The EnMAP hyperspectral imager—An advanced optical payload for future applications in Earth observation programmes

Stuffler, T.; Kaufmann, C.; Höfer, Stefan; Förster, Klaus; Schreier, Günter; Mueller, Andreas; Eckardt, Andreas; Bach, Heike; Penné, B.; Benz, U.; Haydn, R.

doi:10.1016/j.actaastro.2007.01.033

Cited by 160 publications

(95 citation statements)

References 2 publications

(1 reference statement)

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“…When pointing at nadir, the ground sampling distance is 30 m resulting in a swath width of 30 km. For a detailed description of the mission, the instrument and the ground segment, the reader is referred to e.g., [12,13] and the publications within this special issue (e.g., [14]). …”

Section: Enmap System Requirementsmentioning

confidence: 99%

Estimating the Influence of Spectral and Radiometric Calibration Uncertainties on EnMAP Data Products—Examples for Ground Reflectance Retrieval and Vegetation Indices

et al. 2015

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As part of the EnMAP preparation activities this study aims at estimating the uncertainty in the EnMAP L2A ground reflectance product using the simulated scene of Barrax, Spain. This dataset is generated using the EnMAP End-to-End Simulation tool, providing a realistic scene for a well-known test area. Focus is set on the influence of the expected radiometric calibration stability and the spectral calibration stability. Using a Monte-Carlo approach for uncertainty analysis, a larger number of realisations for the radiometric and spectral calibration are generated. Next, the ATCOR atmospheric correction is conducted for the test scene for each realisation. The subsequent analysis of the generated ground reflectance products is carried out independently for the radiometric and the spectral case. Findings are that the uncertainty in the L2A product is wavelength-dependent, and, due to the coupling with the estimation of atmospheric parameters, also spatially variable over the scene. To further illustrate the impact on subsequent data analysis, the influence on two vegetation indices is briefly analysed. Results show that the radiometric and spectral stability both have a high impact on the uncertainty of the narrow-band Photochemical Reflectance Index (PRI), and also the broad-band Normalized Difference Vegetation Index (NDVI) is affected.

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Section: Enmap System Requirementsmentioning

confidence: 99%

Estimating the Influence of Spectral and Radiometric Calibration Uncertainties on EnMAP Data Products—Examples for Ground Reflectance Retrieval and Vegetation Indices

et al. 2015

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“…Earth observing (EO) satellites, endowed with a high temporal resolution, enable the retrieval and hence monitoring of plant biophysical parameters [1][2][3]. With the forthcoming super-spectral Copernicus' Sentinel-2 [4] and Sentinel-3 missions [5] as well as the planned EnMAP [6], HyspIRI [7] and PRISMA [8] imaging spectrometer missions, an unprecedented data stream becomes available. This data influx requires processing techniques, which are reproducible, accurate and fast, when the retrieval of information on plant growth and health status is envisaged.…”

Section: Introductionmentioning

confidence: 99%

On the Semi-Automatic Retrieval of Biophysical Parameters Based on Spectral Index Optimization

et al. 2014

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Regression models based on spectral indices are typically empirical formulae enabling the mapping of biophysical parameters derived from Earth Observation (EO) data. Due to its empirical nature, it remains nevertheless uncertain to what extent a selected regression model is the most appropriate one, until all band combinations and curve fitting functions are assessed. This paper describes the application of a Spectral Index (SI) assessment toolbox in the Automated Radiative Transfer Models Operator (ARTMO) package. ARTMO enables semi-automatic retrieval and mapping of biophysical parameters from optical remote sensing observations. The SI toolbox facilitates the assessment of biophysical parameter retrieval accuracy of established as well as new and generic SIs. For instance, based on the SI formulation used, all possible band combinations of formulations with up to ten bands can be defined and evaluated. Several options are available in the SI assessment: calibration/validation data partitioning, the addition of noise and the definition of curve fitting models. To illustrate its functioning, all two-band combinations according to simple ratio (SR) and normalized difference (ND) formulations as well as various fitting functions (linear, exponential, power, logarithmic, polynomial) functions led to similar best correlations, though spatial differences emerged when applying the functions to HyMap imagery. We suggest that a systematic SI assessment is a strong requirement in the quality assurance approach for accurate biophysical parameter retrieval.

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“…Overall, those experimental systems are playing an important role as precursors for operational spaceborne imaging spectroscopy missions, but the amount and quality of data are unfortunately insufficient for a wide range of potential application fields of imaging spectroscopy. The Environmental Mapping and Analysis Program (EnMAP) German imaging spectroscopy mission [38][39][40][41] is intended to cover this gap in spaceborne imaging spectroscopy for Earth observation. EnMAP is a joint response of German Earth observation research institutions, value-added resellers and space industry to the increasing demand for accurate, quantitative information about the status and evolution of terrestrial ecosystems.…”

Section: Introductionmentioning

confidence: 99%

The EnMAP Spaceborne Imaging Spectroscopy Mission for Earth Observation

et al. 2015

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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 spectroscopy for Earth remote sensing has been demonstrated since the 1980s. However, most of the developments and applications in imaging spectroscopy have largely relied on airborne spectrometers, as the amount and quality of space-based imaging spectroscopy data remain relatively low to date. The upcoming Environmental Mapping and Analysis Program (EnMAP) German imaging spectroscopy mission is intended to fill this gap. An overview of the main characteristics and current status of the mission is provided in this contribution. The core payload of EnMAP consists of a dual-spectrometer instrument measuring in the optical spectral range between 420 and 2450 nm with a spectral sampling distance varying between 5 and 12 nm and a reference signal-to-noise ratio of 400:1 in the visible and near-infrared and 180:1 in the shortwave-infrared parts of the spectrum. EnMAP images will cover a 30 km-wide area in the across-track direction with a ground sampling distance of 30 m. An across-track tilted observation capability will enable a target revisit time of up to four days at the Equator and better at high latitudes. EnMAP 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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The EnMAP hyperspectral imager—An advanced optical payload for future applications in Earth observation programmes

Cited by 160 publications

References 2 publications

Estimating the Influence of Spectral and Radiometric Calibration Uncertainties on EnMAP Data Products—Examples for Ground Reflectance Retrieval and Vegetation Indices

Estimating the Influence of Spectral and Radiometric Calibration Uncertainties on EnMAP Data Products—Examples for Ground Reflectance Retrieval and Vegetation Indices

On the Semi-Automatic Retrieval of Biophysical Parameters Based on Spectral Index Optimization

The EnMAP Spaceborne Imaging Spectroscopy Mission for Earth Observation

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