Artikel

Mohr, S.; Ehret, U.; Kunz, M.; Ludwig, P.; Caldas-Alvarez, A.; Daniell, J. E.; Ehmele, F.; Feldmann, H.; Franca, M. J.; Gattke, C.; Hundhausen, M.; Knippertz, P.; Küpfer, K.; Mühr, B.; Pinto, J. G.; Quinting, J.; Schäfer, A. M.; Scheibel, M.; Seidel, F.; Wisotzky, C. (2023). A multi-disciplinary analysis of the exceptional flood event of July 2021 in central Europe. Part 1: Event description and analysis. Natural hazards and earth system sciences, 23 (2), 525–551. doi:10.5194/nhess-23-525-2023  

Schäfer, A. M.; Daniell, J. E.; Mühr, B.; Skapski, J.-U.; Mohr, S.; Kunz, M. (2023). CEDIM Forensic Disaster Analysis Group (FDA): Kahramanmaraş & Elbistan Erdbeben Türkei. doi:10.5445/IR/1000155770  

Andersen, H.; Cermak, J.; Zipfel, L.; Myers, T. A. (2022). Attribution of Observed Recent Decrease in Low Clouds Over the Northeastern Pacific to Cloud‐Controlling Factors. Geophysical research letters, 49 (3), e2021GL096498. doi:10.1029/2021GL096498  

Bertels, M.; Jutzi, B.; Ulrich, M. (2022). Automatic Real-Time Pose Estimation of Machinery from Images. Sensors, 22 (7), 2627. doi:10.3390/s22072627  

Bluhm, R.; Polonik, P.; Hemes, K. S.; Sanford, L. C.; Benz, S. A.; Levy, M. C.; Ricke, K. L.; Burney, J. A. (2022). Disparate air pollution reductions during California’s COVID-19 economic shutdown. Nature Sustainability, 5 (6), 509–517. doi:10.1038/s41893-022-00856-1 

Boé, J.; Mass, A.; Deman, J. (2022). A simple hybrid statistical–dynamical downscaling method for emulating regional climate models over Western Europe. Evaluation, application, and role of added value?. Climate Dynamics. doi:10.1007/s00382-022-06552-2 

Boldt, M.; Thiele, A.; Schulz, K. (2022). Training data generation for machine learning using GPR images. Proceedings Volume 12268, Earth Resources and Environmental Remote Sensing/GIS Applications XIII, Ed.: K. Schulz, 122680F, SPIE. doi:10.1117/12.2635714 

Bradley, P. E.; Jahn, M. W. (2022). On the Behaviour of p-Adic Scaled Space Filling Curve Indices for High-Dimensional Data. The computer journal, 65 (2), 310–330. doi:10.1093/comjnl/bxaa036 

Christensen, M. W.; Gettelman, A.; Cermak, J.; Dagan, G.; Diamond, M.; Douglas, A.; Feingold, G.; Glassmeier, F.; Goren, T.; Grosvenor, D. P.; Gryspeerdt, E.; Kahn, R.; Li, Z.; Ma, P.-L.; Malavelle, F.; McCoy, I. L.; McCoy, D. T.; McFarquhar, G.; Mülmenstädt, J.; Pal, S.; Possner, A.; Povey, A.; Quaas, J.; Rosenfeld, D.; Schmidt, A.; Schrödner, R.; Sorooshian, A.; Stier, P.; Toll, V.; Watson-Parris, D.; Wood, R.; Yang, M.; Yuan, T. (2022). Opportunistic experiments to constrain aerosol effective radiative forcing. Atmospheric chemistry and physics, 22 (1), 641–674. doi:10.5194/acp-22-641-2022  

Döring, A.; Vogelbacher, M.; Schneider, O.; Müller, J.; Hinz, S.; Matthes, J. (2022). Ratio-based features for bridge damage detection based on displacement influence line and curvature influence line. Bridge Safety, Maintenance, Management, Life-Cycle, Resilience and Sustainability, CRC Press. 

Dörr, N.; Schenk, A.; Hinz, S. (2022). On the Relevance of Temporary Persistent Scatterers for Long-Term PS-InSAR Monitoring. EUSAR 2022 ; 14th European Conference on Synthetic Aperture Radar, 541–546, VDE Verlag. 

Dörr, N.; Schenk, A.; Hinz, S. (2022). Systematic Analysis of Initial Settlement of new Constructions in the Mekong Delta by Coherence Change Detection of Temporary Persistent Scatterers. IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur, 17-22 July 2022, 1111–1114, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IGARSS46834.2022.9883381 

Dörr, N.; Schenk, A.; Hinz, S. (2022). Fully Integrated Temporary Persistent Scatterer Interferometry. IEEE Transactions on Geoscience and Remote Sensing, 60, Art no. 4412815. doi:10.1109/TGRS.2022.3200155 

Evers, M.; Thiele, A.; Hammer, H.; Hinz, S. (2022). The Filling Process of an Embankment Dam Monitored with PSI. IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, 1640–1643, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IGARSS46834.2022.9883950 

Fersch, B.; Kamm, B.; Shehaj, E.; Wagner, A.; Yuan, P.; Möller, G.; Schenk, A.; Geiger, A.; Hinz, S.; Kutterer, H.; Kunstmann, H. (2022). A comprehensive high resolution data collection for tropospheric water vapor assessment for the Upper Rhine Graben, Germany. doi:10.1594/PANGAEA.936447 

Fersch, B.; Wagner, A.; Kamm, B.; Shehaj, E.; Schenk, A.; Yuan, P.; Geiger, A.; Moeller, G.; Heck, B.; Hinz, S.; Kutterer, H.; Kunstmann, H. (2022). Tropospheric water vapor: a comprehensive high-resolution data collection for the transnational Upper Rhine Graben region. Earth System Science Data, 14 (12), 5287–5307. doi:10.5194/essd-14-5287-2022  

Florath, J.; Keller, S. (2022). Supervised Machine Learning Approaches on Multispectral Remote Sensing Data for a Combined Detection of Fire and Burned Area. Remote sensing, 14 (3), Art.-Nr.: 657. doi:10.3390/rs14030657  

Florath, J.; Keller, S.; Abarca-del-Rio, R.; Hinz, S.; Staub, G.; Weinmann, M. (2022). Glacier Monitoring Based on Multi-Spectral and Multi-Temporal Satellite Data: A Case Study for Classification with Respect to Different Snow and Ice Types. Remote sensing, 14 (4), Article no: 845. doi:10.3390/rs14040845  

Franke, S.; Jansen, D.; Binder, T.; Paden, J. D.; Dörr, N.; Gerber, T. A.; Miller, H.; Dahl-Jensen, D.; Helm, V.; Steinhage, D.; Weikusat, I.; Wilhelms, F.; Eisen, O. (2022). Airborne ultra-wideband radar sounding over the shear margins and along flow lines at the onset region of the Northeast Greenland Ice Stream. Earth system science data, 14 (2), 763–779. doi:10.5194/essd-14-763-2022  

Fuchs, J.; Andersen, H.; Cermak, J.; Pauli, E.; Roebeling, R. (2022). High-resolution satellite-based cloud detection for the analysis of land surface effects on boundary layer clouds. Atmospheric Measurement Techniques, 15 (14), 4257–4270. doi:10.5194/amt-15-4257-2022  

Haitz, D.; Hübner, P.; Ulrich, M.; Landgraf, S.; Jutzi, B. (2022). Semantic segmentation with small training datasets: A case study for corrosion detection on the surface of industrial objects. Forum Bildverarbeitung 2022. Ed.: T. Längle; M. Heizmann, 73–85, KIT Scientific Publishing.  

Haitz, D.; Jutzi, B.; Hübner, P.; Ulrich, M. (2022). Corrosion detection for industrial objects: from multi-sensor system to 5D feature space. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIII-B1-2022, 143–150. doi:10.5194/isprs-archives-XLIII-B1-2022-143-2022  

Hammer, H.; Kuny, S.; Schmitz, S.; Thielea, A. (2022). Training a CNN with Simulated Data for ATR – Lessons Learned. EUSAR 2022; 14th European Conference on Synthetic Aperture Radar, 1–6, Institute of Electrical and Electronics Engineers (IEEE). 

Heizmann, M.; Braun, A.; Glitzner, M.; Günther, M.; Hasna, G.; Klüver, C.; Krooß, J.; Marquardt, E.; Overdick, M.; Ulrich, M. (2022). Implementing machine learning: chances and challenges. Automatisierungstechnik, 70 (1), 90–101. doi:10.1515/auto-2021-0149 

Hübner, P.; Wursthorn, S.; Weinmann, M. (2022). Normal classification of 3D occupancy grids for voxel-based indoor reconstruction from point clouds. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, V-4-2022, 121–128. doi:10.5194/isprs-annals-V-4-2022-121-2022  

Jahani, B.; Andersen, H.; Calbó, J.; González, J.-A.; Cermak, J. (2022). Longwave radiative effect of the cloud–aerosol transition zone based on CERES observations. Atmospheric chemistry and physics, 22 (2), 1483–1494. doi:10.5194/acp-22-1483-2022  

Jahn, M. W.; Bradley, P. E. (2022). Topological Access Methods for Spatial and Spatiotemporal Data. ISPRS International Journal of Geo-Information, 11 (10), 533. doi:10.3390/ijgi11100533  

Jahn, M. W.; Bradley, P. E. (2022). A Robustness Study for the Extraction of Watertight Volumetric Models from Boundary Representation Data. ISPRS International Journal of Geo-Information, 11 (4), Artk.Nr.: 224. doi:10.3390/ijgi11040224  

Kühnlein, L.; Keller, S. (2022). Evaluation of Transformers and Convolutional Neural Networks for High-Dimensional Hyperspectral Soil Texture Classification. 2022 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/WHISPERS56178.2022.9955087 

Landgraf, S.; Kühnlein, L.; Hillemann, M.; Hoyer, M.; Keller, S.; Ulrich, M. (2022). Evaluation of self-supervised learning approaches for semantic segmentation of industrial burner flames. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIII-B2-2022, 601–607. doi:10.5194/isprs-archives-XLIII-B2-2022-601-2022  

Li, J.; Weinmann, M.; Sun, X.; Diao, W.; Feng, Y.; Hinz, S.; Fu, K. (2022). VD-LAB: A view-decoupled network with local-global aggregation bridge for airborne laser scanning point cloud classification. ISPRS Journal of Photogrammetry and Remote Sensing, 186, 19–33. doi:10.1016/j.isprsjprs.2022.01.012 

Ludwig, P.; Ehmele, F.; Franca, M. J.; Mohr, S.; Caldas-Alvarez, A.; Daniell, J. E.; Ehret, U.; Feldmann, H.; Hundhausen, M.; Knippertz, P.; Küpfer, K.; Kunz, M.; Mühr, B.; Pinto, J. G.; Quinting, J.; Schäfer, A. M.; Seidel, F.; Wisotzky, C. (2022). A multi-disciplinary analysis of the exceptional flood event of July 2021 in central Europe. Part 2: Historical context and relation to climate change. Natural hazards and earth system sciences discussions. doi:10.5194/nhess-2022-225  

Mao, Y.; Chen, K.; Diao, W.; Sun, X.; Lu, X.; Fu, K.; Weinmann, M. (2022). Beyond single receptive field: A receptive field fusion-and-stratification network for airborne laser scanning point cloud classification. ISPRS Journal of Photogrammetry and Remote Sensing, 188, 45–61. doi:10.1016/j.isprsjprs.2022.03.019 

Mayer, M.; Przybilla, M.; Kamm, B.; Krüger, S.; Rabold, J. (2022). Training of Ethical Competencies in Bsc Degree Programs – a Digital, Multi-Perspective, and Student-Centered Approach. XXVII FIG Congress: Volunteering for the future - Geospatial excellence for a better living. 

Michel, C.; Keller, S. (2022). Determining and Investigating the Variability of Bridges’ Natural Frequencies with Ground-Based Radar. Applied Sciences, 12 (11), Artk.Nr.: 5354. doi:10.3390/app12115354  

Palka, J.; Lenz, A.; Middelmann, W.; Weinmann, M. (2022). Evaluation of the NEON dataset for the automatic detection of treetops and delineation of tree crowns in American and German mixed forests. Proceedings Volume 12268, Earth Resources and Environmental Remote Sensing/GIS Applications XIII, Art.-Nr.: 1226807, SPIE. doi:10.1117/12.2643747 

Pauli, E.; Cermak, J.; Andersen, H. (2022). A satellite‐based climatology of fog and low stratus formation and dissipation times in central Europe. Quarterly Journal of the Royal Meteorological Society, 148 (744), 1439–1454. doi:10.1002/qj.4272  

Pauli, E.; Cermak, J.; Teuling, A. J. (2022). Enhanced nighttime fog and low stratus occurrence over the Landes forest, France. Geophysical research letters, 49 (5), e2021GL097058. doi:10.1029/2021GL097058  

Rebmeister, M.; Auer, S.; Schenk, A.; Hinz, S. (2022). Geocoding of ground-based SAR data for infrastructure objects using the Maximum A Posteriori estimation and ray-tracing. ISPRS Journal of Photogrammetry and Remote Sensing, 189, 110–127. doi:10.1016/j.isprsjprs.2022.04.030 

Schäfer, A.; Daniell, J. E.; Skapski, J.-U.; Mohr, S. (2022). CEDIM Forensic Disaster Analysis Group (FDA) "Volcano & Tsunami Hunga Tonga" Report No. 1. doi:10.5445/IR/1000142014  

Schill, F.; Michel, C.; Firus, A. (2022). Contactless Deformation Monitoring of Bridges with Spatio-Temporal Resolution: Profile Scanning and Microwave Interferometry. Sensors, 22 (23), Art.-Nr.: 9562. doi:10.3390/s22239562  

Schmitz, S.; Thiele, A.; Hammer, H.; Hinz, S. (2022). Impact of highly varying incidence angle on the feature space of polsar images. EUSAR 2022; 14th European Conference on Synthetic Aperture Radar, 360–365, Institute of Electrical and Electronics Engineers (IEEE). 

