H
Hermann Kaufmann
Researcher at University of Potsdam
Publications - 137
Citations - 4475
Hermann Kaufmann is an academic researcher from University of Potsdam. The author has contributed to research in topics: Hyperspectral imaging & EnMAP. The author has an hindex of 35, co-authored 131 publications receiving 3977 citations.
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Journal ArticleDOI
The EnMAP Spaceborne Imaging Spectroscopy Mission for Earth Observation
Luis Guanter,Hermann Kaufmann,Karl Segl,Saskia Foerster,Christian Rogass,Sabine Chabrillat,Theres Kuester,André Hollstein,Godela Rossner,Christian Chlebek,Christoph Straif,Sebastian Fischer,Stefanie Schrader,Tobias Storch,Uta Heiden,Andreas Mueller,Martin Bachmann,Helmut Mühle,Rupert Müller,Martin Habermeyer,Andreas Ohndorf,Joachim Hill,Henning Buddenbaum,Patrick Hostert,Sebastian van der Linden,Pedro J. Leitão,Andreas Rabe,Roland Doerffer,Hajo Krasemann,Hongyan Xi,Wolfram Mauser,Tobias Hank,Matthias Locherer,Michael Rast,Karl Staenz,Bernhard Sang +35 more
TL;DR: An overview of the main characteristics and current status of the EnMAP mission is provided, which will contribute to the development and exploitation of spaceborne imaging spectroscopy applications by making high-quality data freely available to scientific users worldwide.
Journal ArticleDOI
Determination of Chlorophyll Content and Trophic State of Lakes Using Field Spectrometer and IRS-1C Satellite Data in the Mecklenburg Lake District, Germany
Sabine Thiemann,Hermann Kaufmann +1 more
TL;DR: In this paper, a multitemporal data sets of the LISS-III sensor mounted on the Indian Remote Sensing Satellite (IRS-1C) and field reflectance spectra have been evaluated for estimating chlorophyll-a content in lakes.
Journal ArticleDOI
Comparison of Topographic Correction Methods
TL;DR: A comparison of topographic correction methods is conducted for Landsat-5 TM, Lands at-7 ETM+, and SPOT-5 imagery from different geographic areas and seasons, finding no method is superior in all cases.
Journal ArticleDOI
Determination of robust spectral features for identification of urban surface materials in hyperspectral remote sensing data
TL;DR: A new approach for the determination and evaluation of spectral features that are robust against spectral overlap between material classes and within-class variability is proposed and indicates that robust spectral features yield the potential for unsupervised detection of endmembers in hyperspectral image data.
Journal ArticleDOI
Automated differentiation of urban surfaces based on airborne hyperspectral imagery
TL;DR: The results and their comparison with standard spectral classification methods show that the new pixel- and contest-based approach enables reasonable material-oriented differentiation of urban surfaces.