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Jump to: A | B | G | I | J | K | N | S | W | Y
Number of items at this level: 37.

A

Assali, M. and Pipelidis, G. and Podolskiy, V. and Iwaszczuk, Dorota and Heinen, L. and Gerndt, M. (2019):
Quantifying the quality of indoor maps.
Enschede, In: ISPRS Geospatial Week 2019, Enschede, 10–14 June 2019, XLII-2/W13, [Online-Edition: https://doi.org/10.5194/isprs-archives-XLII-2-W13-739-2019],
[Conference or Workshop Item]

B

Busquierand, M. and Lopez-Sanchez, Juan M. and Bargiel, D. (2019):
Added Value of Coherent Copolar Polarimetry at X-Band for Crop-Type Mapping.
In: IEEE Geoscience and Remote Sensing Letters, IEEE, pp. 1-5, ISSN 1558-0571,
DOI: 10.1109/LGRS.2019.2933738,
[Online-Edition: https://ieeexplore.ieee.org/abstract/document/8809193],
[Article]

Bargiel, D. (2017):
A new method for crop classification combining time series of radar images and crop phenology information.
In: Remote Sensing of Environment, RSE, pp. 369-383, 198, DOI: 10.1016/j.rse.2017.06.022,
[Online-Edition: https://authors.elsevier.com/a/1VJli7qzSfgOb],
[Article]

Bargiel, D. and Neuendorf, F. and Schlund, M. and Soergel, U. (2014):
Classification of crops in different European regions based on TerraSAR-X data.
[Conference or Workshop Item]

Baltsavias, M. and Cho, K. and Remondino, F. and Wakabayashi, H. and Soergel, U. (2013):
Rapidmap-rapid mapping and information dissemination for disasters using remote sensing and geoinformation.
In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Antalya, Turkey, XL-7/W2, [Conference or Workshop Item]

Bargiel, D. and Herrmann, S. and Jadczyszyn, J. (2013):
Using high-resolution radar images to determine vegetation cover for soil erosion assessments.
In: Journal of environmental management, Academic Press, pp. 82-90, 124, [Article]

Bargiel, D. (2013):
Capabilities of high resolution satellite radar for the detection of semi-natural habitat structures and grasslands in agricultural landscapes.
In: Ecological Informatics, Elsevier, pp. 9-16, 13, [Article]

Bargiel, D. and Herrmann, S. (2011):
Multi-temporal land-cover classification of agricultural areas in two European regions with high resolution spotlight TerraSAR-X data.
In: Remote Sensing, Molecular Diversity Preservation International, pp. 859-877, 3, (5), [Article]

Bargiel, D. and Herrmann, S. and Soergel, U. and Lohmann, P. (2010):
Land use classification with high resolution satellite radar for estimating the impacts of land use change on the quality of ecosystem services.
na, [Conference or Workshop Item]

G

Gabriel, G. and Lindenthal, N. and Schön, S. and Soergel, U. and Timmen, L. (2015):
Geometrische und gravimetrische Überwachung des GeneSys-Frac-Experiments.
In: AVN - Allgemeine Vermessungs-Nachrichten, Wichmann, pp. 207-218, [Online-Edition: https://www.wichmann-verlag.de/fachzeitschrift-avn/artikelar...],
[Article]

I

Iwaszczuk, Dorota and Koppanyi, Z. and Pfrang, J. and Toth, C. (2019):
Evaluation of a mobile multi-sensor system for seamless outdoor and indoor mapping.
Warsaw, In: Evaluation and Benchmarking Sensors, Systems and Geospatial Data in Photogrammetry and Remote Sensing, Warsaw, 16-17 September 2019, XLII-1/W2, [Online-Edition: https://doi.org/10.5194/isprs-archives-XLII-1-W2-31-2019],
[Conference or Workshop Item]

J

Jahr, Katrin and Iwaszczuk, Dorota and Borrmann, Andre (2019):
Combining airborne images and open data to retrieve knowledge of construction sites.
Leuven, In: 26th EG-ICE Workshop on Intelligent Computing in Engineering, Leuven, June 30 – July 03, 2019, [Conference or Workshop Item]