Steger, C.; Ulrich, M. (2022). A Multi-view Camera Model for Line-Scan Cameras with Telecentric Lenses. Journal of Mathematical Imaging and Vision, 64, 105–130. doi:10.1007/s10851-021-01055-x  

Sun, X.; Wang, P.; Yan, Z.; Xu, F.; Wang, R.; Diao, W.; Chen, J.; Li, J.; Feng, Y.; Xu, T.; Weinmann, M.; Hinz, S.; Wang, C.; Fu, K. (2022). FAIR1M: A benchmark dataset for fine-grained object recognition in high-resolution remote sensing imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 184, 116–130. doi:10.1016/j.isprsjprs.2021.12.004 

Wursthorn, K.; Hillemann, M.; Ulrich, M. (2022). Comparison of uncertainty quantification methods for CNN-based regression. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIII-B2-2022, 721–728. doi:10.5194/isprs-archives-XLIII-B2-2022-721-2022  

Yang, Y.; Cermak, J.; Yang, K.; Pauli, E.; Chen, Y. (2022). Land Use and Land Cover Influence on Sentinel-2 Aerosol Optical Depth below City Scales over Beijing. Remote Sensing, 14 (18), Art.-Nr.: 4677. doi:10.3390/rs14184677  

Zipfel, L.; Andersen, H.; Cermak, J. (2022). Machine-Learning Based Analysis of Liquid Water Path Adjustments to Aerosol Perturbations in Marine Boundary Layer Clouds Using Satellite Observations. Atmosphere, 13 (4), Art.-Nr.: 586. doi:10.3390/atmos13040586  

Zube, A.; Kleiser, D.; Albrecht, A.; Woock, P.; Emter, T.; Ruf, B.; Tchouchenkov, I.; Buller, A.; Wagner, B.; Baatar, G.; Petereit, J. (2022). Autonomously mapping shallow water environments under and above the water surface [Autonome Kartierung von Flachwasserumgebungen unter und über der Wasseroberflache]. at - Automatisierungstechnik, 70 (5), 482–495. doi:10.1515/auto-2021-0145 

Andersen, H.; Cermak, J.; Stirnberg, R.; Fuchs, J.; Kim, M.; Pauli, E. (2021). Assessment of COVID-19 effects on satellite-observed aerosol loading over China with machine learning. Tellus / B, 73 (1), 1–13. doi:10.1080/16000889.2021.1971925  

Arnold, M.; Hoyer, M.; Keller, S. (2021). Convolutional Neural Networks for Detecting Bridge Crossing Events with Ground-Based Interferometric Radar Data. ISPRS annals, V-1-2021, 31–38. doi:10.5194/isprs-annals-V-1-2021-31-2021  

Benz, S. A.; Davis, S. J.; Burney, J. A. (2021). Drivers and projections of global surface temperature anomalies at the local scale. Environmental Research Letters, 16 (6), Article no: 064093. doi:10.1088/1748-9326/ac0661  

Benz, S. A.; Burney, J. A. (2021). Widespread Race and Class Disparities in Surface Urban Heat Extremes Across the United States. Earth’s Future, 9 (7), e2021EF002016. doi:10.1029/2021EF002016  

Bulatov, D.; Stütz, D.; Hacker, J.; Weinmann, M. (2021). Classification of airborne 3D point clouds regarding separation of vegetation in complex environments. Applied Optics, 60 (22), F6-F20. doi:10.1364/AO.422973 

Döring, A.; Waibel, P.; Matthes, J.; Scherer, O.; Keller, H. B.; Keller, S.; Müller, J.; Schneider, O. (2021). Ratio-based features for data-driven bridge monitoring and damage detection. Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations. Ed.: H. Yokota, 2532–2541, CRC Press. doi:10.1201/9780429279119-346 

Dörr, N.; Schenk, A.; Hinz, S. (2021). Analysis of Heterogeneous PS-InSAR Derived Subsidence Rates Using Categorized GIS Objects - A Case Study in the Mekong Delta. 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium, 11-16 July 2021, 2655–2658, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IGARSS47720.2021.9553297 

Dubois, C.; Jutzi, B.; Olijslagers, M.; Pathe, C.; Schmullius, C.; Stelmaszczuk-Górska, M. A.; Vandenbroucke, D.; Weinmann, M. (2021). Knowledge and skills related to active optical sensors in the body of knowledge for earth observation and geoinformation (EO4GEO BOK). ISPRS annals, V-5-2021, 9–16. doi:10.5194/isprs-annals-V-5-2021-9-2021  

Erdnüß, B. (2021). A review of the one-parameter division undistortion model. Volume V-1-2021, 2021 | XXIV ISPRS Congress Imaging today, foreseeing tomorrow, Commission I: 2021 edition, 5-9 July 2021. Ed.: N. Paparoditis, 89–96, International Society for Photogrammetry and Remote Sensing (ISPRS). doi:10.5194/isprs-annals-V-1-2021-89-2021  

Evers, M.; Thiele, A.; Hammer, H.; Cadario, E.; Schulz, K.; Hinz, S. (2021). Concept to analyze the displacement time series of individual persistent scatterers. XXIV ISPRS Congress (2021 edition). Ed.: N. Paparoditis, 147–154, International Society for Photogrammetry and Remote Sensing (ISPRS). doi:10.5194/isprs-archives-XLIII-B3-2021-147-2021  

Florath, J.; Keller, S.; Staub, G.; Weinmann, M. (2021). Optical Remote Sensing for Glacier Monitoring with Respect to Different Snow and Ice Types: A Case Study for the Southern Patagonian Icefield. 11th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 24–26 March 2021, Article no: 33, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/WHISPERS52202.2021.9484055 

Guth, J.; Keller, S.; Hinz, S.; Winter, S. (2021). Towards detecting, characterizing and rating of road class errors in crowd-sourced road network databases. Journal of spatial information science, 22, 31. doi:10.5311/JOSIS.2021.22.677  

Hammer, H.; Lorenz, F.; Cadario, E.; Kuny, S.; Thiele, A. (2021). Enhancement of coherence images for coherent change detection. 13th European Conference on Synthetic Aperture Radar, EUSAR 2021: Online ; 29 March 2021 through 1 April 2021, 881–886, Institute of Electrical and Electronics Engineers (IEEE). 

Hammer, H.; Kuny, S.; Thiele, A. (2021). Enhancing coherence images for coherent change detection: An example on vehicle tracks in airborne sar images. Remote Sensing, 13 (24), 5010. doi:10.3390/rs13245010  

Hermann, M.; Ruf, B.; Weinmann, M. (2021). Real-Time Dense 3D Reconstruction from Monocular Video Data Captured by Low-Cost UAVS. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIII-B2-2021, 361–368. doi:10.5194/isprs-archives-XLIII-B2-2021-361-2021  

Hermann, M.; Pollok, T.; Brommer, D.; Zahn, D. (2021). IVS3D: An Open Source Framework for Intelligent Video Sampling and Preprocessing to Facilitate 3D Reconstruction. 

Hermann, M.; Pollok, T.; Brommer, D.; Zahn, D. (2021). IVS3D: An Open Source Framework for Intelligent Video Sampling and Preprocessing to Facilitate 3D Reconstruction. Advances in Visual Computing: 16th International Symposium, ISVC 2021, Virtual Event, October 4-6, 2021, Proceedings, Part I. Ed.: G. Bebis, 441–454, Springer Verlag. doi:10.1007/978-3-030-90439-5_35 

Hinz, S.; Feitosa, R. Q.; Weinmann, M.; Jutzi, B. (2021). PREFACE: TECHNICAL COMMISSION I. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIII-B1-2021, 7. doi:10.5194/isprs-archives-XLIII-B1-2021-7-2021  

Hinz, S.; Feitosa, R. Q.; Weinmann, M.; Jutzi, B. (2021). Preface: Technical Commission I. ISPRS annals, V-1-2021, 7. doi:10.5194/isprs-annals-V-1-2021-7-2021  

Hübner, P.; Weinmann, M.; Wursthorn, S.; Hinz, S. (2021). Pose Normalization of Indoor Mapping Datasets Partially Compliant with the Manhattan World Assumption. Remote sensing, 13 (23), 4765. doi:10.3390/rs13234765  

Hübner, P.; Weinmann, M.; Wursthorn, S.; Hinz, S. (2021). Automatic voxel-based 3D indoor reconstruction and room partitioning from triangle meshes. ISPRS journal of photogrammetry and remote sensing, 181, 254–278. doi:10.1016/j.isprsjprs.2021.07.002 

Jahn, M. W.; Bradley, P. E. (2021). Computing watertight volumetric models from boundary representations to ensure consistent topological operations. ISPRS annals, VIII-4/W2-2021, 21–28. doi:10.5194/isprs-annals-VIII-4-W2-2021-21-2021  

Jijón-Palma, M. E.; Kern, J.; Amisse, C.; Centeno, J. A. S. (2021). Improving stacked-autoencoders with 1D convolutional-nets for hyperspectral image land-cover classification. Journal of applied remote sensing, 15 (2), Artikel-Nr.: 026506. doi:10.1117/1.JRS.15.026506 

Kattenborn, T.; Leitloff, J.; Schiefer, F.; Hinz, S. (2021). Review on Convolutional Neural Networks (CNN) in vegetation remote sensing. ISPRS journal of photogrammetry and remote sensing, 173, 24–49. doi:10.1016/j.isprsjprs.2020.12.010  

Kern, J. (2021, März 18). UAS-gestützte Detektion von infrastrukturrelevanten Georisiken - AuDeRi - UAS Datensätze. doi:10.5445/IR/1000130454 

Krüger, S.; Mayer, M. (2021). Nachwuchs-Forum "Wie entsteht Berufsethik? - Ein empirischer Antwortversuch". Mitteilungen und Veröffentlichungen aus den Themenbereichen Geodäsie, Geoinformation und Landmanagement, (2), 23–26. 

Kuny, S.; Hammer, H.; Schulz, K. (2021). On the classifier performance for simulation based debris detection in sar imagery. Volume XLIII-B1-2021, XXIV ISPRS Congress Imaging today, foreseeing tomorrow, Commission I: 2021 edition, 5–9 July 2021. Ed.: N. Paparoditis, 45–50, International Society for Photogrammetry and Remote Sensing (ISPRS). doi:10.5194/isprs-archives-XLIII-B1-2021-45-2021  

Leeuw, G. de; A, R. van der; Bai, J.; Xue, Y.; Varotsos, C.; Li, Z.; Fan, C.; Chen, X.; Christodoulakis, I.; Ding, J.; Hou, X.; Kouremadas, G.; Li, D.; Wang, J.; Zara, M.; Zhang, K.; Zhang, Y. (2021). Air Quality over China. Remote sensing, 13 (17), Art.-Nr.: 3542. doi:10.3390/rs13173542  

Li, J.; Weinmann, M.; Sun, X.; Diao, W.; Feng, Y.; Fu, K. (2021). Random Topology and Random Multiscale Mapping: An Automated Design of Multiscale and Lightweight Neural Network for Remote-Sensing Image Recognition. IEEE Transactions on Geoscience and Remote Sensing, 60, Art.Nr. 5610917. doi:10.1109/TGRS.2021.3102988 

Ma, J.; Zhou, J.; Liu, S.; Göttsche, F.-M.; Zhang, X.; Wang, S.; Li, M. (2021). Continuous evaluation of the spatial representativeness of land surface temperature validation sites. Remote sensing of environment, 265, Article no: 112669. doi:10.1016/j.rse.2021.112669 

Maier, P.; Keller, S.; Hinz, S. (2021). Deep Learning with WASI Simulation Data for Estimating Chlorophyll a Concentration of Inland Water Bodies. Remote sensing, 13 (4), 718. doi:10.3390/rs13040718  

Michel, C.; Keller, S. (2021). Introducing a non-invasive monitoring approach for bridge infrastructure with ground-based interferometric radar. 13th European Conference on Synthetic Aperture Radar, EUSAR 2021: Online ; 29 March 2021 through 1 April 2021, 1073–1077, Institute of Electrical and Electronics Engineers (IEEE). 

