The Spaceborne Imaging Spectrometer Desis: Data Access and Scientific Applications

Müller, Rupert; Alonso, Kevin; Bachmann, Martin; Burch, Kara; Carmona, E.; Cerra, Daniele; Dietrich, Daniele; Gege, Peter; Lester, Heath; Heiden, Uta; Holzwarth, Stefanie; Knodt, Uwe; Krutz, David; Marshall, David; Pato, Miguel; Reyes, R. de los; Reinartz, Peter; Tegler, Mirco

doi:10.1109/igarss47720.2021.9554912

Cited by 2 publications

(6 citation statements)

References 11 publications

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“…The DESIS hyperspectral sensor [16] was collaboratively designed by the German Aerospace Center and Teledyne Brown Engineering [25], [33]- [35]. DESIS, a pushbroom sensor, was launched and integrated onto the Multi-User System for Earth Sensing (MUSES) platform of the International Space Station (ISS) in 2018 [33], [34], [36], [37]. It has 235 bands with 2.55 nm bandwidth from 400 to 1000 nm and a spatial resolution of 30 m [37].…”

Section: A Desismentioning

confidence: 99%

“…DESIS, a pushbroom sensor, was launched and integrated onto the Multi-User System for Earth Sensing (MUSES) platform of the International Space Station (ISS) in 2018 [33], [34], [36], [37]. It has 235 bands with 2.55 nm bandwidth from 400 to 1000 nm and a spatial resolution of 30 m [37]. Its signal to noise ratio without binning is 195 [37].…”

Section: A Desismentioning

confidence: 99%

“…It has 235 bands with 2.55 nm bandwidth from 400 to 1000 nm and a spatial resolution of 30 m [37]. Its signal to noise ratio without binning is 195 [37]. The Level 2A DESIS product is atmospherically corrected, terrain corrected, and includes several masks including water, cloud, cloud shadow, and haze [37].…”

Section: A Desismentioning

confidence: 99%

“…The Level 2A DESIS product is atmospherically corrected, terrain corrected, and includes several masks including water, cloud, cloud shadow, and haze [37]. Users can access these data through the Earth Sensor Portal at Teledyne, where they can task new data acquisitions, or through the Earth Observation (EOWEB) GeoPortal, where they can browse archived data [16], [37]. DESIS data have been used for various applications including agricultural crop types [25], [37]- [45].…”

Section: A Desismentioning

confidence: 99%

“…Users can access these data through the Earth Sensor Portal at Teledyne, where they can task new data acquisitions, or through the Earth Observation (EOWEB) GeoPortal, where they can browse archived data [16], [37]. DESIS data have been used for various applications including agricultural crop types [25], [37]- [45].…”

Section: A Desismentioning

confidence: 99%

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New Generation Hyperspectral Data From DESIS Compared to High Spatial Resolution PlanetScope Data for Crop Type Classification

Aneece

Foley

Thenkabail

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Thoroughly investigating the characteristics of new generation hyperspectral and high spatial resolution spaceborne sensors will advance the study of agricultural crops. Therefore, we compared the performances of hyperspectral Deutsches Zentrum fur Luft -und Raumfahrt-(DLR) Earth Sensing Imaging Spectrometer (DESIS) and high spatial resolution PlanetScope in classifying eight crop types in California's Central Valley during the 2020 growing season. The DESIS sensor onboard the International Space Station collects data at 235 hyperspectral narrowbands (HNB) each with 2.55 nm bandwidth from 400-1000 nm and 30 m spatial resolution. In contrast, PlanetScope Dove-R data have 4 multispectral broadbands (MBB) with 3-4 m spatial resolution. We obtained best classification accuracies using 14 DESIS HNB from the August 2020 image, with an overall accuracy of 85% and producer's and user's accuracies of 72-100% and 75-100% respectively for the eight crops. The best classification accuracies using PlanetScope data were obtained using an image mosaic pair from June and August 2020; this resulted in an overall accuracy of 79% and producer's and user's accuracies of 56-100% and 61-100% respectively. Combining the best 14 DESIS HNB from August 2020 with the 4 PlanetScope MBB from August 2020 yielded an overall accuracy of 82% and producer's and user's accuracies of 65-100% and 60-94% respectively. On one-to-one single date comparisons of DESIS versus PlanetScope data, the hyperspectral data always outperformed high spatial resolution data in crop type classification. Nevertheless, high spatial resolution data will remain invaluable in assessing withinfield variability and crop biophysical/biochemical modeling in precision agriculture.

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Section: A Desismentioning

confidence: 99%

Section: A Desismentioning

confidence: 99%

Section: A Desismentioning

confidence: 99%

Section: A Desismentioning

confidence: 99%

Section: A Desismentioning

confidence: 99%

See 3 more Smart Citations

New Generation Hyperspectral Data From DESIS Compared to High Spatial Resolution PlanetScope Data for Crop Type Classification

Aneece

Foley

Thenkabail

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Robust and Reconfigurable On-Board Processing for a Hyperspectral Imaging Small Satellite

et al. 2023

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Hyperspectral imaging is a powerful remote sensing technology, but its use in space is limited by the large volume of data it produces, which leads to a downlink bottleneck. Therefore, most payloads to date have been oriented towards demonstrating the scientific usefulness of hyperspectral data sporadically over diverse areas rather than detailed monitoring of spatio-spectral dynamics. The key to overcoming the data bandwidth limitation is to process the data on-board the satellite prior to downlink. In this article, the design, implementation, and in-flight demonstration of the on-board processing pipeline of the HYPSO-1 cube-satellite are presented. The pipeline provides not only flexible image processing but also reliability and resilience, characterized by robust booting and updating procedures. The processing time and compression rate of the simplest pipeline, which includes capturing, binning, and compressing the image, are analyzed in detail. Based on these analyses, the implications of the pipeline performance on HYPSO-1’s mission are discussed.

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The Spaceborne Imaging Spectrometer Desis: Data Access and Scientific Applications

Cited by 2 publications

References 11 publications

New Generation Hyperspectral Data From DESIS Compared to High Spatial Resolution PlanetScope Data for Crop Type Classification

New Generation Hyperspectral Data From DESIS Compared to High Spatial Resolution PlanetScope Data for Crop Type Classification

Robust and Reconfigurable On-Board Processing for a Hyperspectral Imaging Small Satellite

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