S
Sebastian van der Linden
Researcher at University of Greifswald
Publications - 67
Citations - 3794
Sebastian van der Linden is an academic researcher from University of Greifswald. The author has contributed to research in topics: Hyperspectral imaging & Land cover. The author has an hindex of 23, co-authored 63 publications receiving 2910 citations. Previous affiliations of Sebastian van der Linden include Humboldt University of Berlin & University of Bonn.
Papers
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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.
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Sensitivity of Support Vector Machines to Random Feature Selection in Classification of Hyperspectral Data
TL;DR: Experimental results clearly demonstrate that the generation of an SVM-based classifier system with RFS significantly improves overall classification accuracy as well as producer's and user's accuracies.
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Cross-border Comparison of Post-socialist Farmland Abandonment in the Carpathians
Tobias Kuemmerle,Patrick Hostert,Volker C. Radeloff,Sebastian van der Linden,Kajetan Perzanowski,Ivan Kruhlov +5 more
TL;DR: In this article, the authors developed a change detection method based on support vector machines (SVM) to map farmland abandonment in the border triangle of Poland, Slovakia, and Ukraine in the Carpathians from Landsat TM/ETM+ images from 1986, 1988, and 2000.
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Remote sensing of sun-induced fluorescence to improve modeling of diurnal courses of gross primary production (GPP)
Alexander Damm,Jan Elbers,André Erler,Beniamino Gioli,Karim Hamdi,Ronald Hutjes,Martina Košvancová,Michele Meroni,Franco Miglietta,André Moersch,Jose Moreno,Anke Schickling,Ruth Sonnenschein,Thomas Udelhoven,Sebastian van der Linden,Patrick Hostert,Uwe Rascher +16 more
TL;DR: In this paper, the authors showed that including sun-induced fluorescence into modeling approaches improves their results in predicting diurnal courses of gross primary production (GPP) and photochemical reflectance index of corn.
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A Pixel-Based Landsat Compositing Algorithm for Large Area Land Cover Mapping
TL;DR: This study presents a compositing algorithm that facilitates creating cloud free, seasonally and radiometrically consistent datasets from the Landsat archive, allowing for regional to global LULCC mapping at high spatial resolutions.