Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Rupert Muller"'
Autor:
Miguel Pato, Jim Buffat, Kevin Alonso, Stefan Auer, Emiliano Carmona, Stefan Maier, Rupert Muller, Patrick Rademske, Uwe Rascher, Hanno Scharr
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 18566-18576 (2024)
The successful operation of airborne and space-based spectrometers in recent years holds the promise to map solar-induced fluorescence (SIF) accurately across the globe. Machine learning (ML) can play an important role in this effort, but its applica
Externí odkaz:
https://doaj.org/article/25fa1da6f1dc4faeb86079d3589f0246
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 5514-5533 (2022)
In hyperspectral imagery, differences in ground surface structures cause a large variation in the optical scattering in sunlit and (partly) shadowed pixels. The complexity of the scene demands a general spectral mixture model that can adapt to the di
Externí odkaz:
https://doaj.org/article/edb0653a9d2240aaa3db6a4b0ccb9c90
Autor:
Uta Heiden, Pablo d’Angelo, Peter Schwind, Paul Karlshöfer, Rupert Müller, Simone Zepp, Martin Wiesmeier, Peter Reinartz
Publikováno v:
Remote Sensing, Vol 14, Iss 18, p 4526 (2022)
Reflectance composites that capture bare soil pixels from multispectral image data are increasingly being analysed to model soil constituents such as soil organic carbon. These temporal composites are used instead of single-date multispectral images
Externí odkaz:
https://doaj.org/article/06ecf99f7b8a45ab8e732afef950dc97
Autor:
Daniele Cerra, Miguel Pato, Kevin Alonso, Claas Köhler, Mathias Schneider, Raquel de los Reyes, Emiliano Carmona, Rudolf Richter, Franz Kurz, Peter Reinartz, Rupert Müller
Publikováno v:
Remote Sensing, Vol 13, Iss 13, p 2559 (2021)
Spectral unmixing represents both an application per se and a pre-processing step for several applications involving data acquired by imaging spectrometers. However, there is still a lack of publicly available reference data sets suitable for the val
Externí odkaz:
https://doaj.org/article/de27b5cb690844d2af4f8390a5e80cde
Publikováno v:
Remote Sensing, Vol 13, Iss 3, p 473 (2021)
The authors would like to make the following correction of [...]
Externí odkaz:
https://doaj.org/article/68fa34366ea946ca997e0f9e75fd69d6
Publikováno v:
Remote Sensing, Vol 12, Iss 23, p 3985 (2020)
Shadows are frequently observable in high-resolution images, raising challenges in image interpretation, such as classification and object detection. In this paper, we propose a novel framework for shadow detection and restoration of atmospherically
Externí odkaz:
https://doaj.org/article/8d6ae6ac7f19466aa742dbdf4902a295
Autor:
Raquel de los Reyes, Maximilian Langheinrich, Peter Schwind, Rudolf Richter, Bringfried Pflug, Martin Bachmann, Rupert Müller, Emiliano Carmona, Viktoria Zekoll, Peter Reinartz
Publikováno v:
Sensors, Vol 20, Iss 5, p 1428 (2020)
The atmospheric correction of satellite images based on radiative transfer calculations is a prerequisite for many remote sensing applications. The software package ATCOR, developed at the German Aerospace Center (DLR), is a versatile atmospheric cor
Externí odkaz:
https://doaj.org/article/2e81933125244f0f82269a78becd9aee
Publikováno v:
Remote Sensing, Vol 7, Iss 10, Pp 13190-13207 (2015)
This paper proposes the use of spectral unmixing and sparse reconstruction methods to restore a simulated dataset for the Environmental Mapping and Analysis Program (EnMAP), the forthcoming German spaceborne hyperspectral mission. The described metho
Externí odkaz:
https://doaj.org/article/b30775de8ad643519b9d40a440d1f5e1
Autor:
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
Publikováno v:
Remote Sensing, Vol 7, Iss 7, Pp 8830-8857 (2015)
Imaging spectroscopy, also known as hyperspectral remote sensing, is based on the characterization of Earth surface materials and processes through spectrally-resolved measurements of the light interacting with matter. The potential of imaging spectr
Externí odkaz:
https://doaj.org/article/1ff6855b9e1442db80abe20930fc32f7
Autor:
Kevin Alonso, Martin Bachmann, Kara Burch, Emiliano Carmona, Daniele Cerra, Raquel de los Reyes, Daniele Dietrich, Uta Heiden, Andreas Hölderlin, Jack Ickes, Uwe Knodt, David Krutz, Heath Lester, Rupert Müller, Mary Pagnutti, Peter Reinartz, Rudolf Richter, Robert Ryan, Ilse Sebastian, Mirco Tegler
Publikováno v:
Sensors, Vol 19, Iss 20, p 4471 (2019)
Imaging spectrometry from aerial or spaceborne platforms, also known as hyperspectral remote sensing, provides dense sampled and fine structured spectral information for each image pixel, allowing the user to identify and characterize Earth surface m
Externí odkaz:
https://doaj.org/article/6c26f96681454c3db775b14f71671687