the 10 s ISI condition, suggesting the elicitation of stable ORs. These effects were accompanied by pronounced N1 and frontal P3 amplitudes in the ERP, suggesting that automatic novelty processing and orientation of attention are effective in both age groups. Furthermore, the SCR and ERP effects declined with decreasing ISI length. In addition, differences between the two groups were observable with the fastest presentation rates (i.e., 1 and 0.5 s ISI length). The most prominent difference was a shift of the peak of the frontal positivity from around 300 to 200 ms in the 19–38 years group while in the 55–72 years group the amplitude of the frontal P3 decreased linearly with decreasing ISI length. Taken together, this pattern of results does not suggest a general decline in processing efficacy with healthy aging. At least with very rare changes (here, the novels in the 10 s ISI condition) the OR is as effective in healthy older adults as in younger adults. With faster presentation rates, however, the efficacy of the OR decreases. This seems to result in a switch from novelty to deviant processing in younger adults, but less so in the group of older adults. KW - psychology KW - attention KW - change detection KW - auditory system KW - novelty processing KW - event-related potential (ERP) KW - P300 KW - skin conductance response (SCR) Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-173651 VL - 8 ER - TY - JOUR A1 - Clauss, Kersten A1 - Yan, Huimin A1 - Kuenzer, Claudia T1 - Mapping Paddy Rice in China in 2002, 2005, 2010 and 2014 with MODIS Time Series JF - Remote Sensing N2 - Rice is an important food crop and a large producer of green-house relevant methane. Accurate and timely maps of paddy fields are most important in the context of food security and greenhouse gas emission modelling. During their life-cycle, rice plants undergo a phenological development that influences their interaction with waves in the visible light and infrared spectrum. Rice growth has a distinctive signature in time series of remotely-sensed data. We used time series of MODIS (Moderate Resolution Imaging Spectroradiometer) products MOD13Q1 and MYD13Q1 and a one-class support vector machine to detect these signatures and classify paddy rice areas in continental China. Based on these classifications, we present a novel product for continental China that shows rice areas for the years 2002, 2005, 2010 and 2014 at 250-m resolution. Our classification has an overall accuracy of 0.90 and a kappa coefficient of 0.77 compared to our own reference dataset for 2014 and correlates highly with rice area statistics from China’s Statistical Yearbooks (R2 of 0.92 for 2010, 0.92 for 2005 and 0.90 for 2002). Moderate resolution time series analysis allows accurate and timely mapping of rice paddies over large areas with diverse cropping schemes. KW - agriculture KW - rice KW - China KW - MODIS KW - time series KW - SVM KW - OCSVM KW - change detection Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-180557 VL - 8 IS - 5 ER - TY - JOUR A1 - Ullmann, Tobias A1 - Büdel, Christian A1 - Baumhauer, Roland A1 - Padashi, Majid T1 - Sentinel-1 SAR Data Revealing Fluvial Morphodynamics in Damghan (Iran): Amplitude and Coherence Change Detection JF - International Journal of Earth Science and Geophysics N2 - The Sentinel-1 Satellite (S-1) of ESA's Copernicus Mission delivers freely available C-Band Synthetic Aperture Radar (SAR) data that are suited for interferometric applications (InSAR). The high geometric resolution of less than fifteen meter and the large coverage offered by the Interferometric Wide Swath mode (IW) point to new perspectives on the comprehension and understanding of surface changes, the quantification and monitoring of dynamic processes, especially in arid regions. The contribution shows the application of S-1 intensities and InSAR coherences in time series analysis for the delineation of changes related to fluvial morphodynamics in Damghan, Iran. The investigations were carried out for the period from April to October 2015 and exhibit the potential of the S-1 data for the identification of surface disturbances, mass movements and fluvial channel activity in the surroundings of the Damghan Playa. The Amplitude Change Detection highlighted extensive material movement and accumulation - up to sizes of more than 4,000 m in width - in the east of the Playa via changes in intensity. Further, the Coherence Change Detection technique was capable to indicate small-scale channel activity of the drainage system that was neither recognizable in the S-1 intensity nor the multispectral Landsat-8 data. The run off caused a decorrelation of the SAR signals and a drop in coherence. Seen from a morphodynamic point of view, the results indicated a highly dynamic system and complex tempo-spatial patterns were observed that will be subject of future analysis. Additionally, the study revealed the necessity to collect independent reference data on fluvial activity in order to train and adjust the change detector. KW - SAR KW - InSAR KW - coherence KW - Iran KW - Sentinel-1 KW - radar KW - geomorphology KW - change detection Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-147863 VL - 2 IS - 1 ER -