EnMAP radiometric inflight calibration, post-launch product validation, and instrument characterization activities

This study reports the calibration and validation activities for the Environmental Mapping and Analysis Program (EnMAP; www.enmap.org). EnMAP is a German imaging spectroscopy satellite mission with the declared goal to investigate the Earth's surface with a so far surpassing quality. The key scientific questions to which EnMAP will contribute are related to climate change impacts, land cover changes and processes, natural resources, biodiversity and ecosystems, water availability and quality, geohazards and risk management. The satellite operates in a sun synchronous orbit in 650 km height with a local time of the descending node set to 11:00 and an across tilt opportunity to improve the local revisit time. Two pushbroom spectrometers with 242 channels in total cover the spectral range from 420 nm to 2450 nm with a mean resolution of 6.5 nm in the visible and 10 nm in the shortwave-infrared. The ground nadir pixel size is 30 m and 1000 spatial pixels generate a swath with of 30 km. For the CalVal activities, the routine calibration is conducted within the ground segment of DLR, while the independent validation activities are lead by GFZ. Data is operationally processed on-ground to standardized calibrated products and delivered to the international user community [1]. Standardized data products will comprise radiance and reflectance products that make use of calibration information gained pre- and inflight. To ensure high quality standards, additional independent product validation activities are planned.

[1]  T. Eck,et al.  Variability of Absorption and Optical Properties of Key Aerosol Types Observed in Worldwide Locations , 2002 .

[2]  Luis Alonso,et al.  Scene-based spectral calibration assessment of high spectral resolution imaging spectrometers. , 2009, Optics express.

[3]  U. Benz,et al.  The EnMAP hyperspectral imager—An advanced optical payload for future applications in Earth observation programmes , 2006 .

[4]  Hermann Kaufmann,et al.  Performance of correlation approaches for the evaluation of spatial distortion reductions , 2013 .

[5]  Matthijs C. Dorst.  Distinctive Image Features from Scale-Invariant Keypoints , 2011 .

[6]  Frank Fell,et al.  Numerical simulation of the light field in the atmosphere–ocean system using the matrix-operator method , 2001 .

[7]  Tobias Storch,et al.  THE FUTURE SPACEBORNE HYPERSPECTRAL IMAGER ENMAP: ITS IN-FLIGHT RADIOMETRIC AND GEOMETRIC CALIBRATION CONCEPT , 2012 .

[8]  M. Razinger,et al.  Aerosol analysis and forecast in the European Centre for Medium‐Range Weather Forecasts Integrated Forecast System: 2. Data assimilation , 2009 .

[9]  A. Smirnov,et al.  AERONET-a federated instrument network and data archive for aerosol Characterization , 1998 .

[10]  Luis Guanter,et al.  Reduction of Uncorrelated Striping Noise - Applications for Hyperspectral Pushbroom Acquisitions , 2014, Remote. Sens..

[11]  André Hollstein,et al.  Radiative transfer solutions for coupled atmosphere ocean systems using the matrix operator technique , 2012 .

[12]  Kurtis J. Thome,et al.  Vicarious Radiometric Calibrations of EOS Sensors , 1996 .

[13]  Rene Preusker,et al.  k-bin and k-IR: k-distribution methods without correlation approximation for non-fixed instrument re , 2014 .

[14]  P. Koepke,et al.  Optical Properties of Aerosols and Clouds: The Software Package OPAC , 1998 .

[15]  M. S. Moran,et al.  Reflectance- and radiance-based methods for the in-flight absolute calibration of multispectral sensors , 1987 .

[16]  J. Thepaut,et al.  The ERA‐Interim reanalysis: configuration and performance of the data assimilation system , 2011 .

[17]  Hermann Kaufmann,et al.  Data Quality Assurance for hyperspectral L1 and L2 products - Cal/Val/Mon procedures within the EnMAP Ground Segment , 2014 .

[18]  Robert O. Green,et al.  On-orbit radiometric and spectral calibration characteristics of EO-1 Hyperion derived with an underflight of AVIRIS and in situ measurements at Salar de Arizaro, Argentina , 2003, IEEE Trans. Geosci. Remote. Sens..

[19]  A. Sterl,et al.  The ERA‐40 re‐analysis , 2005 .

[20]  Dennis L. Helder,et al.  Landsat-5 TM and Landsat-7 ETM+ absolute radiometric calibration using the reflectance-based method , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[21]  Angela Lausch,et al.  Reduction of Radiometric Miscalibration—Applications to Pushbroom Sensors , 2011, Sensors.