Michel, C.; Keller, S. (2021). Advancing Ground-Based Radar Processing for Bridge Infrastructure Monitoring. Sensors, 21 (6), 2172. doi:10.3390/s21062172  

Pauli, E.; Cermak, J.; Andersen, H. (2021, Dezember 20). Satellite-based fog and low stratus cloud formation and dissipation times data set. doi:10.5445/IR/1000141293 

Rabold, J.; Heublein, M.; Mayer, M. (2021). Beteiligung von Studierenden bei der Weiterentwicklung des Lehr-Lernsystems. Die Hochschullehre, (6), 520–528. doi:10.3278/HSL2041W  

Rebmeister, M.; Schenk, A.; Bradley, P. E.; Dörr, N.; Hinz, S. (2021). OCLeaS – A tomographic PSI Algorithm using Orthogonal Matching Pursuit and Complex Least Squares. Procedia computer science, 181, 220–230. doi:10.1016/j.procs.2021.01.143  

Ruf, B.; Mohrs, J.; Weinmann, M.; Hinz, S.; Beyerer, J. (2021). ReS²tAC—UAV-borne real-time SGM stereo optimized for embedded ARM and CUDA devices. Sensors, 21 (11), Article: 3938. doi:10.3390/s21113938  

Schenkel, F.; Hinz, S.; Middelmann, W. (2021). Style transfer-based domain adaptation for vegetation segmentation with optical imagery. Applied optics, 60 (22), F109-F117. doi:10.1364/AO.423910 

Schmitz, S.; Weidner, U.; Hammer, H.; Thiele, A. (2021). Evaluating uniform manifold approximation and projection for dimension reduction and visualization of polinsar features. Volume V-1-2021, 2021 | XXIV ISPRS Congress Imaging today, foreseeing tomorrow, Commission I: 2021 edition, 5-9 July 2021. Ed.: N. Paparoditis, 39–46, International Society for Photogrammetry and Remote Sensing (ISPRS). doi:10.5194/isprs-annals-V-1-2021-39-2021  

Schmitz, S.; Wortmeyer, E.; Thiele, A.; Dirks, H.; Wurpts, A. (2021). Detection of Mussel Beds Using Airborne Polarimetric SAR Data. IGARSS 2021 – 2021 IEEE International Geoscience and Remote Sensing Symposium: Proceedings ; 12–16 July 2021, Virtual Symposium, Brussels, Belgium, 7501–7504, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IGARSS47720.2021.9553437 

Schneider, B.; Wortmeyer, E.; Schmitz, S.; Thiele, A.; Havel, P.; Dirks, H. (2021). Evaluating different water-land-boundary approximations to improve sar-derived digital elevation models. L. F. Y. M. Y. H. S. F. R. Q. W. M. J. B. Paparoditis N. Mallet C. (Hrsg.), Volume XLIII-B1-2021, XXIV ISPRS Congress Imaging today, foreseeing tomorrow, Commission I: 2021 edition, 5–9 July 2021. Ed.: N. Paparoditis, 51–56, International Society for Photogrammetry and Remote Sensing (ISPRS). doi:10.5194/isprs-archives-XLIII-B1-2021-51-2021  

Sefrin, O.; Riese, F. M.; Keller, S. (2021). Deep Learning for Land Cover Change Detection. Remote sensing, 13 (1), Article no: 78. doi:10.3390/rs13010078  

Steger, C.; Ulrich, M. (2021). A Camera Model for Line-Scan Cameras with Telecentric Lenses. International journal of computer vision, 129, 80–99. doi:10.1007/s11263-020-01358-3  

Stirnberg, R.; Cermak, J.; Kotthaus, S.; Haeffelin, M.; Andersen, H.; Fuchs, J.; Kim, M.; Petit, J.-E.; Favez, O. (2021). Meteorology-driven variability of air pollution (PM₁) revealed with explainable machine learning. Atmospheric chemistry and physics, 21 (5), 3919–3948. doi:10.5194/acp-21-3919-2021  

Sun, X.; Wang, P.; Yan, Z.; Diao, W.; Lu, X.; Yang, Z.; Zhang, Y.; Xiang, D.; Yan, C.; Guo, J.; Dang, B.; Wei, W.; Xu, F.; Wang, C.; Hansch, R.; Weinmann, M.; Yokoya, N.; Fu, K. (2021). Automated High-resolution Earth Observation Image Interpretation: Outcome of the 2020 Gaofen Challenge. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14. doi:10.1109/JSTARS.2021.3106941  

Sun, X.; Wang, P.; Yan, Z.; Xu, F.; Wang, R.; Diao, W.; Chen, J.; Li, J.; Feng, Y.; Xu, T.; Weinmann, M.; Hinz, S.; Wang, C.; Fu, K. (2021). FAIR1M: A benchmark dataset for fine-grained object recognition in high-resolution remote sensing imagery. doi:10.48550/arXiv.2103.05569 

Ulrich, M.; Hillemann, M. (2021). Generic Hand–Eye Calibration of Uncertain Robots. IEEE International Conference on Robotics and Automation (ICRA), 30 May-5 June 2021, 11060–11066, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICRA48506.2021.9560823 

Vey, S.; Al-Halbouni, D.; Haghighi, M. H.; Alshawaf, F.; Vüllers, J.; Güntner, A.; Dick, G.; Ramatschi, M.; Teatini, P.; Wickert, J.; Weber, M. (2021). Delayed subsidence of the Dead Sea shore due to hydro-meteorological changes. Scientific Reports, 11 (1), 13518. doi:10.1038/s41598-021-91949-y  

Weinmann, M.; Wursthorn, S.; Weinmann, M.; Hübner, P. (2021). Efficient 3D Mapping and Modelling of Indoor Scenes with the Microsoft HoloLens: A Survey. Journal of photogrammetry, remote sensing and geoinformation science, 89, 319–333. doi:10.1007/s41064-021-00163-y  

Wit, K. de; Lexmond, B. R.; Stouthamer, E.; Neussner, O.; Dörr, N.; Schenk, A.; Minderhoud, P. S. J. (2021). Identifying Causes of Urban Differential Subsidence in the Vietnamese Mekong Delta by Combining InSAR and Field Observations. Remote sensing, 13 (2), Art.-Nr. 189. doi:10.3390/rs13020189  

Yang, Y.; Chen, Y.; Yang, K.; Cermak, J.; Chen, Y. (2021). High-resolution aerosol retrieval over urban areas using sentinel-2 data. Atmospheric research, 264, Art.-Nr.: 105829. doi:10.1016/j.atmosres.2021.105829 

Andersen, H.; Cermak, J.; Fuchs, J.; Knippertz, P.; Gaetani, M.; Quinting, J.; Sippel, S.; Vogt, R. (2020). Synoptic-scale controls of fog and low-cloud variability in the Namib Desert. Atmospheric chemistry and physics, 20 (6), 3415–3438. doi:10.5194/acp-20-3415-2020  

Arnold, M.; Keller, S. (2020). Detection and classification of bridge crossing Events with ground-based interferometric radar data and machine learning approaches. ISPRS annals, V-1-2020, 109–116. doi:10.5194/isprs-annals-V-1-2020-109-2020  

Bradley, P. E. (2020). Generalised Diffusion on Moduli Spaces of p-Adic Mumford Curves. P-adic numbers, ultrametric analysis, and applications, 12 (2), 73–89. doi:10.1134/S2070046620020016 

Breunig, M.; Bradley, P. E.; Jahn, M.; Kuper, P.; Mazroob, N.; Rösch, N.; Al-Doori, M.; Stefanakis, E.; Jadidi, M. (2020). Geospatial Data Management Research: Progress and Future Directions. ISPRS International Journal of Geo-Information, 9 (2), 95. doi:10.3390/ijgi9020095  

Bulatov, D.; Stütz, D.; Lucks, L.; Weinmann, M. (2020). Superpoints in RANSAC planes: A new approach for ground surface extraction exemplified on point classification and context-aware reconstruction. Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP. Ed.: K. Bouatouch, 25–37, SciTePress. doi:10.5220/0008895600250037 

Bulatov, D.; Burkard, E.; Ilehag, R.; Kottler, B.; Helmholz, P. (2020). From multi-sensor aerial data to thermal and infrared simulation of semantic 3D models: Towards identification of urban heat islands. Infrared physics & technology, 105, Art. Nr.: 103233. doi:10.1016/j.infrared.2020.103233 

Erdnuess, B. (2020). Proper synchronization of geospatial metadata in motion imagery and its evaluation. Geospatial Informatics X 2020; None; United States; 27 April 2020 through 8 May 2020, Art. Nr.: 113980C, SPIE. doi:10.1117/12.2558696 

Erdnüß, B.; Müller, T. (2020). Leistungsstarke und effiziente Bildinterpolation. Forum Bildverarbeitung 2020. Ed.: T. Längle ; M. Heizmann, 253–265, KIT Scientific Publishing.  

Evers, M.; Kyriou, A.; Thiele, A.; Hammer, H.; Nikolakopoulos, K.; Schulz, K. (2020). How to set up a dam monitoring system with PSInSAR and GPS. Earth Resources and Environmental Remote Sensing/GIS Applications XI. Ed.: K. Schulz, Art.-Nr.: 115340L, SPIE. doi:10.1117/12.2573880 

Evers, M.; Hammer, H.; Thiele, A.; Schulz, K. (2020). Strategies for PS processing of large sentinel-1 datasets. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLIII-B1-2020, 2020, XXIV ISPRS Congress (2020 edition). Ed.: N. Paparoditis, 99–106, ISPRS. doi:10.5194/isprs-archives-XLIII-B1-2020-99-2020  

Franke, S.; Jansen, D.; Binder, T.; Dörr, N.; Helm, V.; Paden, J.; Steinhage, D.; Eisen, O. (2020). Bed topography and subglacial landforms in the onset region of the Northeast Greenland Ice Stream. Annals of Glaciology, 61 (81), 143–153. doi:10.1017/aog.2020.12  

Guth, J.; Wursthorn, S.; Keller, S. (2020). Multi-Parameter Estimation of Average Speed in Road Networks Using Fuzzy Control. ISPRS International Journal of Geo-Information, 9 (1), Article No.55. doi:10.3390/ijgi9010055  

Heizmann, M.; Braun, A.; Hüttel, M.; Klüver, C.; Marquardt, E.; Overdick, M.; Ulrich, M. (2020). Artificial intelligence with neural networks in optical measurement and inspection systems. Automatisierungstechnik, 68 (6), 477–487. doi:10.1515/auto-2020-0006 

Hermann, M.; Ruf, B.; Weinmann, M.; Hinz, S. (2020). Self-Supervised Learning for Monocular Depth Estimation from Aerial Imagery. ISPRS annals, V-2-2020, 357–364. doi:10.5194/isprs-annals-V-2-2020-357-2020  

Heublein, M.; Bradley, P. E.; Hinz, S. (2020). Observing geometry effects on a Global Navigation Satellite System (GNSS)-based water vapor tomography solved by least squares and by compressive sensing. Annales geophysicae, 38 (1), 179–189. doi:10.5194/angeo-38-179-2020  

Hinz, S.; Feitosa, R. Q.; Weinmann, M.; Jutzi, B. (2020). PREFACE: TECHNICAL COMMISSION I. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 43 (B1), 7. doi:10.5194/isprs-archives-XLIII-B1-2020-7-2020  

Hinz, S.; Feitosa, R. Q.; Weinmann, M.; Jutzi, B. (2020). Preface: Technical Commission I. ISPRS annals, 5 (1), 7. doi:10.5194/isprs-annals-V-1-2020-7-2020  

Hübner, P.; Clintworth, K.; Liu, Q.; Weinmann, M.; Wursthorn, S. (2020). Evaluation of HoloLens Tracking and Depth Sensing for Indoor Mapping Applications. Sensors, 20 (4), 1021. doi:10.3390/s20041021  

Hübner, P.; Weinmann, M.; Wursthorn, S. (2020). Voxel-Based Indoor Reconstruction from HoloLens Triangle Meshes. ISPRS annals, V-4-2020, 79–86. doi:10.5194/isprs-annals-V-4-2020-79-2020  

Ilehag, R.; Leitloff, J.; Weinmann, M.; Schenk, A. (2020). Urban Material Classification Using Spectral and Textural Features Retrieved from Autoencoders. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume V-1-2020, 2020, XXIV ISPRS Congress (2020 edition). Ed.: N. Paparoditis, 25–32, ISPRS. doi:10.5194/isprs-annals-V-1-2020-25-2020  

Keller, S.; Gabriel, R.; Guth, J. (2020). Machine Learning Framework for the Estimation of Average Speed in Rural Road Networks with OpenStreetMap Data. ISPRS International Journal of Geo-Information, 9 (11), Art.-Nr.: 638. doi:10.3390/ijgi9110638  

Keller, S.; Michel, C.; Schneider, O.; Müller, J.; Arnold, M.; Döring, A.; Hoyer, M.; Hinz, S.; Keller, H. B. (2020). Überwachung von Brückeninfrastrukturen : Neuer Ansatz von konventionellen und berührungslosen Sensoren. Brückenbau, (3), 22–29. 