K

Koppanyi, Zoltan and Iwaszczuk, Dorota and Zha, Bing and Saul, Can Jozef and Toth, Charles K. and Yilmaz, Alper
Yang, Michael Ying and Rosenhahn, Bodo and Murino, Vittorio (eds.) (2019):
Multimodal Semantic Segmentation: Fusion of RGB and Depth Data in Convolutional Neural Networks.
In: Multimodal Scene Understanding, Academic Press, pp. 41 - 64, DOI: 10.1016/B978-0-12-817358-9.00009-3,
[Online-Edition: http://www.sciencedirect.com/science/article/pii/B9780128173...],
[Book Section]

Kenduiywo, B. K. and Bargiel, D. and Soergel, U. (2017):
Higher Order Dynamic Conditional Random Fields Ensemble for Crop Type Classification in Radar Images.
In: IEEE Transactions on Geoscience and Remote Sensing (TGRS), IEEE, pp. 1-17, [Online-Edition: http://ieeexplore.ieee.org/abstract/document/7924377/?reload...],
[Article]

Kenduiywo, B. K. and Bargiel, D. and Soergel, U. (2016):
CROP TYPE MAPPING FROM A SEQUENCE OF TERRASAR-X IMAGES WITH DYNAMIC CONDITIONAL RANDOM FIELDS.
In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, , 2016 XXIII ISPRS Congress, 12–19 July 2016, Prague, Czech Republic, ISPRS, pp. 59-66, Volume III-7, [Online-Edition: https://www.researchgate.net/profile/Benson_Kenduiywo/public...],
[Article]

Kenduiywo, Benson Kipkemboi (2016):
Spatial-temporal Dynamic Conditional Random Fields crop type mapping using radar images.
Darmstadt, Technische Universitaet Darmstadt Prints, ISBN 978-3-935631-41-9,
[Online-Edition: http://tuprints.ulb.tu-darmstadt.de/id/user/7098],
[Book]

Kenduiywo, B. K. and Bargiel, D. and Soergel, U. (2015):
Spatial-temporal conditional random fields crop classification from terrasar-x images.
In: PIA15+HRIGI15 – Joint ISPRS conference 2015, 25–27 March 2015, München. , München, 25-27 March 2015, [Conference or Workshop Item]

Kenduiywo, B. K. and Tolpekin, V. A. and Stein, A. (2014):
Detection of built-up area in optical and synthetic aperture radar images using conditional random fields.
In: Journal of Applied Remote Sensing, pp. 083672-1, 8, (1), [Online-Edition: http://dx.doi.org/10.1117/1.JRS.8.083672],
[Article]

Kenduiywo, B. K. and Nduati, E. W. and Mundia, C. N. and Korme, T. (2013):
Land-cover mapping using landsat for sustainable green house gas (GHG) inventory development.
In: Global Geospatial Conference (GSDI 14), [Article]

Kenduiywo, B. K. and Odera, P. A. and Hunja, E. (2013):
Orthometric Height Determination using GPS to Fast Track Development: a Case study of Nairobi County, Kenya.
In: Global Geospatial Conference (GSDI 14), [Article]

Kenduiywo, B. K. (2013):
Detection of built-up areas in SAR and optical images using conditional random fields.
In: J. Appl. Remote Sens. , [Article]

Kenduiywo, B. K. (2012):
Detection of built-up area expansion in ASTER and SAR images using conditional random fields.
In: SPIE Remote Sensing, pp. 85370N-85370N, [Article]

N

Niemeyer, J. and Rottensteiner, F. and Soergel, U. and Heipke, C. (2015):
Contextual classification of point clouds using a two stage CRF.
In: PIA15+HRIGI15 – Joint ISPRS conference 2015, München, 25–27 March 2015, [Online-Edition: http://www.pf.bgu.tum.de/isprs/pia15/pia15_prg.html],
[Conference or Workshop Item]

