The EnMAP Spaceborne Imaging Spectroscopy Mission for Earth Observation

By Luis Guanter, H. Kaufmann, K. Segl, S. Foerster, C. Rogass, S. Chabrillat, T. Küster, A. Hollstein, Godela Rossner, C. Chlebek and 26 more. Remote Sensing, 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.

Subfields: Artificial Intelligence, Ecology, Media Technology

View Paper: https://www.semanticscholar.org/paper/2f70864071399bf40309f43533245df79578affe

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Citations in the corpus

Advances in Hyperspectral Image and Signal Processing: A Comprehensive Overview of the State of the Art (2017, background): “Table 1 presents the principal parameters of seven spaceborne imaging spectroscopy missions planned for the near future: the China commercial remote-sensing satellite system, DLR Earth sensing imaging spectrometer (DESIS) [5], environmental mapping and analysis program [6], hyperspectral imager suit”
A Review of Change Detection in Multitemporal Hyperspectral Images: Current Techniques, Applications, and Challenges (2019, background): “However, the Precursore Iperspettrale della Missione Applicativa (PRISMA) [5] was launched on 21 March 2019 [85], and, in the near future, other satellite missions with HS sensors will follow, including ◗ HS Imager Suite (HISUI), planned for launch in 2019 [6] ◗ Environmental Mapping and Analysis Pr”
Linking earth observation and taxonomic, structural and functional biodiversity: local to ecosystem perspectives (2016, methodology): “…EO sensors with a spectral range of 0.4-2.5 m such as the airborne hyperspectral sensors HyMap, HySpex, HyMAP, AISA or EnMAP (Ansner 1998, 2015; Guanter et al., 2015) are very well suited to record different biochemicalbiophysical spectral traits (i.e. chlorophyll, xanthophyll, carotene or 322…”
Evaluation of the PROSAIL Model Capabilities for Future Hyperspectral Model Environments: A Review Study (2018, methodology): “Moreover, off-nadir pointing capabilities of the future sensor can be employed to enhance the data acquisition rate [22], improving seasonal monitoring of crop development through higher temporal sampling rate.”
Remote Sensing Techniques for Soil Organic Carbon Estimation: A Review (2019, background): “1, Proportion of land that is degraded over total land area and also might be useful to establish relevant policies [113,114] Potentially, SSLs could be a strong base for the forthcoming hyperspectral remote sensing of soils from space [115] as they might then be used for enhanced applications in su”
Seasonal variability of multiple leaf traits captured by leaf spectroscopy at two temperate deciduous forests. (2016, neutral): “A globally relevant algorithm for leaf traits that can be used by ground spectral observations (Hilker, Nesic, Coops, & Lessard, 2010), upcoming (e.g., EnMAP; Guanter et al., 2015) or existing or planned satellite missions such as NASA's HyspIRI mission (such as https://hyspiri.jpl.nasa. gov/; Lee e”
Feature Extraction for Hyperspectral Imagery: The Evolution From Shallow to Deep: Overview and Toolbox (2020, methodology): “For example, EnMAP (Environmental Monitoring and Analysis Program), which is a hyperspectral satellite mission, is planning to capture hyperspectral data with a maximum ground coverage of 5000 km × 30 km per day and the target revisit time of 4 days (±30◦) with 512 Gbit onboard mass memory [10].”