Keller, S.; Riese, F. M.; Allroggen, N.; Jackisch, C. (2020, Mai). HydReSGeo: Field experiment dataset of surface-sub-surface infiltration dynamics acquired by hydrological, remote sensing, and geophysical measurement techniques. doi:10.5880/fidgeo.2020.015 

Kim, M.; Kim, H.-C.; Im, J.; Lee, S.; Han, H. (2020). Object-based landfast sea ice detection over West Antarctica using time series ALOS PALSAR data. Remote sensing of environment, 242, 111782. doi:10.1016/j.rse.2020.111782 

Kim, M.; Cermak, J.; Andersen, H.; Fuchs, J.; Stirnberg, R. (2020). A New Satellite-Based Retrieval of Low-Cloud Liquid-Water Path Using Machine Learning and Meteosat SEVIRI Data. Remote sensing, 12 (21), Article: 3475. doi:10.3390/rs12213475  

Kubisch, S.; Guth, J.; Keller, S.; Bull, M. T.; Keller, L.; Braun, A. C. (2020). The contribution of tsunami evacuation analysis to evacuation planning in Chile: Applying a multi-perspective research design. International journal of disaster risk reduction, 45, Article No.101462. doi:10.1016/j.ijdrr.2019.101462  

Maier, P. M.; Keller, S. (2020). SpecWa: Spectral remote sensing data and chlorophyll a values of inland waters. doi:10.5880/fidgeo.2020.036 

Mayer, M.; Rabold, J.; Raible, B.; Muhler, M.; Krüger, S. (2020). Forum für Lehre 2019 am KIT: Geodäsie und Geoinformatik : Ein interdisziplinäres Berufsfeld mit hoher gesellschaftlicher Relevanz. Mitteilungen und Veröffentlichungen aus den Themenbereichen Geodäsie, Geoinformation und Landmanagement, (1), 62–67. 

Pauli, E.; Andersen, H.; Bendix, J.; Cermak, J.; Egli, S. (2020). Determinants of fog and low stratus occurrence in continental central Europe – a quantitative satellite-based evaluation. Journal of hydrology, 591, Art.-Nr.: 125451. doi:10.1016/j.jhydrol.2020.125451 

Riese, F. M. (2020). LUCAS Soil Texture Processing Scripts. doi:10.5281/zenodo.3871431 

Riese, F. M. (2020). Processing Scripts of the ALPACA Dataset. doi:10.5281/zenodo.3871459 

Riese, F. M. (2020, März). Hyperspectral Processing Scripts for the HydReSGeo Dataset 1.0.0. doi:10.5281/zenodo.3706418 

Riese, F. M.; Keller, S.; Hinz, S. (2020). Supervised and Semi-Supervised Self-Organizing Maps for Regression and Classification Focusing on Hyperspectral Data. Remote sensing, 12 (1), Art. Nr.: 7. doi:10.3390/rs12010007  

Riese, F. M.; Schroers, S.; Wienhöfer, J.; Keller, S. (2020, April 9). Aerial Peruvian Andes Campaign (ALPACA) Dataset 2019. doi:10.5445/IR/1000118082 

Schmitt, A.; Wendleder, A.; Kleynmans, R.; Hell, M.; Roth, A.; Hinz, S. (2020). Multi-source and multi-temporal image fusion on hypercomplex bases. Remote sensing, 12 (6), 943. doi:10.3390/rs12060943  

Schmitz, S.; Weinmann, M.; Thiele, A. (2020). Incorporating interferometric coherence into lulc classification of airborne polsar-images using fully convolutional networks. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLIII-B1-2020, 2020, XXIV ISPRS Congress (2020 edition). Ed.: N. Paparoditis, 115–122, ISPRS. doi:10.5194/isprs-archives-XLIII-B1-2020-115-2020  

Sefrin, O.; Riese, F. M.; Keller, S. (2020). Code for Deep Learning for Land Cover Change Detection 1.0.1. doi:10.5281/zenodo.4289079 

Shatnawi, N.; Weidner, U.; Hinz, S. (2020). Monitoring Urban Expansion as a Result of Refugee Fluxes in North Jordan Using Remote Sensing Techniques. Journal of urban planning and development, 146 (3), Art.-Nr.: 04020026. doi:10.1061/(ASCE)UP.1943-5444.0000584 

Stirnberg, R.; Cermak, J.; Fuchs, J.; Andersen, H. (2020). Mapping and Understanding Patterns of Air Quality Using Satellite Data and Machine Learning. Journal of geophysical research / D, 125 (4), Art.e2019JD031380. doi:10.1029/2019JD031380  

Wagner, P.; Riese, F. M.; Keller, S. (2020). CAOS Sentinel-2 Pipeline in Python. doi:10.5281/zenodo.3879622 

Weinmann, M.; Jäger, M. A.; Wursthorn, S.; Jutzi, B.; Weinmann, M.; Hübner, P. (2020). 3D Indoor Mapping with the Microsoft HoloLens: Qualitative and Quantitative Evaluation by Means of Geometric Features. ISPRS annals, V-1-2020, 165–172. doi:10.5194/isprs-annals-V-1-2020-165-2020  

Westerhuis, S.; Fuhrer, O.; Cermak, J.; Eugster, W. (2020). Identifying the key challenges for fog and low stratus forecasting in complex terrain. Quarterly journal of the Royal Meteorological Society, 146 (732), 3347–3367. doi:10.1002/qj.3849 

Woollam, J.; Rietbrock, A.; Leitloff, J.; Hinz, S. (2020). HEX: Hyperbolic Event eXtractor, a Seismic Phase Associator for Highly Active Seismic Regions. Seismological research letters, 91 (5), 2769–2778. doi:10.1785/0220200037 

Adler, B.; Babić, K.; Kalthoff, N.; Lohou, F.; Lothon, M.; Dione, C.; Pedruzo-Bagazgoitia, X.; Andersen, H. (2019). Nocturnal low-level clouds in the atmospheric boundary layer over southern West Africa: an observation-based analysis of conditions and processes. Atmospheric chemistry and physics, 19 (1), 663–681. doi:10.5194/acp-19-663-2019  

Andersen, H.; Cermak, J.; Solodovnik, I.; Lelli, L.; Vogt, R. (2019). Spatiotemporal dynamics of fog and low clouds in the Namib unveiled with ground- and space-based observations. Atmospheric chemistry and physics, 19 (7), 4383–4392. doi:10.5194/acp-19-4383-2019  

Babić, K.; Adler, B.; Kalthoff, N.; Andersen, H.; Dione, C.; Lohou, F.; Lothon, M.; Pedruzo-Bagazgoitia, X. (2019). The observed diurnal cycle of low-level stratus clouds over southern West Africa: a case study. Atmospheric chemistry and physics, 19 (2), 1281–1299. doi:10.5194/acp-19-1281-2019  

Benz, S.; Park, H.; Li, J.; Crawl, D.; Block, J.; Nguyen, M.; Altintas, I. (2019). Understanding a Rapidly Expanding Refugee Camp Using Convolutional Neural Networks and Satellite Imagery. 15th International Conference on eScience (eScience), 243–251, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/eScience.2019.00034 

Boldt, M.; Thiele, A.; Schulz, K.; Meyer, F. J.; Hinz, S. (2019). Practical approach for synthetic aperture radar change analysis in urban environments. Journal of applied remote sensing, 13 (03), Article: 0345281. doi:10.1117/1.JRS.13.034528  

Bradley, P. E. (2019). Methodology for the sequence analysis of building stocks. Building research and information, 47 (2), 141–155. doi:10.1080/09613218.2018.1380343 

Bradley, P. E. (2019). On the Logistic Behaviour of the Topological Ultrametricity of Data. Journal of classification, 36 (2), 266–276. 

Bradley, P. E.; Behnisch, M. (2019). Heavy-tailed distributions for building stock data. Environment and planning / B, 46 (7), 1281–1296. doi:10.1177/2399808318794499 

Erdnüß, B. (2019). Calibration and synchronization of geospatial metadata for aerial sensor systems. Signal Processing, Sensor/Information Fusion, and Target Recognition XXVII. Ed.: I. Kadar, Art.-Nr.: 1101819, Society of Photo-optical Instrumentation Engineers (SPIE). doi:10.1117/12.2518905 

Fuchs, S.; Hilgert, S.; Sotiri, K.; Wagner, A.; Ishikawa, M.; Kern, J.; Jirka, S.; Klassen, I.; Krumm, J.; Malewski, C.; Rohr, H.; Pakzad, K. (2019). Sustainable management of reservoirs - defining minimum data needs and model complexity. GRoW- Water as a Global Resource, Status Seminar 2019, Frankfurt. MuDak-WRM: Multidisciplinary data acquisition as key for a globally applicable water resource management, 12–15, adelphi. 

Giovanella, A.; Bradley, P. E.; Wursthorn, S. (2019). Evaluation of Topological Consistency in CityGML. ISPRS International Journal of Geo-Information, 8 (6), Article: 278. doi:10.3390/ijgi8060278  

Guth, J.; Wursthorn, S.; Braun, A. C.; Keller, S. (2019). Development of a generic concept to analyze the accessibility of emergency facilities in critical road infrastructure for disaster scenarios: exemplary application for the 2017 wildfires in Chile and Portugal. Natural hazards, 97 (3), 979–999. doi:10.1007/s11069-019-03672-7 

Hillemann, M.; Meidow, J.; Jutzi, B. (2019). Impact of different trajectories on extrinsic self-calibration for vehicle-based mobile laser scanning systems. The international archives of photogrammetry, remote sensing and spatial information sciences, XLII-2/W16, 119–125. doi:10.5194/isprs-archives-XLII-2-W16-119-2019  

Hillemann, M.; Weinmann, M.; Mueller, M. S.; Jutzi, B. (2019). Automatic Extrinsic Self-Calibration of Mobile Mapping Systems Based on Geometric 3D Features. Remote sensing, 11 (16), Article: 1955. doi:10.3390/rs11161955  

Hübner, P.; Landgraf, S.; Weinmann, M.; Wursthorn, S. (2019). Evaluation of the Microsoft HoloLens for the Mapping of Indoor Building Environments. 39. Wissenschaftlich-Technische Jahrestagung der DGPF - Dreiländertagung OVG – DGPF – SGPF - Photogrammetrie - Fernerkundung - Geoinformation, Wien, 20 - 22. Februar 2019. Ed. T. B. Kersten, 44–53, Deutsche Gesellschaft für Photogrammetrie. 

Ilehag, R.; Schenk, A.; Huang, Y.; Hinz, S. (2019). KLUM: An urban VNIR and SWIR spectral library consisting of building materials. Remote sensing, 11 (18), Article: 2149. doi:10.3390/rs11182149  

JET Contributors; Eriksson, J.; Hellesen, C.; Binda, F.; Cecconello, M.; Conroy, S.; Ericsson, G.; Giacomelli, L.; Gorini, G.; Hjalmarsson, A.; Kiptily, V. G.; Mantsinen, M.; Nocente, M.; Sahlberg, A.; Salewski, M.; Sharapov, S.; Tardocchi, M. (2019). Measuring fast ions in fusion plasmas with neutron diagnostics at JET. Plasma physics and controlled fusion, 61 (1), Art. Nr.: 014027. doi:10.1088/1361-6587/aad8a6 

