Prof. Uwe Sörgel is the head of the Institute for Photogrammetry at the Universitaet Stuttgart since 2016.
| Books, Book Chapters, Dissertations |
|---|
Soergel, Uwe; Wegner, Jan Dirk; Thiele, Antje [2016]
Fusion von optischen und Radardaten. In Band „Photogrammetrie und Fernerkundung“, Christian Heipke (Ed.) – Handbuch der Geodäsie, 6 Bände, Willi Freeden, Reiner Rummel (Eds.). Springer Berlin Heidelberg, ISBN 978-3-662-46900-2.
DOI: 10.1007/978-3-662-46900-2_54-1
| Peer Reviewed Journal Papers |
|---|
Gu, H.; Han, Y.; Yang, Y.; Li, H.; Liu, Z.; Soergel, U.; Blaschke, T. & Cui, S. [2018]
An Efficient Parallel Multi-Scale Segmentation Method for Remote Sensing Imagery. Remote Sens. 2018, 10, 590.
DOI: 10.3390/rs10040590
Kenduiywo, B. K.; Bargiel, D. & Soergel, U. [2018]
Crop-type mapping from a sequence of Sentinel 1 images. International Journal of Remote Sensing.
DOI: 10.1080/01431161.2018.1460503
Schilling, H.; Bulatov, D.; Niessner, R.; Middelmann W. and Soergel, U. [2018]
Detection of Vehicles in Multisensor Data via Multibranch Convolutional Neural Networks. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
DOI: 10.1109/JSTARS.2018.2825099
Li, H.; Ghamisi, P.; Soergel, U.& Zhu, X.X [2018]
Hyperspectral and LiDAR Fusion Using Deep Three-Stream Convolutional Neural Networks. Remote Sens. 2018, 10, 1649.
DOI: 10.3390/rs10101649
Gu, H.; Li, H.; Yan, L.; Liu, Z.; Blaschke, T. & Soergel, U. [2017]
An Object-Based Semantic Classification Method for High Resolution Remote Sensing Imagery Using Ontology. Remote Sens. 2017, 9, 329.
DOI: 10.3390/rs9040329
Kenduiywo, B. K.; Bargiel, D. & Soergel, U. [2017]
Higher Order Dynamic Conditional Random Fields Ensemble for Crop Type Classification in Radar Images. IEEE Transactions on Geoscience and Remote Sensing, ISSN 0196-2892, Volume 55, Issue: 8, Aug. 2017, pp. 4638-4654.
DOI: 10.1109/TGRS.2017.2695326
Schack, L.; Soergel, U. & Heipke, C. [2017]
Assigning Persistent Scatterers of Regular Multi-Story Buildings to
Optical Oblique Images. PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, (), 1-8.
URL: http://link.springer.com/article/10.1007/s41064-017-0005-4
DOI: 10.1007/s41064-017-0005-4
Schunert, A. & Soergel, U. [2016]
Assignment of Persistent Scatterers to Buildings. In: IEEE Transactions on Geoscience and Remote Sensing, ISSN 0196-2892, Volume 54, Issue 6, pp. 3116-3127.
DOI: 10.1109/TGRS.2015.2511583
| Peer Reviewed Conference Papers |
|---|
Mandlburger, G.; Pfeifer, N. & Soergel, U. [2017]
Water Surface Reconstruction in Airborne Laser Bathymetry from Redundant Bed Observations. ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W4, 123-130.
DOI: 10.5194/isprs-annals-IV-2-W4-123-2017
Yang, C.H. & Soergel, U. [2017]
Monitoring of Building Construction by 4D Change Detection Using Multi-temporal SAR Images. ISPRS Annals of The Photogrammetry, Remote Sensing and Spatial Information Sciences, IV-1/W1, pp. 35-42 (ISPRS Hannover Workshop 2017, Hannover, Germany).
DOI: 10.5194/isprs-annals-IV-1-W1-35-2017
Kenduiywo, B. K.; Bargiel, D. & Soergel, U. [2016]
Crop Type Mapping from a Sequence of TerraSAR-X Images with Dynamic Conditional Random Fields. ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-7, pp. 59-66.
DOI: 10.5194/isprs-annals-III-5-57-2016
Yang, C.-H.; Kenduiywo, B.K. & Soergel, U. [2016]
4D change detection based on persistent scatterer interferometry. Pattern Recogniton in Remote Sensing (PRRS), 2016 9th IAPR Workshop on Pattern Recogniton in Remote Sensing, Cancun, Mexico. 6p.
DOI: 10.1109/PRRS.2016.7867016
Schack, L.; Soergel, U. & Heipke, C. [2016]
Graph Matching for the Registration of Persistent Scatters to Optical Oblique Imagery. ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-7, pp. 195-202.
DOI: 10.5194/isprs-annals-III-7-195-2016
Yang, C.-H.; Kenduiywo, B. K. & Soergel, U. [2016]
Change Detection Based on Persistent Scatterer Interferometry – A New Method of Monitoring Building Changes. ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-7, pp. 243-250.
DOI: 10.5194/isprs-annals-III-7-243-2016
| Non-reviewed Conference Papers |
|---|
Schmohl, S. & Soergel, U. [2019]
ALS Klassifizierung mit Submanifold Sparse Convolutional Networks. Dreiländertagung der DGPF, der OVG und der SGPF in Wien, Österreich – Publikationen der DGPF, Band 28, 2019, pp. 111-122.
URL: https://www.dgpf.de/src/tagung/jt2019/proceedings/proceedings/papers/23_3LT2019_Schmohl_Soergel.pdf
Yang, C.H. & Soergel, U. [2017]
Urban Monitoring by 4D Change Detection Using Multi-temporal SAR Images. DGPF annual conference, Würzburg, Germany. Publikationen der DGPF, Band 26, 2017. pp. 233-244.
URL: http://www.dgpf.de/src/tagung/jt2017/proceedings/proceedings/papers/23_DGPF2017_Yang_Soergel.pdf
Schmidt, A.; Kruse, C.; Rottensteiner, F.; Soergel, U. & Heipke, C. [2016]
Network Detection in Raster Data Using Marked Point Processes. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B3, pp. 701-708.
DOI: 10.5194/isprs-archives-XLI-B3-701-2016
Niemeyer, J.; Rottensteiner, F.; Soergel, U. & Heipke, C. [2016]
Hierarchical Higher Order CRF for the Classification of Airborne Lidar Point Clouds in Urban Areas. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B3, pp. 655-662.
DOI: 10.5194/isprs-archives-XLI-B3-655-2016
Schack, L.; Soergel, U. & Heipke, C. [2016]
Graph matching for the registration of persistent scatterers to optical oblique imagery. Proceedings, Asian Conference on Remote Sensing, Colombo, 8p., on USB-Stick.
Balz, T.; Haala, N. & Soergel, U. [2005]
Combining LIDAR, InSAR, SAR and SAR-Simulation for Change Detection Applications in Cloud-prone Areas. In: 1st Intern. Symposium on Cloude-Prone and Rainy Areas Remote Sensing (CARRS), Hong-Kong, pp. 68-79.