Niemeyer, J. and Rottensteiner, F. and Soergel, U. (2014):
Contextual classification of lidar data and building object detection in urban areas.
In: ISPRS Journal of Photogrammetry and Remote Sensing, pp. 152-186, [Article]

Niemeyer, J. and Soergel, U. (2013):
Opportunities of Airborne Laser Bathymetry for the Monitoring of the Sea Bed on the Baltic Sea Coast.
In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Antalya, Turkey, 11 – 17 November 2013, XL-7/W2, [Conference or Workshop Item]

Nduati, E. W. and Mundia, C. N. and Ngigi, M. M. and Kenduiywo, B. K. (2013):
A Remote Sensing-based approach to Evaluation of Trends and Impacts of Land Surface changes in the Mara Ecosystem.
In: Global Geospatial Conference (GSDI 14), [Article]

S

Song, Y. and Niemeyer, J. and Ellmer, W. and Soergel, U. and Heipke, C. (2015):
Comparison of Three Airborne Laser Bathymetry Data Sets for Monitoring the German Baltic Sea Coast.
In: Proc. SPIE 9638, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2015, SPIE, [Online-Edition: http://proceedings.spiedigitallibrary.org/proceeding.aspx?ar...],
[Article]

Schack, L. and Soergel, U. and Heipke, C. (2015):
Persistent scatterer aided facade lattice extraction in single airborne optical oblique images.
In: PIA15+HRIGI15 – Joint ISPRS conference 2015, 25–27 March 2015, München. , München, 25-27 March 2015, [Conference or Workshop Item]

Schack, L. and Soergel, U. (2014):
Exploiting Regular Patterns to Group Persistent Scatterers in Urban Areas.
In: Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal, IEEE, PP, (99), ISSN 1939-1404,
[Online-Edition: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=tru...],
[Article]

Sefercik, U. G. and Soergel, U. (2014):
Influence of temporal baseline on the vertical absolute accuracies of TSX HS interferometric DSMs: Case Study on Berlin.
In: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-7, [Conference or Workshop Item]

Schmidt, A. and Niemeyer, J. and Rottensteiner, F. and Soergel, U. (2014):
Contextual Classification of Full Waveform Lidar Data in the Wadden Sea.
In: Geoscience and remote sensing , IEEE, pp. 1614-1618, 11, (9), [Online-Edition: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6739...],
[Article]

Schmidt, A. and Soergel, U. (2013):
Monitoring and change detection of Wadden Sea areas using Lidar data.
In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Antalya, Turkey, 11-17 Nov. 2013, XL-7/W2, [Conference or Workshop Item]

Soergel, U. and Jacobsen, K. and Schack, L. (2013):
TanDEM-X Mission: Overview and evaluation of intermediate results.
In: IntArchPhRS, Antalya, Turkey, 40-7/W2, [Conference or Workshop Item]

W

Wegner, J. D. and Ziehn, J. R. and Soergel, U. (2013):
Combining high-resolution optical and InSAR features for height estimation of buildings with flat roofs.
In: Geoscience and Remote Sensing, IEEE, pp. 5840-5854, 52, (9), ISSN 0196-2892,
[Online-Edition: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=tru...],
[Article]

Wahome, V. W, and Kenduiywo, B. K. (2013):
Fuel station inventory mapping for data management and compliance enforcement.
In: ESRI Eastern Africa Education User Conference, [Article]

Y

Yang, C. H. and Soergel, U. (2015):
Rapid disaster analysis based on SAR techniques.
München, In: PIA15+HRIGI15 – Joint ISPRS conference 2015, 25–27 March 2015, [Online-Edition: http://www.pf.bgu.tum.de/isprs/pia15/pia15_prg.html],
[Conference or Workshop Item]

Yang, C. H. and Soergel, U. and Lanaras, Ch. and Baltsavias, E. and Remondino, F. and Wakabayashi, H. (2014):
Rapid Disaster Analysis based on Remote Sensing: A Case Study about the Tohoku Tsunami Disaster 2011.
In: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL-7, [Conference or Workshop Item]

This list was generated on Sun Oct 13 01:08:47 2019 CEST.