JET Contributors; Fitzgerald, M.; Buchanan, J.; Sharapov, S. E.; Kiptily, V. G.; Sertoli, M.; Szepesi, G.; Boom, J.; Akers, R. J.; King, D.; Abduallev, S.; Abhangi, M.; Abreu, P.; Afzal, M.; Aggarwal, K. M.; Ahlgren, T.; Ahn, J. H.; Aho-Mantila, L.; Aiba, N.; Airila, M.; Albanese, R.; Aldred, V.; Alegre, D.; Alessi, E.; Aleynikov, P.; Alfier, A.; Alkseev, A.; Allinson, M.; Alper, B.; Alves, E.; Ambrosino, G.; Ambrosino, R.; Amicucci, L.; Amosov, V.; Sunden, E. A.; Angelone, M.; Anghel, M.; Angioni, C.; Appel, L.; Appelbee, C.; Arena, P.; Ariola, M.; Arnichand, H.; Arshad, S.; Ash, A.; Ashikawa, N.; Aslanyan, V.; Asunta, O.; Auriemma, F.; Austin, Y.; Avotina, L.; Axton, M. D.; Ayres, C.; Bacharis, M.; Baciero, A.; Baiao, D.; Bailey, S.; Baker, A.; Balboa, I.; Balden, M.; Balshaw, N.; Bament, R.; Banks, J. W.; Baranov, Y. F.; Barnard, M. A.; Barnes, D.; Barnes, M.; Barnsley, R.; Wiechec, A. B.; Orte, L. B.; Baruzzo, M.; Basiuk, V.; Bassan, M.; Bastow, R.; Batista, A.; Batistoni, P.; Baughan, R.; Bauvir, B.; Baylor, L.; Bazylev, B.; Beal, J.; Beaumont, P. S.; Beckers, M.; Beckett, B.; Becoulet, A.; Bekris, N.; Beldishevski, M.; Bell, K.; Belli, F.; Bellinger, M.; Belonohy, E.; Ben Ayed, N.; Benterman, N. A.; Bergsaker, H.; Bernardo, J.; Bernert, M.; Berry, M.; Bertalot, L.; Besliu, C.; Beurskens, M.; Bieg, B.; Bielecki, J.; Biewer, T.; Bigi, M.; Bilkova, P.; Binda, F.; Bisoffi, A.; Bizarro, J. P. S.; Bjorkas, C.; Blackburn, J.; Blackman, K.; Blackman, T. R.; Blanchard, P.; Blatchford, P.; Bobkov, V.; Boboc, A.; Bodnar, G.; Bogar, O.; Bolshakova, I.; Bolzonella, T.; Bonanomi, N.; Bonelli, F.; Boom, J.; Booth, J.; Borba, D.; Borodin, D.; Borodkina, I.; Botrugno, A.; Bottereau, C.; Boulting, P.; Bourdelle, C.; Bowden, M.; Bower, C.; Bowman, C.; Boyce, T.; Boyd, C.; Boyer, H. J.; Bradshaw, J. M. A.; Braic, V.; Bravanec, R.; Breizman, B.; Bremond, S.; Brennan, P. D.; Breton, S.; Brett, A.; Brezinsek, S.; Bright, M. D. J.; Brix, M.; Broeckx, W.; Brombin, M.; Broslawski, A.; Brown, D. P. D.; Brown, M.; Bruno, E.; Bucalossi, J.; Buch, J.; Buchanan, J.; Buckley, M. A.; Budny, R.; Bufferand, H.; Bulman, M.; Bulmer, N.; Bunting, P.; Buratti, P.; Burckhart, A.; Buscarino, A.; Busse, A.; Butler, N. K.; Bykov, I.; Byrne, J.; Cahyna, P.; Calabro, G.; Calvo, I.; Camenen, Y.; Camp, P.; Campling, D. C.; Cane, J.; Cannas, B.; Capel, A. J.; Card, P. J.; Cardinali, A.; Carman, P.; Carr, M.; Carralero, D.; Carraro, L.; Carvalho, B. B.; Carvalho, I.; Carvalho, P.; Casson, F. J.; Castaldo, C.; Catarino, N.; Caumont, J.; Causa, F.; Cavazzana, R.; Cave-Ayland, K.; Cavinato, M.; Cecconello, M.; Ceccuzzi, S.; Cecil, E.; Cenedese, A.; Cesario, R.; Challis, C. D.; Chandler, M.; Chandra, D.; Chang, C. S.; Chankin, A.; Chapman, I. T.; Chapman, S. 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Nuclear fusion, 59 (1), Art. Nr.: 016004. doi:10.1088/1741-4326/aaea1e 

JET Contributors; Frassinetti, L.; Dunne, M. G.; Sheikh, U.; Saarelma, S.; Roach, C. M.; Stefanikova, E.; Maggi, C.; Horvath, L.; Pamela, S.; Luna, E. de la; Wolfrum, E.; Bernert, M.; Blanchard, P.; Labit, B.; Merle, A.; Guimarais, L.; Coda, S.; Meyer, H.; Hillesheim, J. C.; Abduallev, S.; Abhangi, M.; Abreu, P.; Afzal, M.; Aggarwal, K. M.; Ahlgren, T.; Ahn, J. H.; Aho-Mantila, L.; Aiba, N.; Airila, M.; Albanese, R.; Aldred, V.; Alegre, D.; Alessi, E.; Aleynikov, P.; Alfier, A.; Alkseev, A.; Allinson, M.; Alper, B.; Alves, E.; Ambrosino, G.; Ambrosino, R.; Amicucci, L.; Amosov, V.; Sunden, E. A.; Angelone, M.; Anghel, M.; Angioni, C.; Appel, L.; Appelbee, C.; Arena, P.; Ariola, M.; Arnichand, H.; Arshad, S.; Ash, A.; Ashikawa, N.; Aslanyan, V.; Asunta, O.; Auriemma, F.; Austin, Y.; Avotina, L.; Axton, M. D.; Ayres, C.; Bacharis, M.; Baciero, A.; Baiao, D.; Bailey, S.; Baker, A.; Balboa, I.; Balden, M.; Balshaw, N.; Bament, R.; Banks, J. W.; Baranov, Y. F.; Barnard, M. A.; Barnes, D.; Barnes, M.; Barnsley, R.; Wiechec, A. B.; Orte, L. B.; Baruzzo, M.; Basiuk, V.; Bassan, M.; Bastow, R.; Batista, A.; Batistoni, P.; Baughan, R.; Bauvir, B.; Baylor, L.; Bazylev, B.; Beal, J.; Beaumont, P. S.; Beckers, M.; Beckett, B.; Becoulet, A.; Bekris, N.; Beldishevski, M.; Bell, K.; Belli, F.; Bellinger, M.; Belonohy, E.; Ben Ayed, N.; Benterman, N. A.; Bergsaker, H.; Bernardo, J.; Bernert, M.; Berry, M.; Bertalot, L.; Besliu, C.; Beurskens, M.; Bieg, B.; Bielecki, J.; Biewer, T.; Bigi, M.; Bilkova, P.; Binda, F.; Bisoffi, A.; Bizarro, J. P. S.; Bjorkas, C.; Blackburn, J.; Blackman, K.; Blackman, T. R.; Blanchard, P.; Blatchford, P.; Bobkov, V.; Boboc, A.; Bodnar, G.; Bogar, O.; Bolshakova, I.; Bolzonella, T.; Bonanomi, N.; Bonelli, F.; Boom, J.; Booth, J.; Borba, D.; Borodin, D.; Borodkina, I.; Botrugno, A.; Bottereau, C.; Boulting, P.; Bourdelle, C.; Bowden, M.; Bower, C.; Bowman, C.; Boyce, T.; Boyd, C.; Boyer, H. J.; Bradshaw, J. M. A.; Braic, V.; Bravanec, R.; Breizman, B.; Bremond, S.; Brennan, P. D.; Breton, S.; Brett, A.; Brezinsek, S.; Bright, M. D. J.; Brix, M.; Broeckx, W.; Brombin, M.; Broslawski, A.; Brown, D. P. D.; Brown, M.; Bruno, E.; Bucalossi, J.; Buch, J.; Buchanan, J.; Buckley, M. A.; Budny, R.; Bufferand, H.; Bulman, M.; Bulmer, N.; Bunting, P.; Buratti, P.; Burckhart, A.; Buscarino, A.; Busse, A.; Butler, N. K.; Bykov, I.; Byrne, J.; Cahyna, P.; Calabro, G.; Calvo, I.; Camenen, Y.; Camp, P.; Campling, D. C.; Cane, J.; Cannas, B.; Capel, A. J.; Card, P. J.; Cardinali, A.; Carman, P.; Carr, M.; Carralero, D.; Carraro, L.; Carvalho, B. B.; Carvalho, I.; Carvalho, P.; Casson, F. J.; Castaldo, C.; Catarino, N.; Caumont, J.; Causa, F.; Cavazzana, R.; Cave-Ayland, K.; Cavinato, M.; Cecconello, M.; Ceccuzzi, S.; Cecil, E.; Cenedese, A.; Cesario, R.; Challis, C. D.; Chandler, M.; Chandra, D.; Chang, C. S.; Chankin, A.; Chapman, I. T.; Chapman, S. C.; Chernyshova, M.; Chitarin, G.; Ciraolo, G.; Ciric, D.; Citrin, J.; Clairet, F.; Clark, E.; Clark, M.; Clarkson, R.; Clatworthy, D.; Clements, C.; Cleverly, M.; Coad, J. P.; Coates, P. A.; Cobalt, A.; Coccorese, V.; Cocilovo, V.; Coda, S.; Coelho, R.; Coenen, J. W.; Coffey, I.; Colas, L.; Collins, S.; Conka, D.; Conroy, S.; Conway, N.; Coombs, D.; Cooper, D.; Cooper, S. R.; Corradino, C.; Corre, Y.; Corrigan, G.; Cortes, S.; Coster, D.; Couchman, A. S.; Cox, M. P.; Craciunescu, T.; Cramp, S.; Craven, R.; Crisanti, F.; Croci, G.; Croft, D.; Crombe, K.; Crowe, R.; Cruz, N.; Cseh, G.; Cufar, A.; Cullen, A.; Curuia, M.; Czarnecka, A.; Dabirikhah, H.; Dalgliesh, P.; Dalley, S.; Dankowski, J.; Darrow, D.; Davies, O.; Davis, W.; Day, C.; Day, I. E.; De Bock, M.; Castro, A. de; Cal, E. de la; Luna, E. de la; De Masi, G.; Pablos, J. L. de; De Temmerman, G.; De Tommasi, G.; Vries, P. de; Deakin, K.; Deane, J.; Agostini, F. D.; Dejarnac, R.; Delabie, E.; Harder, N. den; Dendy, R. O.; Denis, J.; Denner, P.; Devaux, S.; Devynck, P.; Di Maio, F.; Di Siena, A.; Di Troia, C.; Dinca, P.; D’Inca, R.; Ding, B.; Dittmar, T.; Doerk, H.; Doerner, R. P.; Donne, T.; Dorling, S. E.; Dormido-Canto, S.; Doswon, S.; Douai, D.; Doyle, P. T.; Drenik, A.; Drewelow, P.; Drews, P.; Duckworth, P.; Dumont, R.; Dumortier, P.; Dunai, D.; Dunne, M.; Duran, I.; Durodie, F.; Dutta, P.; Duval, B. P.; Dux, R.; Dylst, K.; Dzysiuk, N.; Edappala, P. V.; Edmond, J.; Edwards, A. M.; Edwards, J.; Eich, T.; Ekedahl, A.; El-Jorf, R.; Elsmore, C. G.; Enachescu, M.; Ericsson, G.; Eriksson, F.; Eriksson, J.; Eriksson, L. G.; Esposito, B.; Esquembri, S.; Esser, H. G.; Esteve, D.; Evans, B.; Evans, G. E.; Evison, G.; Ewart, G. D.; Fagan, D.; Faitsch, M.; Falie, D.; Fanni, A.; Fasoli, A.; Faustin, J. M.; Fawlk, N.; Fazendeiro, L.; Fedorczak, N.; Felton, R. C.; Fenton, K.; Fernades, A.; Fernandes, H.; Ferreira, J.; Fessey, J. A.; Fevrier, O.; Ficker, O.; Field, A.; Fietz, S.; Figueiredo, A.; Figueiredo, J.; Fil, A.; Finburg, P.; Firdaouss, M.; Fischer, U.; Fittill, L.; Fitzgerald, M.; Flammini, D.; Flanagan, J.; Fleming, C.; Flinders, K.; Fonnesu, N.; Fontdecaba, J. M.; Formisano, A.; Forsythe, L.; Fortuna, L.; Fortuna-Zalesna, E.; Fortune, M.; Foster, S.; Franke, T.; Franklin, T.; Frasca, M.; Frassinetti, L.; Freisinger, M.; Fresa, R.; Frigione, D.; Fuchs, V.; Fuller, D.; Futatani, S.; Fyvie, J.; Gal, K.; Galassi, D.; Galazka, K.; Galdon-Quiroga, J.; Gallagher, J.; Gallart, D.; Galvao, R.; Gao, X.; Gao, Y.; Garcia, J.; Garcia-Carrasco, A.; Garcia-Munoz, M.; Gardarein, J.-L.; Garzotti, L.; Gaudio, P.; Gauthier, E.; Gear, D. F.; Gee, S. J.; Geiger, B.; Gelfusa, M.; Gerasimov, S.; Gervasini, G.; Gethins, M.; Ghani, Z.; Ghate, M.; Gherendi, M.; Giacalone, J. C.; Giacomelli, L.; Gibson, C. S.; Giegerich, T.; Gil, C.; Gil, L.; Gilligan, S.; Gin, D.; Giovannozzi, E.; Girardo, J. B.; Giroud, C.; Giruzzi, G.; Gloeggler, S.; Godwin, J.; Goff, J.; Gohil, P.; Goloborod’ko, V.; Gomes, R.; Goncalves, B.; Goniche, M.; Goodliffe, M.; Goodyear, A.; Gorini, G.; Gosk, M.; Goulding, R.; Goussarov, A.; Gowland, R.; Graham, B.; Graham, M. E.; Graves, J. P.; Grazier, N.; Grazier, P.; Green, N. R.; Greuner, H.; Grierson, B.; Griph, F. S.; Grisolia, C.; Grist, D.; Groth, M.; Grove, R.; Grundy, C. N.; Grzonka, J.; Guard, D.; Guerard, C.; Guillemaut, C.; Guirlet, R.; Gurl, C.; Utoh, H. H.; Hackett, L. J.; Hacquin, S.; Hagar, A.; Hager, R.; Hakola, A.; Halitovs, M.; Hall, S. J.; Cook, S. P. H.; Hamlyn-Harris, C.; Hammond, K.; Harrington, C.; Harrison, J.; Harting, D.; Hasenbeck, F.; Hatano, Y.; Hatch, D. R.; Haupt, T. D. V.; Hawes, J.; Hawkes, N. C.; Hawkins, J.; Hawkins, P.; Haydon, P. W.; Hayter, N.; Hazel, S.; Heesterman, P. J. L.; Heinola, K.; Hellesen, C.; Hellsten, T.; Helou, W.; Hemming, O. N.; Hender, T. C.; Henderson, M.; Henderson, S. S.; Henriques, R.; Hepple, D.; Hermon, G.; Hertout, P.; Hidalgo, C.; Highcock, E. G.; Hill, M.; Hillairet, J.; Hillesheim, J.; Hillis, D.; Hizanidis, K.; Hjalmarsson, A.; Hobirk, J.; Hodille, E.; Hogben, C. H. A.; Hogeweij, G. M. D.; Hollingsworth, A.; Hollis, S.; Homfray, D. A.; Horacek, J.; Hornung, G.; Horton, A. R.; Horton, L. D.; Horvath, L.; Hotchin, S. P.; Hough, M. R.; Howarth, P. J.; Hubbard, A.; Huber, A.; Huber, V.; Huddleston, T. M.; Hughes, M.; Huijsmans, G. T. A.; Hunter, C. L.; Huynh, P.; Hynes, A. M.; Iglesias, D.; Imazawa, N.; Imbeaux, F.; Imrisek, M.; Incelli, M.; Innocente, P.; Irishkin, M.; Ivanova-Stanik, I.; Jachmich, S.; Jacobsen, A. S.; Jacquet, P.; Jansons, J.; Jardin, A.; Jarvinen, A.; Jaulmes, F.; Jednorog, S.; Jenkins, I.; Jeong, C.; Jepu, I.; Joffrin, E.; Johnson, R.; Johnson, T.; Johnston, J.; Joita, L.; Jones, G.; Jones, T. T. C.; Hoshino, K. 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I.; Otin, R.; Owen, A.; Paccagnella, R.; Pace, N.; Pacella, D.; Packer, L. W.; Page, A.; Pajuste, E.; Palazzo, S.; Pamela, S.; Panja, S.; Papp, P.; Paprok, R.; Parail, V.; Park, M.; Diaz, F. P.; Parsons, M.; Pasqualotto, R.; Patel, A.; Pathak, S.; Paton, D.; Patten, H.; Pau, A.; Pawelec, E.; Soldan, C. P.; Peackoc, A.; Pearson, I. J.; Pehkonen, S.-P.; Peluso, E.; Penot, C.; Pereira, A.; Pereira, R.; Puglia, P. P. P.; Thun, C. P. von; Peruzzo, S.; Peschanyi, S.; Peterka, M.; Petersson, P.; Petravich, G.; Petre, A.; Petrella, N.; Petrzilka, V.; Peysson, Y.; Pfefferle, D.; Philipps, V.; Pillon, M.; Pintsuk, G.; Piovesan, P.; Pires dos Reis, A.; Piron, L.; Pironti, A.; Pisano, F.; Pitts, R.; Pizzo, F.; Plyusnin, V.; Pomaro, N.; Pompilian, O. G.; Pool, P. J.; Popovichev, S.; Porfiri, M. T.; Porosnicu, C.; Porton, M.; Possnert, G.; Potzel, S.; Powell, T.; Pozzi, J.; Prajapati, V.; Prakash, R.; Prestopino, G.; Price, D.; Price, M.; Price, R.; Prior, P.; Proudfoot, R.; Pucella, G.; Puglia, P.; Puiatti, M. E.; Pulley, D.; Purahoo, K.; Puetterich, T.; Rachlew, E.; Rack, M.; Ragona, R.; Rainford, M. S. J.; Rakha, A.; Ramogida, G.; Ranjan, S.; Rapson, C. J.; Rasmussen, J. J.; Rathod, K.; Ratta, G.; Ratynskaia, S.; Ravera, G.; Rayner, C.; Rebai, M.; Reece, D.; Reed, A.; Refy, D.; Regan, B.; Regana, J.; Reich, M.; Reid, N.; Reimold, F.; Reinhart, M.; Reinke, M.; Reiser, D.; Rendell, D.; Reux, C.; Reyes Cortes, S. D. A.; Reynolds, S.; Riccardo, V.; Richardson, N.; Riddle, K.; Rigamonti, D.; Rimini, F. G.; Risner, J.; Riva, M.; Roach, C.; Robins, R. J.; Robinson, S. A.; Robinson, T.; Robson, D. 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(Team, ASDEX Upgrade, Team, TCV & Team, EUROfusion MST1, Hrsg.) Nuclear fusion, 59 (7), Art. Nr.: 076038. doi:10.1088/1741-4326/ab1eb9 

