Cross-sensor calibration and validation between DESIS and HISUI Hyperspectral Imager on the International Space Station (ISS)

Yamamoto, Hirokazu; Obata, Kenta; Tsuchida, Seigi; Kerr, Grégoire; Bachmann, Martin

doi:10.1109/igarss.2016.7729496

Cited by 3 publications

(4 citation statements)

References 8 publications

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“…In this context, it is worth pointing out that, with the upcoming launch of HISUI, two additional imaging spectrometers will be mounted on the ISS, so that simultaneous data acquisitions from the same platforms will become possible, facilitating cross-validation and cross-calibration activities [89]. In addition, the spectrometers of the Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder mission, which will be installed on the ISS around 2023 [24], will allow for new possibilities of highly accurate cross-calibration.…”

Section: Application Fields Of Desismentioning

confidence: 99%

Data Products, Quality and Validation of the DLR Earth Sensing Imaging Spectrometer (DESIS)

Alonso¹,

Bachmann

Burch

et al. 2019

Sensors

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117

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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 sparsely available spaceborne imaging spectrometry data and will be part of the upcoming fleet of such new instruments in orbit. DESIS measures in the spectral range from 400 and 1000 nm with a spectral sampling distance of 2.55 nm and a Full Width Half Maximum (FWHM) of about 3.5 nm. The ground sample distance is 30 m with 1024 pixels across track. In this article, a detailed review is given on the applicability of DESIS data based on the specifics of the instrument, the characteristics of the ISS orbit, and the methods applied to generate products. The various DESIS data products available for users are described with the focus on specific processing steps. The results of the data quality and product validation studies show that top-of-atmosphere radiance, geometrically corrected, and bottom-of-atmosphere reflectance products meet the mission requirements. The limitations of the DESIS data products are also subject to a critical examination.

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Section: Application Fields Of Desismentioning

confidence: 99%

Data Products, Quality and Validation of the DLR Earth Sensing Imaging Spectrometer (DESIS)

Alonso¹,

Bachmann

Burch

et al. 2019

Sensors

Self Cite

117

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show abstract

“…For example, the German hyperspectral sensor onboard the ISS, DESIS, provides radiance products [2]. Intercalibration between HISUI and DESIS [7] requires the radiance-to-radiance conversion of the spectral band adjustment, and the uncertainty could be evaluated using the equations derived in the present study (Equations (10)- (13)).…”

Section: Discussionmentioning

confidence: 99%

“…Hyperspectral sensors will be placed on the ISS, including the Hyperspectral Imager Suite (HISUI) [3], the Earth Surface Mineral Dust Source Investigation (EMIT) [4], and the Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder (CPF) [5]. Radiometric intercalibration of these sensors plays a crucial role in evaluating radiometric consistency across sensors (e.g., CPF and HISUI [6] and HISUI and DESIS [7]), thereby allowing multiple sensors to be tied onto a common radiometric scale for interoperability and synergistic applications [8,9].…”

Section: Introductionmentioning

confidence: 99%

Sensitivity Analysis Method for Spectral Band Adjustment between Hyperspectral Sensors: A Case Study Using the CLARREO Pathfinder and HISUI

Obata

2019

Remote Sensing

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The International Space Station has become the platform for deploying hyperspectral sensors covering the solar reflective spectral range for earth observation. Intercalibration of hyperspectral sensors plays a crucial role in evaluating/improving radiometric consistency. When intercalibrating between hyperspectral sensors, spectral band adjustment is required to mitigate the effects of differences between the relative spectral responses (RSRs) of the sensors. Errors in spectral parameters used in spectral band adjustment are propagated through to the adjustment results. The present study analytically approximated the uncertainty in the spectral band adjustment for evaluating the relative contributions of uncertainties in parameters associated with the exo-atmosphere, atmosphere, and surface to the total uncertainty. Numerical simulations using the derived equations were conducted to perform a sensitivity analysis for the case of the spectral band adjustment between the Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder (CPF) and the Hyperspectral Imager Suite (HISUI). The results show that the effects of errors in the solar irradiance were greater than those of other sources of error, indicating that accurate estimates of atmospheric reflectances and tranismittances are not needed for spectral band adjustment between CPF and HISUI in the atmospheric windows. The accuracy of the analytical approximation was also evaluated in the simulations. The framework of the sensitivity analysis is applicable to other pairs of hyperspectral sensors.

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“…RadCalNet data offer a unique opportunity to compare the radiometric performance of Landsat OLI to Terra's ASTER. This work also provides an evaluation of the Railroad Valley and Gobabeb sites of RadCalNet for sensors at a 15 m spatial resolution to help fill the gap between results from past studies with 10 m and 30 m spatial resolutions [4,[11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Intercomparison of Landsat Operational Land Imager and Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer Radiometric Calibrations Using Radiometric Calibration Network Data

Yarahmadi,

Thome,

Wenny

et al. 2024

Remote Sensing

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This paper presents a comprehensive intercomparison study investigating the radiometric performance of and concurrence among the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Landsat 8 Operational Land Imager (L8 OLI), and Landsat 9 OLI (L9 OLI) instruments. This study leverages data sourced from the Radiometric Calibration Network (RadCalNet) and focuses on spectral bands relevant for vegetation analysis and land cover classification, encompassing a thorough assessment of data quality, uncertainties, and underlying influencing factors. This study’s outcomes underscore the efficacy of RadCalNet in evaluating the precision and reliability of remote sensing data, offering valuable insights into the strengths and limitations of ASTER, L8 OLI, and L9 OLI. These insights serve as a foundation for informed decision making in environmental monitoring and resource management, highlighting the pivotal role of RadCalNet in gauging the radiometric performance of remote sensing sensors. Results from RadCalNet sites, namely Railroad Valley Playa and Gobabeb, show their possible suitability for sensors with spatial resolutions down to 15 m. The results indicate that the measurements from both ASTER and OLI closely align with the data from RadCalNet, and the observed agreement falls comfortably within the total range of potential errors associated with the sensors and the test site information.

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Cross-sensor calibration and validation between DESIS and HISUI Hyperspectral Imager on the International Space Station (ISS)

Cited by 3 publications

References 8 publications

Data Products, Quality and Validation of the DLR Earth Sensing Imaging Spectrometer (DESIS)

Data Products, Quality and Validation of the DLR Earth Sensing Imaging Spectrometer (DESIS)

Sensitivity Analysis Method for Spectral Band Adjustment between Hyperspectral Sensors: A Case Study Using the CLARREO Pathfinder and HISUI

Intercomparison of Landsat Operational Land Imager and Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer Radiometric Calibrations Using Radiometric Calibration Network Data

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