The Enmap German Spaceborne Imaging Spectroscopy Mission: Update and Highlights of Recent Preparatory Activities

Chabrillat, Sabine; Guanter, Luis; Segl, Karl; Foerster, Saskia; Fischer, Sebastian; Rossner, Godela; Schickling, Anke; LaPorta, Laura; Honold, Hans‐Peter; Storch, Tobias

doi:10.1109/igarss39084.2020.9324006

Cited by 8 publications

(5 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, they can distort the estimated reflectance spectrum in visible wavelengths, harming snow or vegetation studies that rely on features in this spectral range. Solar illumination geometry in mountains affects current satellite imagery from Landsat 8/9 and Sentinel-2A/B, it affects data from imaging spectrometers EnMAP (Chabrillat et al, 2020) and EMIT (Connelly et al, 2021), and it will affect data from future missions SBG (Cawse-Nicholson et al, 2021;Stavros et al, 2022) and CHIME (Rast et al, 2021). Locally, fine-resolution DEMs will be available from lidar, InSAR, or structure-from-motion deployed from drones or aircraft, and slightly coarser DEMs will be available using structure-from-motion from spaceborne data.…”

Section: Discussionmentioning

confidence: 99%

Error and Uncertainty Degrade Topographic Corrections of Remotely Sensed Data

et al. 2022

View full text Add to dashboard Cite

Earth's mountain regions significantly influence the planet's climate, hydrology, ecology, and geology. Studying them with remote sensing requires that we compensate for the influence of topography on the reflection of solar radiation. Digital elevation models (DEMs) are used across scientific disciplines to understand topography's effect on the remotely sensed signal. Small errors in the estimates of elevation lead to larger errors in calculations of the solar illumination on the terrain and portions that are in shadow, thereby leading to misinterpretation of remotely sensed imagery from satellites and airplanes. Here, we present estimates of the errors and uncertainty in DEM retrievals, and we identify some outright mistakes. Compensating for uncertainty will inform algorithms that consider the effect of Earth's topography, improving the characterization from satellite missions of attributes of the planet's surface.

show abstract

Section: Discussionmentioning

confidence: 99%

Error and Uncertainty Degrade Topographic Corrections of Remotely Sensed Data

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Solar illumination geometry in mountains affects current satellite imagery from Landsat 8/9 and Sentinel-2A/B, it affects data from imaging spectrometers EnMAP (Chabrillat et al, 2020) and EMIT (Connelly et al, 2021), and it will affect data from future missions SBG (Cawse-Nicholson et al, 2021;Stavros et al, 2022) and CHIME (Rast et al, 2021). Locally, fine-resolution DEMs will be available from lidar, InSAR, or structure-frommotion deployed from drones or aircraft, and slightly coarser DEMs will be available using structure-from-motion from spaceborne data.…”

Section: Discussionmentioning

confidence: 99%

Error and Uncertainty Degrade Topographic Corrections of Remotely Sensed Data

Dozier

Bair

Baskaran

et al. 2022

Preprint

View full text Add to dashboard Cite

Chemical and biological composition of surface materials and physical structure and arrangement of those materials determine the intrinsic reflectance of Earth's land surface. The apparent reflectance-as measured by a spaceborne or airborne sensor that has been corrected for atmospheric attenuation-depends also on topography, surface roughness, and the atmosphere.Especially in Earth's mountains, estimating properties of scientific interest from remotely sensed data requires compensation for topography. Doing so requires information from digital elevation models (DEMs). Available DEMs with global coverage are derived from spaceborne interferometric radar and stereo-photogrammetry at ˜30 m spatial resolution. Locally or regionally, lidar altimetry, interferometric radar, or stereo-photogrammetry produces DEMs with finer resolutions. Characterization of their quality typically expresses the root-mean-square (RMS) error of the elevation, but the accuracy of remotely sensed retrievals is sensitive to uncertainties in topographic properties that affect incoming and reflected radiation and that are inadequately represented by the RMS error of the elevation. The most essential variables are the cosine of the local solar illumination angle on a slope, the shadows cast by neighboring terrain, and the view factor, the fraction of the overlying hemisphere open to the sky. Comparison of global DEMs with locally available fine-scale DEMs shows that calculations with the global products consistently underestimate the cosine of the solar angle and underrepresent shadows. Analyzing imagery of Earth's mountains from current and future spaceborne missions requires addressing the uncertainty introduced by errors in DEMs on algorithms that analyze remotely sensed data to produce information about Earth's surface.

show abstract

“…The Environmental Mapping and Analysis Program (EnMAP, www.enmap.org, accessed on 10 November 2021) is a spaceborne imaging spectroscopy mission under development and planned for launch in the first half-year of 2022 with an operational lifetime of 5 years [3,19]. The Space Agency of the German Aerospace Center (DLR) covers the mission management, and DLR'S Earth Observation Center (EOC) together with the German Space Operations Center (GSOC) are responsible for establishing and operating the ground segment [20].…”

Section: Overview Of the Enmap Missionmentioning

confidence: 99%

Analysis-Ready Data from Hyperspectral Sensors—The Design of the EnMAP CARD4L-SR Data Product

et al. 2021

Self Cite

View full text Add to dashboard Cite

Today, the ground segments of the Landsat and Sentinel missions provide a wealth of well-calibrated, characterized datasets which are already orthorectified and corrected for atmospheric effects. Initiatives such as the CEOS Analysis Ready Data (ARD) propose and ensure guidelines and requirements so that such datasets can readily be used, and interoperability within and between missions is a given. With the increasing availability of data from operational and research-oriented spaceborne hyperspectral sensors such as EnMAP, DESIS and PRISMA, and in preparation for the upcoming global mapping missions CHIME and SBG, the provision of analysis ready hyperspectral data will also be of increasing interest. Within this article, the design of the EnMAP Level 2A Land product is illustrated, highlighting the necessary processing steps for CEOS Analysis Ready Data for Land (CARD4L) compliant data products. This includes an overview of the design of the metadata, quality layers and archiving workflows, the necessary processing chain (system correction, orthorectification and atmospheric correction), as well as the resulting challenges of this procedure. Thanks to this operational approach, the end user will be provided with ARD products including rich metadata and quality information, which can readily be integrated in analysis workflows, and combined with data from other sensors.

show abstract

The Enmap German Spaceborne Imaging Spectroscopy Mission: Update and Highlights of Recent Preparatory Activities

Cited by 8 publications

References 4 publications

Error and Uncertainty Degrade Topographic Corrections of Remotely Sensed Data

Error and Uncertainty Degrade Topographic Corrections of Remotely Sensed Data

Error and Uncertainty Degrade Topographic Corrections of Remotely Sensed Data

Analysis-Ready Data from Hyperspectral Sensors—The Design of the EnMAP CARD4L-SR Data Product

Contact Info

Product

Resources

About