JET Contributors; Neverov, V. S.; Kukushkin, A. B.; Kruezi, U.; Stamp, M. F.; Weisen, H.; Joffrin, E.; Abduallev, S.; Abhangi, M.; Abreu, P.; Afzal, M.; Aggarwal, K. M.; Ahlgren, T.; Ahn, J. H.; Aho-Mantila, L.; Aiba, N.; Airila, M.; Albanese, R.; Aldred, V.; Alegre, D.; Alessi, E.; Aleynikov, P.; Alfier, A.; Alkseev, A.; Allinson, M.; Alper, B.; Alves, E.; Ambrosino, G.; Ambrosino, R.; Amicucci, L.; Amosov, V.; Sunden, E. A.; Angelone, M.; Anghel, M.; Angioni, C.; Appel, L.; Appelbee, C.; Arena, P.; Ariola, M.; Arnichand, H.; Arshad, S.; Ash, A.; Ashikawa, N.; Aslanyan, V.; Asunta, O.; Auriemma, F.; Austin, Y.; Avotina, L.; Axton, M. D.; Ayres, C.; Bacharis, M.; Baciero, A.; Baiao, D.; Bailey, S.; Baker, A.; Balboa, I.; Balden, M.; Balshaw, N.; Bament, R.; Banks, J. W.; Baranov, Y. F.; Barnard, M. A.; Barnes, D.; Barnes, M.; Barnsley, R.; Wiechec, A. B.; Orte, L. B.; Baruzzo, M.; Basiuk, V.; Bassan, M.; Bastow, R.; Batista, A.; Batistoni, P.; Baughan, R.; Bauvir, B.; Baylor, L.; Bazylev, B.; Beal, J.; Beaumont, P. S.; Beckers, M.; Beckett, B.; Becoulet, A.; Bekris, N.; Beldishevski, M.; Bell, K.; Belli, F.; Bellinger, M.; Belonohy, E.; Ben Ayed, N.; Benterman, N. A.; Bergsaker, H.; Bernardo, J.; Bernert, M.; Berry, M.; Bertalot, L.; Besliu, C.; Beurskens, M.; Bieg, B.; Bielecki, J.; Biewer, T.; Bigi, M.; Bilkova, P.; Binda, F.; Bisoffi, A.; Bizarro, J. P. S.; Bjorkas, C.; Blackburn, J.; Blackman, K.; Blackman, T. R.; Blanchard, P.; Blatchford, P.; Bobkov, V.; Boboc, A.; Bodnar, G.; Bogar, O.; Bolshakova, I.; Bolzonella, T.; Bonanomi, N.; Bonelli, F.; Boom, J.; Booth, J.; Borba, D.; Borodin, D.; Borodkina, I.; Botrugno, A.; Bottereau, C.; Boulting, P.; Bourdelle, C.; Bowden, M.; Bower, C.; Bowman, C.; Boyce, T.; Boyd, C.; Boyer, H. J.; Bradshaw, J. M. A.; Braic, V.; Bravanec, R.; Breizman, B.; Bremond, S.; Brennan, P. D.; Breton, S.; Brett, A.; Brezinsek, S.; Bright, M. D. J.; Brix, M.; Broeckx, W.; Brombin, M.; Broslawski, A.; Brown, D. P. D.; Brown, M.; Bruno, E.; Bucalossi, J.; Buch, J.; Buchanan, J.; Buckley, M. A.; Budny, R.; Bufferand, H.; Bulman, M.; Bulmer, N.; Bunting, P.; Buratti, P.; Burckhart, A.; Buscarino, A.; Busse, A.; Butler, N. K.; Bykov, I.; Byrne, J.; Cahyna, P.; Calabro, G.; Calvo, I.; Camenen, Y.; Camp, P.; Campling, D. C.; Cane, J.; Cannas, B.; Capel, A. J.; Card, P. J.; Cardinali, A.; Carman, P.; Carr, M.; Carralero, D.; Carraro, L.; Carvalho, B. B.; Carvalho, I.; Carvalho, P.; Casson, F. J.; Castaldo, C.; Catarino, N.; Caumont, J.; Causa, F.; Cavazzana, R.; Cave-Ayland, K.; Cavinato, M.; Cecconello, M.; Ceccuzzi, S.; Cecil, E.; Cenedese, A.; Cesario, R.; Challis, C. D.; Chandler, M.; Chandra, D.; Chang, C. S.; Chankin, A.; Chapman, I. T.; Chapman, S. 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Pollok, T.; Junglas, L.; Ruf, B.; Schumann, A. (2019). UnrealGT: Using Unreal Engine to Generate Ground Truth Datasets. Advances in Visual Computing : 14th International Symposium on Visual Computing, ISVC 2019, Lake Tahoe, NV, USA, October 7–9, 2019, Proceedings, Part I. Ed.: George Bebis, 670–682, Springer. doi:10.1007/978-3-030-33720-9_52 

Riese, F. M. (2019). Processing Scripts for Thermal Infrared Cameras. doi:10.5281/zenodo.3576242 

Riese, F. M. (2019). SUSI: SUpervised Self-organIzing maps in Python. Zenodo. doi:10.5281/zenodo.2609130 

Riese, F. M. (2019). CNN Soil Texture Classification. Zenodo. doi:10.5281/zenodo.2540718 

Riese, F. M.; Keller, S. (2019). Hyperspectral Regression: Code Examples. doi:10.5281/zenodo.3450676 

Riese, F. M.; Keller, S. (2019). SUSI: Supervised Self-Organizing Maps for Regression and Classification in Python. 

Riese, F. M.; Keller, S. (2019). Soil Texture Classification with 1D Convolutional Neural Networks based on Hyperspectral Data. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2019 ISPRS) Geospatial Week 2019, Enschede, NL, June 10-14, 2019. Vol. IV-2/W5, 615–621. doi:10.5194/isprs-annals-IV-2-W5-615-2019  

Ruf, B.; Pollok, T.; Weinmann, M. (2019). Efficient Surface-Aware Semi-Global Matching with Multi-View Plane-Sweep Sampling. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, IV-2/W7, 137–144. doi:10.5194/isprs-annals-IV-2-W7-137-2019  

Schmitz, S.; Weinmann, M.; Ruf, B. (2019). Automatic co-registration of aerial imagery and untextured model data utilizing average shading gradients. ISPRS Geospatial Week, 10-14 June 2019, Enschede, The Netherlands, 581–588, ISPRS. doi:10.5194/isprs-archives-XLII-2-W13-581-2019  

Sefrin, O.; Riese, F. M.; Keller, S. (2019). Soil Texture Processing. doi:10.5281/zenodo.3431628 

Spirig, R.; Vogt, R.; Larsen, J. A.; Feigenwinter, C.; Wicki, A.; Franceschi, J.; Parlow, E.; Adler, B.; Kalthoff, N.; Cermak, J.; Andersen, H.; Fuchs, J.; Bott, A.; Hacker, M.; Wagner, N.; Maggs-Kölling, G.; Wassenaar, T.; Seely, M. (2019). Probing the fog life-cycles in the Namib desert. Bulletin of the American Meteorological Society, 100 (12), 2491–2507. doi:10.1175/BAMS-D-18-0142.1 

Stirnberg, R.; Cermak, J.; Kotthaus, S.; Haeffelin, M.; Andersen, H.; Kim, M. (2019). Variability of air pollution (PM1) analyzed using explainable Machine Learning. Proceedings of the 9th International Workshop on Climate Informatics: CI 2019. Ed.: J. Brajard, 157–161, National Center for Atmospheric Research. doi:10.5065/y82j-f154 

Stötzer, J.; Wursthorn, S.; Keller, S. (2019). Fuzzy Estimation of Link Travel Time from a Digital Elevation Model and Road Hierarchy Level. Proceedings of the 5th International Conference on Geographical Information Systems Theory, Applications and Management (GISTAM), Heraklion, GR, May 3-5, 2019. Vol. 1, 15–25, SciTePress. doi:10.5220/0007655800150025 

Ulrich, M.; Follmann, P.; Neudeck, J.-H. (2019). A comparison of shape-based matching with deep-learning-based object detection. Technisches Messen, 86 (11), 685–698. doi:10.1515/teme-2019-0076 

Ulrich, M.; Steger, C. (2019). A camera model for cameras with hypercentric lenses and some example applications. Machine vision and applications, 30 (6), 1013–1028. doi:10.1007/s00138-019-01032-w  

Weinmann, M.; Weinmann, M. (2019). Urban Scene Labeling Based on Multi-Modal Data Acquired from Aerial Sensor Platforms. 2019 Joint Urban Remote Sensing Event (JURSE), Vannes, France, France, 22 - 24 Mai 2019, 1–4, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/JURSE.2019.8809035 

Weinmann, M.; Weinmann, M. (2019). Fusion of hyperspectral, multispectral, color and 3D point cloud information for the semantic interpretation of urban environments. ISPRS Geospatial Week 2019, 10-14 June 2019, Enschede, The Netherlands, 1899–1906, ISPRS. doi:10.5194/isprs-archives-XLII-2-W13-1899-2019  

Wiegner, M.; Mattis, I.; Pattantyús-Ábrahám, M.; Bravo-Aranda, J. A.; Poltera, Y.; Haefele, A.; Hervo, M.; Görsdorf, U.; Leinweber, R.; Gasteiger, J.; Haeffelin, M.; Wagner, F.; Cermak, J.; Komínková, K.; Brettle, M.; Münkel, C.; Pönitz, K. (2019). Aerosol backscatter profiles from ceilometers: validation of water vapor correction in the framework of CeiLinEx2015. Atmospheric measurement techniques, 12 (1), 471–490. doi:10.5194/amt-12-471-2019  

Woollam, J.; Rietbrock, A.; Hinz, S.; Leitloff, J. (2019). HEX: Hyperbolic Event eXtractor, a seismic phase association algorithm for regions of intense seismicity. AGU Fall Meeting 2019, San Francisco, 9 – 13 December 2019. 

