The Gaofen-5 02 (GF-5 02) satellite is equipped with two Earth observation sensors, the Advanced Hyperspectral Imager (AHSI) and the Full-Spectrum Spectral Imager (VIMI), which are used in environmental monitoring, natural resource exploration and so on. In this study, a spectral calibration method by matching the effective top-of-atmosphere (TOA) reflectance and atmospheric transmittance at the atmospheric absorption channels of 760 nm, 940 nm, 1140 nm, and 2060 nm was introduced. The spectral calibration method was validated with simulated hyperspectral data and the accuracy of center wavelength and full-width at half-maximum (FWHM) were generally better than 0.18 nm and 0.57 nm, respectively. Then, the method was applied to calibrate the center wavelength and FWHM of the GF-5 02/AHSI with a hyperspectral image collected on 7 May 2022. The spectral calibration results showed that the center wavelength and FWHM of GF-5 02/AHSI shifts with -0.375 nm and 0.35 nm, respectively. These results demonstrated a significant improvement in the surface reflectance spectrum of the inversions after spectral calibration at the Railroad Valley Playa (RVP) site.

The advanced hyperspectral imager (AHSI) is one of the sensors aboard the Chinese Gaofen-5 (GF-5) satellite, possessing characteristics of high spatial and spectral resolution, as well as width swath. To better understand the radiometric performance of GF-5/AHIS after its launch, this article presents an on-orbit radiometric calibration approach for AHSI visible and near-infrared (VNIR) and shortwave infrared (SWIR) sensors from field automatic observations with a field spectrometer in the absence of SWIR measurements. A spectrum extension method was proposed to extend the retrieved surface hyperspectral reflectance in the VNIR spectral ranges to SWIR by incorporating the historical hyperspectral reflectance library. The radiometric calibration coefficients of GF-5/AHSI were calculated by linear fitting of the observed digital number (DN) values with GF-5/AHSI and predicted at-sensor radiances with MODTRAN 5 based on extended hyperspectral surface reflectance. Comparisons with onboard calibration results were also performed, and the averaged relative differences were within 5% with$1\delta $standard deviations less than 10% for most bands, except for those in the atmospheric absorption and low signal-to-noise ratio bands. The comparison results indicate that the on-site radiometric calibration results are consistent with the onboard results, and the operational on-orbit radiometric calibration approach is reliable in the case that there are no measurements in the SWIR spectra range. The on-orbit radiometric performance of GF-5/AHSI rapidly degraded during the first several months after its launch and then tended to be relatively stable.

When using a field calibration site to perform in-orbit radiometric calibration of a space-borne remote sensor, the measured signal by the sensor may contain radiation from adjacent pixels, due to scattering in the Earth’s atmosphere and the sensor viewing characteristics. If this is not accounted for in the modeling, the accuracy of the radiometric calibration will be reduced. Nonuniformities of the ground target are more significant for the calibration of high-resolution sensors. In addition, if the brightness contrast of neighboring targets is not small, the impact of the adjacency effects will be more significant. It is important to quantitatively analyze and estimate the influence of this kind of adjacency effects, to reduce the uncertainty of in-orbit radiometric calibration. To evaluate the adjacency effects caused by atmospheric multiple scattering, this article constructed a local atmospheric point spread function model using long time-series satellite-ground synchronous observation data and developed an adjacency effects simulation method, which considers background reflectance spectral information. Tests on Sentinel-2A and Worldview-3 imagery overpassing the Baotou calibration and validation site (Baotou C&V site) (China) indicate that the proposed modeling method can effectively account for the influence of the adjacency effects in vicarious calibration. Uncertainties of relevant parameters and their contributions to the calibration result were also analyzed, and uncertainty assessment results show that the vicarious radiometric calibration scheme considering adjacency effects correction can bring about a total uncertainty less than 7%.

This paper presents a series of temporal vicarious radiometric calibration results of ZY3-MUX sensor over 2016–2019 using the reflectance-based approach. The synchronous ground measuring data have been collected from Baotou sandy site in China given that its high-frequency standard product including surface reflectance and atmospheric parameters. The results show the average difference of radiometric calibration coefficients between calculated results and the official coefficients in each year of ZY3-MUX sensor are 4.6%, 4.6%, 0.64%, 6.28%, respectively. The long-term stability of the radiometric calibration using the data of four years shows a good consistent, and the average difference is 0.92%, 0.64%, 0.50% and 0.65% for ZY3-MUX sensor, respectively. In addition, uncertainty analysis shows that the overall uncertainty for ZY3-MUX radiometric calibration is 4.42%, 4.44%, 4.66% and 3.92%, which also confirms the credibility for radiation quality of Baotou sandy site.

