2019
DOI: 10.3390/s19204471
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Data Products, Quality and Validation of the DLR Earth Sensing Imaging Spectrometer (DESIS)

Abstract: Imaging spectrometry from aerial or spaceborne platforms, also known as hyperspectral remote sensing, provides dense sampled and fine structured spectral information for each image pixel, allowing the user to identify and characterize Earth surface materials such as minerals in rocks and soils, vegetation types and stress indicators, and water constituents. The recently launched DLR Earth Sensing Imaging Spectrometer (DESIS) installed on the International Space Station (ISS) closes the long-term gap of sparsel… Show more

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Cited by 119 publications
(91 citation statements)
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“…The relative difference in surface reflectance between RadCalNet and DESIS is below 5% for wavelengths above 600 nm, while the relative difference increases up to 10% for shorter wavelengths (∼ 400-600 nm). This is consistent with DESIS results reported in [18], and it is explained as an overestimation of the AOT in remote sensing (AOT DESIS ∼0.25) from arid sites with respect to the measured value (AOT RCN = 0.035). However, comparisons with Sentinel-2 data (<30 min.…”
Section: Comparison Of Boa Surface Reflectance Between Multi-spectralsupporting
confidence: 92%
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“…The relative difference in surface reflectance between RadCalNet and DESIS is below 5% for wavelengths above 600 nm, while the relative difference increases up to 10% for shorter wavelengths (∼ 400-600 nm). This is consistent with DESIS results reported in [18], and it is explained as an overestimation of the AOT in remote sensing (AOT DESIS ∼0.25) from arid sites with respect to the measured value (AOT RCN = 0.035). However, comparisons with Sentinel-2 data (<30 min.…”
Section: Comparison Of Boa Surface Reflectance Between Multi-spectralsupporting
confidence: 92%
“…In order to minimize the effect of the uncertainty of the scene AOT calculation, and its effect on the accuracy of the surface reflectance, the AOT value measured on the RadCalNet sites at the time of the BOA measurements might be used as input for PACO's atmospheric correction algorithms (for validation purposes). New software possibilities, like AOT input (already explored in [18]), are handy to compare the surface reflectance from different sensors from these types of homogeneous but arid sites, where DDV-based AOT extraction algorithms can not be applied or they are under low retrieved statistics. The results presented in this study are consistent with the same L2A validation study on the commissioning data of DESIS hyperspectral [18] camera system.…”
Section: Discussionmentioning
confidence: 99%
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