Segl, K.[Karl]
* 2001: Detection of small objects from high-resolution panchromatic satellite imagery based on supervised image segmentation
* 2003: Fusion of spectral and shape features for identification of urban surface cover types using reflective and thermal hyperspectral data
* 2004: Edge- and region-based segmentation technique for the extraction of large, man-made objects in high-resolution satellite imagery
* 2009: ENMAP: The Future Hyperspectral Satellite Mission: Product Generation
* 2014: Reduction of Uncorrelated Striping Noise: Applications for Hyperspectral Pushbroom Acquisitions
* 2014: Robust Automated Image Co-Registration of Optical Multi-Sensor Time Series Data: Database Generation for Multi-Temporal Landslide Detection
* 2014: Simulation of Multitemporal and Hyperspectral Vegetation Canopy Bidirectional Reflectance Using Detailed Virtual 3-D Canopy Models
* 2015: EnMAP Spaceborne Imaging Spectroscopy Mission for Earth Observation, The
* 2015: Estimating the Influence of Spectral and Radiometric Calibration Uncertainties on EnMAP Data Products: Examples for Ground Reflectance Retrieval and Vegetation Indices
* 2015: S2eteS: An End-to-End Modeling Tool for the Simulation of Sentinel-2 Image Products
* 2015: Spectral Unmixing of Forest Crown Components at Close Range, Airborne and Simulated Sentinel-2 and EnMAP Spectral Imaging Scale
* 2016: EnGeoMAP 2.0: Automated Hyperspectral Mineral Identification for the German EnMAP Space Mission
* 2016: Improving Sensor Fusion: A Parametric Method for the Geometric Coalignment of Airborne Hyperspectral and Lidar Data
* 2016: Potential of Resolution-Enhanced Hyperspectral Data for Mineral Mapping Using Simulated EnMAP and Sentinel-2 Images
* 2016: Prediction of Common Surface Soil Properties Based on Vis-NIR Airborne and Simulated EnMAP Imaging Spectroscopy Data: Prediction Accuracy and Influence of Spatial Resolution
* 2016: Ready-to-Use Methods for the Detection of Clouds, Cirrus, Snow, Shadow, Water and Clear Sky Pixels in Sentinel-2 MSI Images
* 2017: AROSICS: An Automated and Robust Open-Source Image Co-Registration Software for Multi-Sensor Satellite Data
* 2017: Hyperspectral and Lidar Intensity Data Fusion: A Framework for the Rigorous Correction of Illumination, Anisotropic Effects, and Cross Calibration
* 2019: 3D hyperspectral point cloud generation: Fusing airborne laser scanning and hyperspectral imaging sensors for improved object-based information extraction
* 2023: First Retrievals of Surface and Atmospheric Properties Using EnMAP Measurements over Antarctica
* 2024: SNOWTRAN: A Fast Radiative Transfer Model for Polar Hyperspectral Remote Sensing Applications
Includes: Segl, K.[Karl] Segl, K.
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