Bringfried Pflug
German Aerospace Center
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Featured researches published by Bringfried Pflug.
Remote Sensing | 2017
Ferran Gascon; Catherine Bouzinac; Olivier Thépaut; Mathieu Jung; Benjamin Francesconi; Jérôme Louis; Vincent Lonjou; Bruno Lafrance; Stephane Massera; Angélique Gaudel-Vacaresse; Florie Languille; Bahjat Alhammoud; Françoise Viallefont; Bringfried Pflug; Jakub Bieniarz; Sébastien Clerc; Laëtitia Pessiot; Thierry Tremas; Enrico Cadau; Roberto de Bonis; Claudia Isola; Philippe Martimort
As part of the Copernicus programme of the European Commission (EC), the European Space Agency (ESA) has developed and is currently operating the Sentinel-2 mission that is acquiring high spatial resolution optical imagery. This article provides a description of the calibration activities and the status of the mission products validation activities after one year in orbit. Measured performances, from the validation activities, cover both Top-Of-Atmosphere (TOA) and Bottom-Of-Atmosphere (BOA) products. The presented results show the good quality of the mission products both in terms of radiometry and geometry and provide an overview on next mission steps related to data quality aspects.
Remote Sensing | 2016
Katja Dörnhöfer; Anna Göritz; Peter Gege; Bringfried Pflug; Natascha Oppelt
Satellite remote sensing may assist in meeting the needs of lake monitoring. In this study, we aim to evaluate the potential of Sentinel-2 to assess and monitor water constituents and bottom characteristics of lakes at spatio-temporal synoptic scales. In a field campaign at Lake Starnberg, Germany, we collected validation data concurrently to a Sentinel-2A (S2-A) overpass. We compared the results of three different atmospheric corrections, i.e., Sen2Cor, ACOLITE and MIP, with in situ reflectance measurements, whereof MIP performed best (r = 0.987, RMSE = 0.002 sr−1). Using the bio-optical modelling tool WASI-2D, we retrieved absorption by coloured dissolved organic matter (aCDOM(440)), backscattering and concentration of suspended particulate matter (SPM) in optically deep water; water depths, bottom substrates and aCDOM(440) were modelled in optically shallow water. In deep water, SPM and aCDOM(440) showed reasonable spatial patterns. Comparisons with in situ data (mean: 0.43 m−1) showed an underestimation of S2-A derived aCDOM(440) (mean: 0.14 m−1); S2-A backscattering of SPM was slightly higher than backscattering from in situ data (mean: 0.027 m−1 vs. 0.019 m−1). Chlorophyll-a concentrations (~1 mg·m−3) of the lake were too low for a retrieval. In shallow water, retrieved water depths exhibited a high correlation with echo sounding data (r = 0.95, residual standard deviation = 0.12 m) up to 2.5 m (Secchi disk depth: 4.2 m), though water depths were slightly underestimated (RMSE = 0.56 m). In deeper water, Sentinel-2A bands were incapable of allowing a WASI-2D based separation of macrophytes and sediment which led to erroneous water depths. Overall, the results encourage further research on lakes with varying optical properties and trophic states with Sentinel-2A.
Remote Sensing | 2018
Georgia Doxani; Eric F. Vermote; Jean-Claude Roger; Ferran Gascon; Stefan Adriaensen; David Frantz; Olivier Hagolle; André Hollstein; Grit Kirches; Fuqin Li; Jérôme Louis; Antoine Mangin; Nima Pahlevan; Bringfried Pflug; Quinten Vanhellemont
The Atmospheric Correction Inter-comparison eXercise (ACIX) is an international initiative with the aim to analyse the Surface Reflectance (SR) products of various state-of-the-art atmospheric correction (AC) processors. The Aerosol Optical Thickness (AOT) and Water Vapour (WV) are also examined in ACIX as additional outputs of an AC processing. In this paper, the general ACIX framework is discussed; special mention is made of the motivation to initiate this challenge, the inter-comparison protocol and the principal results. ACIX is free and open and every developer was welcome to participate. Eventually, 12 participants applied their approaches to various Landsat-8 and Sentinel-2 image datasets acquired over sites around the world. The current results diverge depending on the sensors, products and sites, indicating their strengths and weaknesses. Indeed, this first implementation of processor inter-comparison was proven to be a good lesson for the developers to learn the advantages and limitations of their approaches. Various algorithm improvements are expected, if not already implemented, and the enhanced performances are yet to be investigated in future ACIX experiments.
