Clemens Eisank
Clemens Eisank
DVT - Daten-Verarbeitung-Tirol GmbH
No verified email
Title
Cited by
Cited by
Year
Automated parameterisation for multi-scale image segmentation on multiple layers
L Drăguţ, O Csillik, C Eisank, D Tiede
ISPRS Journal of photogrammetry and Remote Sensing 88, 119-127, 2014
5292014
Automated object-based classification of topography from SRTM data
L Drăguţ, C Eisank
Geomorphology 141, 21-33, 2012
1972012
Object representations at multiple scales from digital elevation models
L Drăguţ, C Eisank
Geomorphology 129 (3-4), 183-189, 2011
1562011
Local variance for multi-scale analysis in geomorphometry
L Drăguţ, C Eisank, T Strasser
Geomorphology 130 (3-4), 162-172, 2011
1152011
An object-based approach for semi-automated landslide change detection and attribution of changes to landslide classes in northern Taiwan
D Hölbling, B Friedl, C Eisank
Earth Science Informatics 8 (2), 327-335, 2015
822015
Assessment of multiresolution segmentation for delimiting drumlins in digital elevation models
C Eisank, M Smith, J Hillier
Geomorphology 214, 452-464, 2014
772014
An object-based workflow to extract landforms at multiple scales from two distinct data types
S d'Oleire-Oltmanns, C Eisank, L Drăgut, T Blaschke
IEEE Geoscience and Remote Sensing Letters 10 (4), 947-951, 2013
642013
Comparing manual and semi-automated landslide mapping based on optical satellite images from different sensors
D Hölbling, C Eisank, F Albrecht, F Vecchiotti, B Friedl, E Weinke, A Kociu
Geosciences 7 (2), 37, 2017
352017
Developing a semantic model of glacial landforms for object-based terrain classification–the example of glacial cirques
C Eisank, L Dragut, J Götz, T Blaschke
Proc. the International Archives of the Photogrammetry, Remote Sensing and …, 2010
332010
A generic procedure for semantics-oriented landform classification using object-based image analysis
C Eisank, L Drăguţ, T Blaschke
Geomorphometry 2011, 125-128, 2011
322011
Accounting for covariate distributions in slope-unit-based landslide susceptibility models. A case study in the alpine environment
G Amato, C Eisank, D Castro-Camilo, L Lombardo
Engineering geology 260, 105237, 2019
282019
Expert knowledge for object-based landslide mapping in Taiwan
C Eisank, D Hölbling, B Friedl, YC Chen, KT Chang
South-Eastern European Journal of Earth Observation and Geomatics 3 (2S …, 2014
182014
A comparison of methods to incorporate scale in geomorphometry
L Drăguţ, C Eisank, T Strasser, T Blaschke
Proceedings Geomorphometry, 133-139, 2009
162009
Comparing object-based landslide detection methods based on polarimetric SAR and optical satellite imagery—A case study in Taiwan
S Plank, D Hölbling, C Eisank, B Friedl, S Martinis, A Twele
Proceedings of the 7th International Workshop on Science and Applications of …, 2015
112015
Automated classification of topography from SRTM data using object-based image analysis
L Drăguţ, C Eisank
Geomorphometry, 7-9, 2011
112011
Semi-Global Matching of Pléiades tri-stereo imagery to generate detailed digital topography for high-alpine regions
C Eisank, L Rieg, C Klug, H Kleindienst, R Sailer
GI_Forum_2015–Geospatial Minds for Society, 168-177, 2015
102015
Terrain extraction in built-up areas from satellite stereo-imagery-derived surface models: a stratified object-based approach
F Luethje, D Tiede, C Eisank
ISPRS International Journal of Geo-Information 6 (1), 9, 2017
92017
Automated classification of topography from SRTM data using object-based image analysis
L Dragut, C Eisank
Geomorphometry. org, 2011
92011
User requirements for an Earth Observation (EO)-based landslide information web service
F Albrecht, D Hölbling, E Weinke, C Eisank
Landslides and Engineered Slopes. Experience, Theory and Practice, 301-308, 2018
72018
An object-based workflow for integrating spatial scale and semantics to derive landforms from digital elevation models
C Eisank
PhD thesis | Department of Geoinformatics - Z_GIS | University of Salzburg, 2013
52013
The system can't perform the operation now. Try again later.
Articles 1–20