The processing chain and Cal/Val operations of the future hyperspectral satellite mission EnMAP

Müller, Rupert; Bachmann, Martin; Makasy, Christine; Miguel, Amaia de; Müller, Andreas; Neumann, Andreas; Palubinskas, Gintautas; Richter, Rudolf; Schneider, Mathias; Storch, Tobias; Walzel, Thomas; Kaufmann, Hermann; Guanter, Luis; Segl, Karl; Heege, Thomas; Kiselev, Viacheslav

doi:10.1109/aero.2010.5446973

Cited by 15 publications

(10 citation statements)

References 8 publications

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“…2. Being the spectral range not constant across all the spectra, each spectrum has been resampled to the 244 bands of the future EnMAP mission's sensor [12], spanning the interval 0.42-2.45 μm, as described in [13]. The dataset looks a difficult one at first sight, as in some occasions the spectra exhibit similar behaviour or overlap (Fig.…”

Section: Resultsmentioning

confidence: 99%

Compression-based unsupervised clustering of spectral signatures

Cerra

Bieniarz

Avbelj

et al. 2011

2011 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)

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This paper proposes to use compression-based similarity measures to cluster spectral signatures on the basis of their similarities. Such universal distances estimate the shared information between two objects by comparing their compression factors, which can be obtained by any standard compressor. Experiments on rocks categorization show that these methods may outperform traditional choices for spectral distances based on vector processing.

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Section: Resultsmentioning

confidence: 99%

Compression-based unsupervised clustering of spectral signatures

Cerra

Bieniarz

Avbelj

et al. 2011

2011 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)

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“…It comprises processor elements to generate quality information, quicklooks, water-land masks, cloud masks, tiling, correction of known effects like odd-even and nonuniformity, conversion to physical at-sensor radiance values, direct geo-referencing with image-to-image adjustment and atmospheric corrections separated for land and water surface applications. A detailed description of the EnMAP processing chain is available in [5].…”

Section: Data Processingmentioning

confidence: 99%

The EnMAP Mission: From Observation Request to Data Delivery

Habermeyer¹,

Pinnel²,

Storch³

et al. 2019

IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium

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EnMAP (Environmental Mapping and Analysis Program, www.enmap.org) is a German, Earth observing, imaging spectroscopy, spaceborne mission planned for launch in 2020. The data products will cover the spectral range from 420 nm to 2450 nm with a spectral sampling distance between 5 and 12 nm with an expected signal-to-noise-ratio of 400:1 in the visible near-infrared and 180:1 in the shortwave infrared parts of the electromagnetic spectrum. The resulting images will cover an area of 30 km in the acrosstrack direction with a ground sampling distance of 30 m. The across-track tilt-capability of 30° enables revisit times of less than four days. The resulting data products will be freely available to the scientific user community for measuring, deriving, and analyzing diagnostic parameters, which describe vital processes on the Earth's surface comprising agriculture, forestry, soil and geological environments, as well as coastal zones and inland waters. This work concentrates on the description of activities performed and facilities involved for the preparation of these products. It starts out by the description of the User Portals for observation requests and acquisition planning, touches the aspects of creating the time-lines, the commanding and controlling of the satellite, the downlink of the telemetry and payload data, the design of the processing chain and the archiving of data plus a set of activities flanking the above for the provision of high-quality data products.

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“…the FOV (Field-of-View) of 2.63 deg and the IFOV (Instantaneous Field-of-View) of 9.5 arcsec, also characterization data are considered which justify e.g. the MTF (Modular Transfer Function) of more than 0.25 at 60 m and more than 0.64 at 240 m. The geometric characterization and calibration is based on pre-flight simulations and measurements performed in the laboratory [3] and complemented by inflight measurements performed in vicarious characterization and calibration campaigns [1]. Direct Georeferencing…”

Section: Overview Of Conceptsmentioning

confidence: 99%

Pre- and in-flight geometric characterization and calibration concepts for the EnMAP mission

Storch¹,

Lenfert

Schneider³

et al. 2012

2012 IEEE International Geoscience and Remote Sensing Symposium

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The future hyperspectral satellite mission EnMAP (Environmental Mapping and Analysis Program; www.enmap.org) will substantially improve remote sensing standard products and generate new user-driven information products on the status and evolution of different ecosystems. The launch is planned for 2016 with mission operations of five years. This paper describes the EnMAP mission and focuses on the status and challenges of how to achieve the required accuracies in geometric correction which applies the method of direct georeferencing. The pre-flight activities including simulations and measurements complement the initial and routine in-flight activities. The concepts for geometric characterization and calibration are analyzed and how thereby the absolute geo-location accuracy and the co-registration between the two spectrometers are realized in the operational on-ground processing. One spectrometer covers the spectral range from 420 nm to 1000 nm and 900 nm to 2450 nm is covered by the other one.

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The processing chain and Cal/Val operations of the future hyperspectral satellite mission EnMAP

Cited by 15 publications

References 8 publications

Compression-based unsupervised clustering of spectral signatures

Compression-based unsupervised clustering of spectral signatures

The EnMAP Mission: From Observation Request to Data Delivery

Pre- and in-flight geometric characterization and calibration concepts for the EnMAP mission

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