Andersen, H.; Cermak, J. (2018). First fully diurnal fog and low cloud satellite detection reveals life cycle in the Namib. Atmospheric measurement techniques, 11 (10), 5461–5470. doi:10.5194/amt-11-5461-2018  

Bayram, B.; Demir, N.; Akpinar, B.; Oy, S.; Erdem, F.; Vögtle, T.; Seker, D. Z. (2018). Effect of different segmentation methods using optical satellite imagery to estimate fuzzy clustering parameters for Sentinel-1A SAR images. The international archives of photogrammetry, remote sensing and spatial information sciences, 42 (1), 39–43. doi:10.5194/isprs-archives-XLII-1-39-2018  

Boldt, M.; Thiele, A.; Schulz, K.; Hinz, S. (2018). On the categorization of high activity objects using differential attribute profiles. The international archives of photogrammetry, remote sensing and spatial information sciences, 42 (1), 59–64. doi:10.5194/isprs-archives-XLII-1-59-2018  

Boldt, M.; Thiele, A.; Schulz, K.; Hinz, S. (2018). On the classification of high activity objects. 12th European Conference on Synthetic Aperture Radar, EUSAR 2018; Eurogress AachenAachen; Germany; 4 June 2018 through 7 June 2018, 131–136, VDE Verlag. 

Bradley, P. E.; Keller, S.; Weinmann, M. (2018). Unsupervised Feature Selection Based on Ultrametricity and Sparse Training Data: A Case Study for the Classification of High-Dimensional Hyperspectral Data. Remote sensing, 10 (10), Art.Nr.: 1564. doi:10.3390/rs10101564  

Braun, A.; Stötzer, J.; Kubisch, S.; Keller, S. (2018). Critical Infrastructure Analysis (CRITIS) in Developing Regions – Designing an Approach to Analyse Peripheral Remoteness, Risks of Accessibility Loss, and Isolation due to Road Network Insufficiencies in Chile. GI-Forum, 6 (2), 302 - 321. doi:10.1553/giscience2018_02_s302 

Cermak, J. (2018). Fog and Low Cloud Frequency and Properties from Active-Sensor Satellite Data. Remote sensing, 10 (8), 1209. doi:10.3390/rs10081209  

Chen, K.; Fu, K.; Sun, X.; Weinmann, M.; Hinz, S.; Jutzi, B.; Weinmann, M. (2018). DEEP SEMANTIC SEGMENTATION OF AERIAL IMAGERY BASED ON MULTI-MODAL DATA. International Geoscience and Remote Sensing Symposium, Observing, Understanding and Forecasting the Dynamics of Our Planet (IGARSS 2018), Valencia, E, July 22-17, 2018, Institute of Electrical and Electronics Engineers (IEEE). 

Chen, K.; Weinmann, M.; Gao, X.; Yan, M.; Hinz, S.; Jutzi, B. (2018). Residual Shuffling Convolutional Neural Networks for Deep Semantic Image Segmentation Using Multi-Modal Data. 2018 ISPRS TC II Mid-term Symposium "Towards Photogrammetry 2020"; Riva del Garda; Italy, June 4-7, 2018. Ed.: T. Fuse, 65–72, Copernicus Publications. doi:10.5194/isprs-annals-IV-2-65-2018  

Chen, K.; Weinmann, M.; Sun, X.; Yan, M.; Hinz, S.; Jutzi, B.; Weinmann, M. (2018). SEMANTIC SEGMENTATION OF AERIAL IMAGERY VIA MULTI-SCALE SHUFFLING CONVOLUTIONAL NEURAL NETWORKS WITH DEEP SUPERVISION. ISPRS annals, IV-1, 29–36. doi:10.5194/isprs-annals-IV-1-29-2018  

Follmann, P.; Böttger, T.; Härtinger, P.; König, R.; Ulrich, M. (2018). MVTec D2S: Densely Segmented Supermarket Dataset. Computer Vision – ECCV 2018. Ed.: V. Ferrari, 581–597, Springer. doi:10.1007/978-3-030-01249-6_35 

Fuchs, J.; Cermak, J.; Andersen, H. (2018). Building a cloud in the southeast Atlantic: understanding low-cloud controls based on satellite observations with machine learning. Atmospheric chemistry and physics, 18 (22), 16537–16552. doi:10.5194/acp-18-16537-2018  

Gabriel, R.; Keller, S.; Matthes, J.; Waibel, P.; Keller, H. B.; Hinz, S. (2018). Infrared measurements and estimation of temperature in the restrictive scope of an industrial cement plant. 2018 ISPRS Technical Commission I Midterm Symposium on Innovative Sensing - From Sensors to Methods and Applications; Karlsruhe; Germany; 10 October 2018 through 12 October 2018, 53–60, Curran. doi:10.5194/isprs-annals-IV-1-53-2018  

Giovanella, A.; Bradley, P. E.; Wursthorn, S. (2018). Detection and evaluation of topological consistency in CityGML datasets. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, TC IV Mid-Term Symposium on 3D Spatial Information Science - The Engine of Change; Delft; NL, October 1-5, 2018, 59–66, Copernicus Publications. doi:10.5194/isprs-annals-IV-4-59-2018  

Grinberg, M.; Ruf, B.; Monka, S.; Kollman, M.; Buller, A.; Tchouchenkov, I. (2018). Embedded Stereokamera-basierte reaktive Kollisionsvermeidung für UAVs Embedded stereo vision based reactive collision avoidance for UAVs. Forum Bildverarbeitung 2018. Hrsg.: T. Längle, P. L. Fernando, M. Heizmann, 277–290, KIT Scientific Publishing. doi:10.5445/IR/1000088327  

Grudzielanek, A. M.; Cermak, J. (2018). Temporal Patterns and Vertical Temperature Gradients in Micro-Scale Drainage Flow Observed Using Thermal Imaging. Atmosphere, 9 (12), Article: 498. doi:10.3390/atmos9120498  

Heublein, M.; Alshawaf, F.; Erdnüß, B.; Zhu, X. X.; Hinz, S. (2018). Compressive sensing reconstruction of 3D wet refractivity based on GNSS and InSAR observations. Journal of geodesy, 1–21. doi:10.1007/s00190-018-1152-0  

Hübner, P.; Weinmann, M.; Hillemann, M.; Jutzi, B.; Wursthorn, S. (2018). Combining independent visualization and tracking systems for augmented reality. 2018 ISPRS TC II Mid-term Symposium “Towards Photogrammetry 2020”, 455–462, International Society for Photogrammetry and Remote Sensing (ISPRS). doi:10.5194/isprs-archives-XLII-2-455-2018  

Hübner, P.; Weinmann, M.; Wursthorn, S. (2018). Marker-based localization of the Microsoft HoloLens in building models. ISPRS TC I Mid-term Symposium “Innovative Sensing – From Sensors to Methods and Applications", 195–202, International Society for Photogrammetry and Remote Sensing (ISPRS). doi:10.5194/isprs-archives-XLII-1-195-2018  

Ilehag, R.; Bulatov, D.; Helmholz, P.; Belton, D. (2018). Classification and representation of commonly used roofing material using multisensorial aerial data. The international archives of photogrammetry, remote sensing and spatial information sciences, 42 (1), 217–224. doi:10.5194/isprs-archives-XLII-1-217-2018  

Jutzi, B.; Weinmann, M.; Hinz, S. (2018). PREFACE. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-1, 1–3. doi:10.5194/isprs-archives-XLII-1-1-2018  

Jutzi, B.; Weinmann, M.; Hinz, S. (2018). PREFACE. ISPRS annals, IV-1, 1–3. doi:10.5194/isprs-annals-IV-1-1-2018  

Keller, S.; Maier, P.; Riese, F.; Norra, S.; Holbach, A.; Börsig, N.; Wilhelms, A.; Moldaenke, C.; Zaake, A.; Hinz, S. (2018). Hyperspectral Data and Machine Learning for Estimating CDOM, Chlorophyll a, Diatoms, Green Algae and Turbidity. International journal of environmental research and public health, 15 (9), 1881/1–15. doi:10.3390/ijerph15091881  

Keller, S.; Riese, F. M.; Allroggen, N.; Jackisch, C.; Hinz, S. (2018). Modeling Subsurface Soil Moisture Based on Hyperspectral Data : First Results of a Multilateral Field Campaign. Photogrammetrie, Fernerkundung, Geoinformatik, Kartographie 2018 (PFGK18) : Beiträge der 37. Wissenschaftlich-Technische Jahrestagung der DGPF e.V., 5. Münchner GI-Runde Runder Tisch GIS e.V. und des 66. Deutscher Kartographie Kongress der DGfK e.V., München, Deutschland, 7. - 9. März 2018. Hrsg.: T. P. Kersten, 34–48, Deutsche Gesellschaft für Photogrammetrie. 

Keller, S.; Riese, F. M.; Stötzer, J.; Maier, P. M.; Hinz, S. (2018). Developing a machine learning framework for estimating soil moisture with VNIR hyperspectral data. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences - Symposium “Innovative Sensing – From Sensors to Methods and Applications”, Karlsruhe, Germany, 10–12 October 2018. Volume: IV-1, 101–108, ISPRS. doi:10.5194/isprs-annals-IV-1-101-2018  

Kern, J.; Schenk, A.; Hinz, S. (2018). Radiometric Calibration of a UAV-Mounted Hyperspectral Snapshot Camera with Focus on Uniform Spectral Sampling. 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS 2018), Amsterdam, NL, September 23-26, 2018, Article No.8747027, IEEE Computer Society. doi:10.1109/WHISPERS.2018.8747027 

Kim, M.; Lee, J.; Han, D.; Shin, M.; Im, J.; Lee, J.; Quackenbush, L. J.; Gu, Z. (2018). Convolutional Neural Network-Based Land Cover Classification Using 2-D Spectral Reflectance Curve Graphs With Multitemporal Satellite Imagery. IEEE journal of selected topics in applied earth observations and remote sensing, 11 (12), 4604–4617. doi:10.1109/JSTARS.2018.2880783 

Kim, M.; Lee, J.; Im, J. (2018). Deep learning-based monitoring of overshooting cloud tops from geostationary satellite data. GIScience and remote sensing, 55 (5), 763–792. doi:10.1080/15481603.2018.1457201 

Kuny, S.; Ihrig, R.; Boldt, M.; Thiele, A. (2018). Study on phenological changes in TerraSAR-X time series. 12th European Conference on Synthetic Aperture Radar, EUSAR 2018; Eurogress AachenAachen; Germany; 4 June 2018 through 7 June 2018, 55–58, VDE Verlag. 

Leitloff, J.; Riese, F. M. (2018). Examples for CNN training and classification on Sentinel-2 data. doi:10.5281/zenodo.3268451 

Maier, P. M.; Hinz, S.; Keller, S. (2018). Estimation of Chlorophyll a, Diatoms and Green Algae Based on Hyperspectral Data with Machine Learning Approaches. Photogrammetrie, Fernerkundung, Geoinformatik, Kartographie 2018 (PFGK18) : Beiträge der 37. Wissenschaftlich-Technische Jahrestagung der DGPF e.V., 5. Münchner GI-Runde Runder Tisch GIS e.V. und des 66. Deutscher Kartographie Kongress der DGfK e.V., München, Deutschland, 7. - 10. März 2018. Hrsg.: T. P. Kersten, 49–57, Deutsche Gesellschaft für Photogrammetrie. 

Maier, P. M.; Keller, S. (2018). Machine learning regression on hyperspectral data to estimate multiple water parameters. 