Image and Signal Processing for Remote Sensing XXIII | 2017
Magdalena Main-Knorn; Bringfried Pflug; Jérôme Louis; Vincent Debaecker; Uwe Müller-Wilm; Ferran Gascon
In the frame of the Copernicus programme, ESA has developed and launched the Sentinel-2 optical imaging mission that delivers optical data products designed to feed downstream services mainly related to land monitoring, emergency management and security. The Sentinel-2 mission is the constellation of two polar orbiting satellites Sentinel-2A and Sentinel-2B, each one equipped with an optical imaging sensor MSI (Multi-Spectral Instrument). Sentinel-2A was launched on June 23rd, 2015 and Sentinel-2B followed on March 7th, 2017. With the beginning of the operational phase the constellation of both satellites enable image acquisition over the same area every 5 days or less. To use unique potential of the Sentinel-2 data for land applications and ensure the highest quality of scientific exploitation, accurate correction of satellite images for atmospheric effects is required. Therefore the atmospheric correction processor Sen2Cor was developed by Telespazio VEGA Deutschland GmbH on behalf of ESA. Sen2Cor is a Level-2A processor which main purpose is to correct single-date Sentinel-2 Level-1C Top-Of-Atmosphere (TOA) products from the effects of the atmosphere in order to deliver a Level-2A Bottom-Of-Atmosphere (BOA) reflectance product. Additional outputs are an Aerosol Optical Thickness (AOT) map, a Water Vapour (WV) map and a Scene Classification (SCL) map with Quality Indicators for cloud and snow probabilities. Telespazio France and DLR have teamed up in order to provide the calibration and validation of the Sen2Cor processor. Here we provide an overview over the Sentinel-2 data, processor and products. It presents some processing examples of Sen2Cor applied to Sentinel-2 data, provides up-to-date information about the Sen2Cor release status and recent validation results at the time of the SPIE Remote Sensing 2017.
Remote Sensing of Clouds and the Atmosphere XIX; and Optics in Atmospheric Propagation and Adaptive Systems XVII | 2014
Bringfried Pflug; Magdalena Main-Knorn
Atmospheric correction of satellite images is necessary for many applications of remote sensing, i.e. computation of vegetation indices and biomass estimation. The largest uncertainty in atmospheric correction arises out of spatial and temporal variation of aerosol amount and type. Therefore validation of aerosol estimation is one important step in validation of atmospheric correction algorithms. Our ground-based measurements of aerosol-optical thickness spectra (AOT) were performed synchronously to overpasses of satellites Rapid-Eye and Landsat. Validation of aerosol retrieval by the widely used atmospheric correction tool ATCOR1,2 was then realized by comparison of AOT derived from satellite data with the ground-truths. Mean uncertainty is ΔAOT550 ≈ 0.04, corresponding approximately to uncertainty in surface albedo of Δρ ≈ 0.004. Generally, ATCOR-derived AOT values are mostly overestimated when compared to the ground-truth measurements. Very little differences are found between Rapid-Eye and Landsat sensors. Differences between using rural and maritime aerosols are negligible within the visible spectral range.
Remote Sensing of Clouds and the Atmosphere XIV | 2009
Bringfried Pflug
Radiance measurements within the O2A-absorption band contain information about height distribution of scattering particles. This is widely used for estimation of cloud-top height from satellite data. Within cloud free scenes over the ocean, there is still enough information contained for separation of aerosol loading within the maritime boundary layer and enhanced aerosol loading in the upper troposphere or stratosphere. If stratospheric aerosol content is low, then thin cirrus clouds can be observed. Alternatively, a volcanic ash cloud within the stratosphere or upper troposphere can be investigated after volcanic eruptions. This is demonstrated within this paper by one application example.
Remote Sensing | 1998
Harald Krawczyk; Bringfried Pflug; Birgit Gerasch
Satellite remote sensing of atmospheric properties is important for investigation of atmospheric pollution and also for remote sensing of the underlying surface, where an atmospheric correction is needed. For the proof of new methodological concepts the multispectral imaging spectrometer MOS was developed in the DLR Institute of Space Sensor Technology and launched on the Indian satellite IRS- P3. It has 13 bands in the VIS/NIR region with 10nm bandwidth. MOS successfully provides data for more than 2 years over European and Northern African coasts. The paper will introduce a standard atmospheric correction scheme for MOS data over water regions using measurements in the near IR form 685 nm to 1000 nm. This method is based on a 2- channel correction, estimating the aerosol optical depth and the Angstrom coefficient for the spectral behavior of the optical thickness. After extrapolation of the visible region the atmospheric correction is applied. Examples will be shown from the Baltic and North Sea regions. The obtained result will be compared and discussed with available in situ measurements taken simultaneously with MOS overflights. Lastly, this algorithm is applied to an observation of forest fire smoke over Malaysia.
Remote Sensing of Environment | 2014
Theresa Mannschatz; Bringfried Pflug; Erik Borg; Karl-Heinz Feger; Peter Dietrich
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences | 2015
Bringfried Pflug; Magdalena Main-Knorn; Aliaksei Makarau; Rudolf Richter
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences | 2015
Magdalena Main-Knorn; Bringfried Pflug; Vincent Debaecker; Jérôme Louis