The hyperspectral imager suite (HISUI) is a recently commissioned spaceborne hyperspectral sensor that is expected to provide higher-quality information for terrestrial and aquatic monitoring at a global scale. To maximize the utility of the detailed spectra observed by HISUI, calibration and validation activities have been intensively conducted for the past several years. However, research on long-term monitoring of sensor radiometric characteristics and checking inter-band radiometric consistency is still limited. This study provided the first results of cross- and inter-band calibrations using five scenes acquired over a desert calibration site during 2021–2023, and calculated relative cross-calibration coefficients (RCCCs) to calibrate all the HISUI bands. To make full use of the limited amount of data archived over the calibration site, off-nadir scenes obtained by wide-swath counterpart sensors [i.e., the moderate resolution imaging spectroradiometer (MODIS)] were used for the cross-calibration, with correction by a bidirectional reflectance distribution function. The obtained RCCCs successfully mitigated the inter-band radiometric variability of HISUI data, which was consistent with the in situ surface reflectance data observed by the radiometric calibration network (RadCalNet). Time-series analysis further revealed a notable discrepancy between the visible to near-infrared and short-wave infrared (SWIR) spectral domains after the International Space Station (ISS) maneuvers in spring 2022. This article is also a prompt report of this phenomenon and will soon contribute to HISUI radiometric calibration, particularly after the maneuver events.

Hyperspectral Imager Suite (HISUI) was launched in December 2019 and started its operation observation from International Space Station in October 2020. HISUI data are being acquired based on data acquisition requests from HISUI project and principal investigators of HISUI Research Announcement. The total area of acquired HISUI data by December 2021 exceeded 110 M km2and the data are being used in various application studies. HISUI will be operated by FY2023. In this presentation, HISUI's instrument and operation status will be presented together with its early results in terms of geology and greenhouse gas emission.

We assessed the degradation of the radiance lamp in the onboard calibration system of the Spectral Profiler, a hyperspectral sensor onboard the Japanese Selenological and Engineering Explorer (SELENE), which was launched in September 2007 and observed the Moon until June 2009. We found that the output of the radiance lamp soon after launch increased by 3.2%–4.6% as compared with the prelaunch output, after which it decreased over time. The total decrease during the mission lifetime of about 1.5 years after the increase of 3.2%–4.6% was ~1.1%–1.5%, which is slightly larger than the$0.8\,\mu \text{m}$. The trend of the wavelength dependence was shown to be consistent with a model of blackbody radiance with a decrease in temperature of the lamp of about −5 K, suggesting that the degradation of the lamp was mostly due to temperature decrease of about −3 K/yr. Our results may provide an important constraint on the quantitative assessment of the degradation of the sensitivity of remote-sensing sensors using an onboard calibration system, such as the Advanced Spaceborne Thermal Emission and Reflection Radiometer.

This paper reports on the initial analysis of spectral smile calibration of the Hyperspectral Imager Suite (HISUI) onboard the International Space Station, which has been continuously acquiring data since September 4, 2020. HISUI is an optical hyperspectral imager consisting of two subsystems: VNIR covering 400 to 980nm at intervals of 10 nm, and SWIR covering 895 to 2481nm at 12.5nm intervals. Based on the atmospheric correction for actual observation images, we assessed cross-track dependences of the wavelength deviation (spectral smile) and the full-width at half-maximum (FWHM) of the HISUI response function. We found that significant spectral smile was observed, with maximum variations of 1.8nm in VNIR and 4.3–4.5nm in SWIR. In addition, the cross-track variation of FWHM was observed with maximum variations of 5.0nm for VNIR and 2.5–3.5nm for SWIR.We used the results to model the smile functions to update a smile correction table in the internal calibration system of HISUI. Then, we evaluated how the smile functions reduce the spectral smile in the data acquired after the update on September 27, 2021.We confirmed that VNIR showed a nearly flat profile within 0.25nm with a nearly constant FWHM. For SWIR, although a slight amount of spectral smile and a variation of FWHM were still observed partly due to wavelength dependence in the spectral smile, the spectral smile was reduced to <~2.2 nm. This study demonstrated that wavelength calibration using actual observation images for ground surfaces is important for the characterization of hyperspectral sensors.