Mandlburger, G.; Jutzi, B. (2018). FEASIBILITY INVESTIGATION ON SINGLE PHOTON LIDAR BASED WATER SURFACE MAPPING. ISPRS annals, IV-1, 109–116. doi:10.5194/isprs-annals-IV-1-109-2018  

Mueller, M.; Metzger, A.; Jutzi, B. (2018). CNN-Based Initial Localization Improved by Data Augmentation. ISPRS TC I Mid-term Symposium “Innovative Sensing – From Sensors to Methods and Applications”, 10–12 October 2018, Karlsruhe, Germany, 117–124, ISPRS. doi:10.5194/isprs-annals-IV-1-117-2018  

Mueller, M. S.; Jutzi, B. (2018). UAS Navigation with SqueezePoseNet—Accuracy Boosting for Pose Regression by Data Augmentation. Drones, 2 (1), 7. doi:10.3390/drones2010007  

Müller, M.; Stüker, S.; Waibel, A. (2018). Neural language codes for multilingual acoustic models. 19th Annual Conference of the International Speech Communication, INTERSPEECH 2018; Hyderabad International Convention Centre (HICC)Hyderabad; India; 2 September 2018 through 6 September 2018. Ed.: C. C. Sekhar, 2419–2423, ISCA. doi:10.21437/Interspeech.2018-1241 

Müller, T.; Erdnüß, B. (2018). Stochastische Mustererkennung zur Bildsegmentierung = Stochastic pattern recognition for image segmentation. Forum Bildverarbeitung 2018. Hrsg.: T. Längle, P. L. Fernando, M. Heizmann, 173–184, KIT Scientific Publishing. doi:10.5445/IR/1000088266  

Niessner, R.; Schilling, H.; Hinz, S.; Jutzi, B. (2018). Klassifikation von Fahrzeugen aus RGB- und LiDAR-Daten mit Convolutional Neural Networks. 38. Wissenschaftlich-Technische Jahrestagung der DGPF und PFGK18 Tagung, München, 7-9. März 2018. Hrsg.: T.P. Kersten, 767–777, DGPF. 

Nilo, S. T.; Romano, F.; Cermak, J.; Cimini, D.; Ricciardelli, E.; Cersosimo, A.; Paola, F. D.; Gallucci, D.; Gentile, S.; Geraldi, E.; Larosa, S.; Ripepi, E.; Viggiano, M. (2018). Fog Detection Based on Meteosat Second Generation-Spinning Enhanced Visible and InfraRed Imager High Resolution Visible Channel. Remote sensing, 10 (4), Art.Nr. 541. doi:10.3390/rs10040541  

Riese, F. M.; Keller, S. (2018). Introducing a Framework of Self-Organizing Maps for Regression of Soil Moisture with Hyperspectral Data. IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain, 22nd - 27th July, 2018, 6151–6154, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IGARSS.2018.8517812 

Riese, F. M.; Keller, S. (2018, April 24). Hyperspectral benchmark dataset on soil moisture. doi:10.5281/zenodo.1227837 

Riese, F. M.; Keller, S. (2018). Fusion of hyperspectral and ground penetrating radar data to estimate soil moisture. 9th Workshop on Hyperspectral Image and Signal Processing : Evolution in Remote Sensing (Whispers 2018), Amsterdam, NL, September 23-26, 2018, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/WHISPERS.2018.8747076 

Ruf, B.; Monka, S.; Kollmann, M.; Grinberg, M. (2018). Real-Time On-Board Obstacle Avoidance for UAVs based on Embedded Stereo Vision. The international archives of photogrammetry, remote sensing and spatial information sciences, XLII-1, 363–370. doi:10.5194/isprs-archives-XLII-1-363-2018  

Ruf, B.; Thiel, L.; Weinmann, M. (2018). Deep Cross-Domain Building Extraction for Selective Depth Estimation from Oblique Aerial Imagery. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, IV-1, 125–132. doi:10.5194/isprs-annals-IV-1-125-2018  

Siegfarth, C.; Voegtle, T.; Fabinski, C. (2018). Comparison of two methods for 2D pose estimation of industrial workpieces in images - CNN vs. Classical image processing system. The international archives of photogrammetry, remote sensing and spatial information sciences, 42 (1), 401–405. doi:10.5194/isprs-archives-XLII-1-401-2018  

Stirnberg, R.; Cermak, J.; Andersen, H. (2018). An Analysis of Factors Influencing the Relationship between Satellite-Derived AOD and Ground-Level PM10. Remote sensing, 10 (9), Art.-Nr.: 1353/1–17. doi:10.3390/rs10091353  

Weinmann, M.; Maier, P. M.; Florath, J.; Weidner, U. (2018). Investigation on the potential of hyperspectral and Sentinel-2 data for land-cover / land-use classification. 2018 ISPRS Technical Commission I Midterm Symposium on Innovative Sensing - From Sensors to Methods and Applications; Karlsruhe; Germany; 10 October 2018 through 12 October 2018. Ed.: S. Hinz, 155–162, Curran. doi:10.5194/isprs-annals-IV-1-155-2018  

Weinmann, M.; Weidner, U. (2018). Erste Erfahrungen mit der Nutzung von Sentinel-2 Daten zur multispektralen und multitemporalen Analyse mit verschiedenen Klassifizierungsverfahren. Photogrammetrie - Fernerkundung - Geoinformatik - Kartographie - 2018 : 38. Wissenschaftlich-Technische Jahrestagung der DGPF e.V., 5. Münchner GI-Runde Runder Tisch GIS e.V., 66. Deutscher Kartographie Kongress der DGfK e.V. : 7.-9. März 2018 in München : Beiträge, 58–70, DGPF. 

Weinmann, M.; Blomley, R.; Weinmann, M.; Jutzi, B. (2018). Investigations on the potential of binary and multi-class classification for object extraction from airborne laser scanning point clouds. 38. Wissenschaftlich-Technische Jahrestagung der DGPF und PFGK18 Tagung, München, 7-9. März 2018. Hrsg.: T.P. Kersten, 408–421, DGPF. 

Weinmann, M.; Weidner, U. (2018). Land-Cover and Land-Use Classification Based on Multitemporal Sentinel-2 Data. IEEE International Geoscience & Remote Sensing Symposium : proceedings : July 22–27, 2018, Valencia, Spain, 4946–4949, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IGARSS.2018.8519301 

Weinmann, M.; Weinmann, M. (2018). Geospatial Computer Vision Based on Multi-Modal Data—How Valuable Is Shape Information for the Extraction of Semantic Information?. Remote sensing, 10 (1), 2. doi:10.3390/rs10010002  

Welte, A.; Hammer, H.; Thiele, A.; Hinz, S. (2018). Urban change detection in TanDEM-X interferograms. 12th European Conference on Synthetic Aperture Radar, EUSAR 2018; Eurogress AachenAachen; Germany; 4 June 2018 through 7 June 2018, 148–152, VDE Verlag. 

Andersen, H.; Cermak, J.; Fuchs, J.; Knutti, R.; Lohmann, U. (2017). Understanding the drivers of marine liquid-water cloud occurrence and properties with global observations using neural networks. Atmospheric chemistry and physics, 17 (15), 9535–9546. doi:10.5194/acp-17-9535-2017  

Bartelsen, J.; Müller, T.; Ring, J.; Mück, K.; Brüstle, S.; Erdnüß, B.; Lutz, B.; Herbst, T. (2017). Video change detection for fixed wing UAVs. SPIE Security + Defence : Target and Background Signatures, Warsaw, Poland, 11th - 14th September 2017, Art.Nr. 104320K, Society of Photo-optical Instrumentation Engineers (SPIE). doi:10.1117/12.2278094 

Blomley, R.; Hovi, A.; Weinmann, M.; Hinz, S.; Korpela, I.; Jutzi, B. (2017). Tree species classification using within crown localization of waveform LiDAR attributes. ISPRS journal of photogrammetry and remote sensing, 133, 142–156. doi:10.1016/j.isprsjprs.2017.08.013 

Boldt, M.; Thiele, A.; Schulz, K.; Hinz, S. (2017). Change Classification in SAR Time Series : A Functional Approach. SPIE Remote Sensing : Earth Resources and Environmental Remote Sensing/GIS Applications VIII, Warsaw, Poland, 11th - 14th September 2017, Art.Nr. 1042802, Society of Photo-optical Instrumentation Engineers (SPIE). doi:10.1117/12.2277578 

Böttger, T.; Ulrich, M.; Steger, C. (2017). Subpixel-Precise Tracking of Rigid Objects in Real-Time. Image Analysis. Part 1. Ed.: P. Sharma, 54–65, Springer Verlag. doi:10.1007/978-3-319-59126-1_5 

Bradley, P. E. (2017). Finding Ultrametricity in Data using Topology. Journal of classification, 34 (1), 76–84. doi:10.1007/s00357-017-9228-8 

Breunig, M.; Borrmann, A.; Rank, E.; Hinz, S.; Kolbe, T.; Schilcher, M.; Mundani, R.-P.; Jubierre, J. R.; Flurl, M.; Thomsen, A.; Donaubauer, A.; Ji, Y.; Urban, S.; Laun, S.; Vilgertshofer, S.; Willenborg, B.; Menninghaus, M.; Steuer, H.; Wursthorn, S.; Leitloff, J.; Al-Doori, M.; Mazroobsemnani, N. (2017). Collaborative multi-scale 3D city and infrastructure modeling and simulation. The international archives of photogrammetry, remote sensing and spatial information sciences, 42 (4W4), 341–352. doi:10.5194/isprs-archives-XLII-4-W4-341-2017  

CEDIM. (2017). CEDIM Research Report 2015-2016. (M. Kunz & A. Dittrich, Hrsg.), CEDIM. doi:10.5445/IR/1000069933  

Dittrich, A.; Weinmann, M.; Hinz, S. (2017). Analytical and numerical investigations on the accuracy and robustness of geometric features extracted from 3D point cloud data. ISPRS journal of photogrammetry and remote sensing, (126), 195–208. doi:10.1016/j.isprsjprs.2017.02.012 

Drost, B.; Ulrich, M.; Bergmann, P.; Härtinger, P.; Steger, C. (2017). Introducing MVTec ITODD — A Dataset for 3D Object Recognition in Industry. 2017 IEEE International Conference on Computer Vision Workshops (ICCVW), 2200–2208, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICCVW.2017.257 

Dubois, C.; Nascetti, A.; Thiele, A.; Crespi, M.; Hinz, S. (2017). SAR-SIFT for matching multiple SAR images and radargrammetry [SAR-SIFT für das Matching von Multiplen SAR Bildern und Radargrammetry]. PFG - Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 85 (3), 149–158. doi:10.1007/s41064-017-0019-y 

Erdnüß, B. (2017). Das baryzentrische Verhältnis als Invariante der projektiven Geometrie = The barycentric ratio as invariant of projective geometry. Technisches Messen, 84 (7-8), 479–492. doi:10.1515/teme-2017-0014 

Fuchs, J.; Cermak, J.; Andersen, H.; Hollmann, R.; Schwarz, K. (2017). On the Influence of Air Mass Origin on Low-Cloud Properties in the Southeast Atlantic. Journal of geophysical research / Atmospheres. doi:10.1002/2017JD027184 

Hillemann, M.; Jutzi, B. (2017). UCalMiCeL - Unified Intrinsic and Extrinsic Calibration of a Multi-Camera-System and a Laserscanner. 4th ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences - International Conference on Unmanned Aerial Vehicles in Geomatics, Bonn, Germany, 4.-7. September 2017. Ed.: C. Stachniss. Vol. IV-2/W3., 49–57, ISPRS. doi:10.5194/isprs-annals-IV-2-W3-17-2017  

Ihrig, R.; Kuny, S.; Thiele, A.; Hinz, S. (2017). Analysis of phenological changes of high vegetation in amplitude images of SAR time series. SPIE Remote Sensing : Earth Resources and Environmental Remote Sensing/GIS Applications VIII, Warsaw, Poland, 11th - 14th September 2017, Art.Nr. 104280W, Society of Photo-optical Instrumentation Engineers (SPIE). doi:10.1117/12.2278417 

Ilehag, R.; Auer, S.; D’Angelo, P. (2017). Exploitation of digital surface models generated from worldview-2 data for sar simulation techniques. 2017 ISPRS Hannover Workshop : High-Resolution Earth Imaging for Geospatial Information (HRIGI 17) - City Models, Roads and Traffic (CMRT 17) - Image Sequence Analysis (ISA 17) - European Calibration and Orientation Workshop (EuroCOW 17), Hannover, Germany, 6-9 June 2017. Ed.: C. Heipke, 55–61. doi:10.5194/isprs-archives-XLII-1-W1-55-2017  

Ilehag, R.; Schenk, A.; Hinz, S. (2017). Concept for classifying facade elements based on material, geometry and thermal radiation using multimodal UAV remote sensing. 4th ISPRS International Conference on Unmanned Aerial Vehicles in Geomatics, Bonn, Germany, 4th - 7th September 2017, 145–151, International Society for Photogrammetry and Remote Sensing (ISPRS). doi:10.5194/isprs-archives-XLII-2-W6-145-2017  

Ilehag, R.; Weinmann, M.; Schenk, A.; Keller, S.; Jutzi, B.; Hinz, S. (2017). Revisiting Existing Classification Approaches for Building Materials Based on Hyperspectral Data. The international archives of photogrammetry, remote sensing and spatial information sciences, XLII-3/W3, 65–71. doi:10.5194/isprs-archives-XLII-3-W3-65-2017  

Jahn, M. W.; Bradley, P. E.; Al Doori, M.; Breunig, M. (2017). Topologically Consistent Models for Efficient Big Geo-Spatio-Temporal Data Distribution. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 12th 3D Geoinfo Conference 2017, Melbourne, Australia, 26th - 27th October 2017, 65–72, Copernicus Publications. doi:10.5194/isprs-annals-IV-4-W5-65-2017  

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