The multispectral imager (MII), onboard the Sustainable Development Science Satellite 1 (SDGSAT-1), performs detailed terrestrial change detection and coastal monitoring. SDGSAT-1 was launched at 2:19 UTC on 5 November 2021, as the world’s first Earth science satellite to serve the United Nations 2030 Sustainable Development Agenda. A vicarious radiometric calibration experiment was conducted at the Dunhuang calibration site (Gobi Desert, China) on 14 December 2021. In-situ measurements of ground reflectance, aerosol optical depth (AOD), total columnar water vapor, radiosonde data, and diffuse-to-global irradiance (DG) ratio were performed to predict the top-of-atmosphere radiance by the reflectance-, irradiance-, and improved irradiance-based methods using the moderate resolution atmospheric transmission model. The MII calibration coefficients were calculated by dividing the top-of-atmosphere radiance by the average digital number value of the image. The radiometric calibration coefficients calculated by the three calibration methods were reliable (average relative differences: 2.20% (reflectance-based vs. irradiance-based method) and 1.43% (reflectance-based vs. improved irradiance-based method)). The total calibration uncertainties of the reflectance-, irradiance-, and improved irradiance-based methods were 2.77–5.23%, 3.62–5.79%, and 3.50–5.23%, respectively. The extra DG ratio measurements in the latter two methods did not improve the calibration accuracy for AODs ≤ 0.1. The calibrated MII images were verified using Landsat-8 Operational Land Imager (OLI) and Sentinel-2A MultiSpectral Instrument (MSI) images. The retrieved ground reflectances of the MII over different surface types were cross-compared with those of OLI and MSI using the FAST Line-of-sight Atmospheric Analysis of Hypercubes software. The MII retrievals differed by <0.0075 (7.13%) from OLI retrievals and <0.0084 (7.47%) from MSI retrievals for calibration coefficients from the reflectance-based method; <0.0089 (7.57%) from OLI retrievals and <0.0111 (8.65%) from MSI retrievals for the irradiance-based method; and <0.0082 (7.33%) from OLI retrievals and <0.0101 (8.59%) from MSI retrievals for the improved irradiance-based method. Thus, our findings support the application of SDGSAT-1 data.

The absolute radiometric accuracy of the Fengyun 3D advanced Medium Resolution Spectral Imager (FY3D MERSI-II) thermal infrared bands was evaluated using the collected field measurements and atmospheric transfer simulations during 16–22 August 2019 at Lake Qinghai. A thermal infrared radiometer equipped on an unmanned surface vehicle was used to continuously collect the water temperature. Atmospheric conditions, surface emissivity, and aerosol optical depth measured near the field experiment site were adopted by the atmospheric transfer code to calculate the parameters about the influence of atmosphere on long-wave radiation, including the path radiance and the transmittance propagated from land surface to the satellite. The radiometric calibration accuracy analysis suggests that the differences between the simulated brightness temperature and satellite-based brightness temperature are −0.346 K and −0.722 K for channel 24 on 18 and 20 August, respectively, while it reaches −0.460 K and −1.036 K for channel 25 on 18 and 20 August, respectively. The vicarious calibration coefficients were found to be in good agreement with the internal onboard calibration coefficient in channel 24 and 25 of the FY3D MERSI-II according to the validation analysis in selected regions. The thermal infrared bands of the FY3D have a good in-orbit operational status according to our vicarious calibration experiments.

Nighttime light plays an important role in social economy and human activities by observing artificial light at night. Accurate radiometric calibration is the basis of quantitative applications and influences the accuracy of surface information revision. A nighttime light payload, named Glimmer Imager (GLI) is onboard the Sustainable Development Goals Satellite (SDGSAT-1). The payload can acquire nighttime light observations with a spatial resolution of 10 m in the panchromatic bands, and 40 m in Red/Green/Blue bands. In this paper, we proposed a vicarious radiometric calibration method for the GLI of SDGSAT-1 based on point light source, and conducted experiment in the Dunhuang radiometric calibration site. Atmospheric profile, aerosol optical depth (AOD), and total column water vapor content were measured during the in-situ measurements, and were used to simulate the at-sensor radiance at the entrance of satellite payload via MODerate resolution atmospheric TRANsmission (MOTRAN). Our result shows that there is a strong linear correlation between the simulated atsensor radiance and the DN value, with R ² larger than 0.91. Moreover, uncertainties of the vicarious radiometric calibration induced by relative spectral response shift, AOD content measurements, atmospheric profile measurements, AOD type assumption, and specialized point light itself are also discussed. Results show that the overall uncertainty of vicarious radiometric calibration for nighttime light payload onboard SDGSAT-1 based on point light sources is between 4.00% and 5.50%. The comparison between GLI/SDGSAT-1 and DNB/VIIRS at Athens, Denver, and Milan shows a strong correlation with R ² larger than 0.80. Our analysis reveals the feasibility of vicarious radiometric calibration method based on point light source for nighttime light payload.

The Sustainable Development Science Satellite 1 (SDGSAT-1) satellite, launched in November 2021, is dedicated to providing data detailing the “traces of human activities” for the implementation of the United Union’s 2030 Agenda for Sustainable Development and global scientific research. The glimmer imager (GI) that is equipped on SDGSAT-1 can provide nighttime light (NL) data with a 10 m panchromatic (PAN) band and red, green, and blue (RGB) bands of 40 m resolution, which can be used for a wide range of applications, such as in urban expansion, population studies of cities, and economics of cities, as well as nighttime aerosol thickness monitoring. The 10 m PAN band can be fused with the 40 m RGB bands to obtain a 10 m RGB NL image, which can be used to identify the intensity and type of night lights and the spatial distribution of road networks and to improve the monitoring accuracy of sustainable development goal (SDG) indicators related to city developments. Existing remote sensing image fusion algorithms are mainly developed for daytime optical remote sensing images. Compared with daytime optical remote sensing images, NL images are characterized by a large amount of dark (low-value) pixels and high background noises. To investigate whether daytime optical image fusion algorithms are suitable for the fusion of GI NL images and which image fusion algorithms are the best choice for GI images, this study conducted a comprehensive evaluation of thirteen state-of-the-art pansharpening algorithms in terms of quantitative indicators and visual inspection using four GI NL datasets. The results showed that PanNet, GLP_HPM, GSA, and HR outperformed the other methods and provided stable performances among the four datasets. Specifically, PanNet offered UIQI values ranging from 0.907 to 0.952 for the four datasets, whereas GSA, HR, and GLP_HPM provided UIQI values ranging from 0.770 to 0.856. The three methods based on convolutional neural networks achieved more robust and better visual effects than the methods using multiresolution analysis at the original scale. According to the experimental results, PanNet shows great potential in the fusion of SDGSAT-1 GI imagery due to its robust performance and relatively short training time. The quality metrics generated at the degraded scale were highly consistent with visual inspection, but those used at the original scale were inconsistent with visual inspection.