Hyperspectral Imager Suite (HISUI) was launched in December 2019 and successfully attached to Japan Experiment Module Exposed Facility, International Space Station. Due to data communication problems, its initial check out activities have been delayed, but its first light image was acquired and released in September 2020. HISUI data delivery to Research Users will start in 1Q of Japanese FY2021 (April - June 2021).

Recently, the use of a rough set theory for land cover classification has progressed significantly, leading to the production of highly accurate maps. However, information loss can occur through the discretization of digital numbers (DNs), and an additional effort may be required to determine the parameter settings. Furthermore, previous studies have not clarified the characteristics of land cover classification based on the rough set theory. This letter develops a new method of grade-added rough sets (GRS) to solve the problems of the existing land cover classifications employing the rough set theory and investigates the characteristics of GRS as a representative land cover classification method. By considering the grade, GRS prevents information loss from discretization and does not require any parameters to be set. To assess the proposed GRS, three experiments were conducted. First, the accuracy of GRS was compared with that of classical rough sets (CRSs), a maximum likelihood classifier (MLC), and a support vector machine (SVM). The other experiments investigated the sensitivity of the classification accuracy with respect to the category class definitions and selection of training data, respectively. GRS was found to be as accurate as existing classification methods and more robust than both MLC and SVM in terms of the category class definitions and selection of training data. These results imply that the classes can be defined without considering the ease of classification based on spectral reflection characteristics, thus reducing the burden on users, and the classification results have a high degree of reliability because they are independent of the training data.

Hyperspectral Imager Suite (HISUI) was launched on Dec. 5, 2019 and successfully attached to Japan Experiment Module Exposed Facility, International Space Station. Currently, initial check out activities are ongoing, and the first light images will be released around August, 2020. The distribution of HISUI Level 1 products will be started in the first half of 2021.

Hyperspectral Imager Suite (HISUI) is a future spaceborne hyperspectral Earth imaging system being developed by Japanese Ministry of Economy, Trade, and Industry (METI). HISUI will be launched and deployed on International Space Station (ISS) for two - three year operation from 2020. Manufacturing and testing of Hyperspectral sensor were completed. Integration and test of HISUI Exposed Payload System is being conducted. HISUI data policy and research announcement as well as synergy with other earth observing instruments onboard ISS are also being discussed.

Hyperspectral Imager Suite (HISUI) is a future spaceborne hyperspectral Earth imaging system being developed by Japanese Ministry of Economy, Trade, and Industry (METI). HISUI will be launched and deployed on International Space Station (ISS) for two - three year operation from 2020. Manufacturing and testing of HISUI Flight Model were almost completed, and design of HISUI Exposed Payload System is being conducted. HISUI data policy and research announcement as well as synergy with other earth observing instruments onboard ISS are also being discussed.

Hyperspectral Imager Suite (HISUI) is a future spaceborne hyperspectral Earth imaging system being developed by Japanese Ministry of Economy, Trade, and Industry (METI). HISUI will be launched and deployed on International Space Station (ISS) for three year operation from 2019. In FY2016, manufacturing and testing of HISUI Flight Model and design of HISUI Exposed Payload System were conducted. HISUI data policy and research announcement as well as synergy with other earth observing instruments onboard ISS are also being discussed.

Hyperspectral Imager Suite (HISUI) is a future spaceborne hyperspectral Earth imaging system being developed by Japanese Ministry of Economy, Trade, and Industry (METI). HISUI project is currently being promoted by three organizations each of which has a contract with METI together with several scientists from universities and national research institutes. Recently, it was decided to deploy HISUI on International Space Station. The current status of HISUI project will be introduced in the presentation.

The ASTER on-demand processing service, which provides a Digital Elevation Model (DEM) and orthorectified images was developed and deployed on the GEO Grid system. It is designed to support the latest algorithms for radiometric and atmospheric corrections developed by researchers as well as the geometric correction and other DEM processing options. The functions and options in this service are developed and implemented as modules, so that they can be arranged as the user requires. Although the system is an experimental, it can provide higher quality data sets than the standard products.