The Chinese Gaofen-1(GF-1) high resolution satellite loaded with four Wide Field of View (WFV) cameras provides observations with high temporal and spatial resolutions. However, the radiometric calibration accuracy of the GF1/WFV should be given when being used to monitoring the earth. In this study, radiometric calibration of the GF1/WFV was carried out first with automatic instrumented Baotou site. Then, the determined radiometric calibration coefficients were cross validated with the MultiSpectral Imager (MSI) onboard the Sentinel-2 satellite. The preliminary results show that the radiometric performances of the four WFV cameras are relatively stable with averaged relative difference less than -1.85%. The standard deviation of the radiometric calibration coefficients during the period from April 2019 to June 2020 is 0.0056, 0.0081, 0.0072, and 0.0076 with respect to the blue, green, red, and near infrared channel. The results of cross validation with Sentinel-2/MSI suggest that the averaged relative difference is -3.16%, -4.28%, -1.15%, and -3.22% with respect to the blue, green, red, and near infrared channel. The results of cross-validation demonstrate that radiometric calibration of the GF-1/WFV cameras using automatic instrumented Baotou site is feasible and operational. And, it is also essential and necessary to update the on-orbit radiometric calibration coefficients of GF-1/WFV cameras during its' entire lifetime for further quantitative application.

As the growing interest in the use of the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) low light data, there is an urgent need to obtain high accuracy product at low radiances. Currently the low light calibration accuracy was previously estimated at a moderate 15% using extended sources while the long-term stability has yet to be characterized. This paper gives a new method to quantitative analysis DNB data by using a specialized ground light point source at night, which is active designed light sources at selected site (Baotou of Inner Mongolia, China). It presents a possibility to resolve the need for SI traceable active light sources to monitor the calibration stability, radiometric and geolocation accuracy, and point spread functions of the DNB.

The Radiometric Calibration Network (RadCalNet) provide SI-traceable Top-of-Atmosphere (TOA) spectrally-resolved reflectance for automated radiometric calibration of optical satellite sensors. Each RadCalNet site is equipped with automated ground instrumentation in order to provide continuous measurements of both surface reflectance and local environmental/atmospheric conditions needed for the derivation of TOA reflectance values. It is very valuable to use these data in calibrating and motoring optical satellite sensors with the recent launches of very large number of satellites. The work presented here shows the results of vicarious calibration of SuperView-1 satellite sensor using RadCalNet TOA reflectance product. The results also indicated that there was a good consistency among the vicarious calibration coefficients from different RadCalNet sites.

Directional reflectance of Baotou sandy calibration site was measured in September 2017. Directional reflectance factors were collected using the Multi-Angles Observation System (MAOS) designed by Academy of Opto-Electronics (AOE), Chinese Academy of Sciences. The directional reflectance was measured at a few viewing and azimuth angles in the 0-30° and 0-360° angular ranges, respectively. Anisotropy and directional effect of surface reflectance were analyzed based on the measured directional reflectance factors. The bidirectional reflectance distribution function (BRDF) model of the calibration site was also modelled, and the model fitting error was approximated to be within 2%. The BRDF model was also used to correct angular difference between ground measurements and satellite measurements in vicarious radiometric calibration carried out in Baotou sandy calibration site, and calibration results with and without angular correction were shown in this work.

When using field calibration site to perform on-orbit radiometric calibration for a space-borne remote sensor, the observed signal of the sensor may contain energy from adjacent pixels, due to existence of the earth atmosphere and sensor viewing characteristics. Hence the accuracy of radiometric calibration will be decreased to some extent. When calibration of high-resolution sensor is concerned, the non-uniformity of the ground target will be relatively more obvious. In addition, if the brightness contrast of neighboring targets is not small, the impact of adjacency effect will be more outstanding. How to quantitatively analyze and eliminate the influence of this kind of adjacency effect, becomes an actual demand to reduce the uncertainty of on-orbit radiometric calibration. Aiming at the adjacent effect caused by atmospheric multiple scattering, this paper analyzed radiation transfer mechanism first, then constructed a local atmospheric point spread function model using long time-series satellite-ground synchronous observation data, developed an adjacency effect correction method used in on-orbit vicarious calibration, which considers background reflectance spectral information. Test on Sentinel-2A imagery indicates that the proposed correction method can effectively alleviate the influence of adjacency effect in vicarious calibration.

Radiometric characteristics monitoring of optical remote sensing data is a very essential step that enables further quantitative study and application of the data. In this paper, long term vicarious radiometric calibration using ground reflected radiance-based approach was introduced in this study. A case study of Sentinel 2A multispectral imager (MSI) vicarious radiometric characteristics monitoring based on our proposed approach with an automatic observation system was conducted over a large scale desert at the Baotou calibration site in Inner Mongolia, China. And, twelve clear Sentinel 2A MSI scenes as well as ground measurements were successfully acquired during the year of 2017. Top of Atmospheric (TOA) radiance and reflectance were predicted with introduced approach from ground reflected radiance and atmospheric data. The long term radiometric calibration results suggests that the Sentinel 2A MSI display a stable radiometric performance over the calibration period. Vicarious and onboard radiometric calibration results were also cross compared with average relative error about 5%. Uncertainty analysis also show that the TOA radiance overall uncertainty is less than 3.5% due to the atmospheric characteristics, surface characteristics, and the calibration model uncertainties sources.

In this study, the automatic reflectance-based method is used to vicarious radiometrically calibrate the satellite optical sensors using the desert target located in the Baotou site in China. The ground reflected radiance of the desert target were collected automatically using an automatic observation system. The reflectance of the desert target was calculated with the radiance collected with the automatic observation system and the total irradiance simulated from MODTRAN code based on the atmospheric parameters. Then, the TOA radiance can be predicted with MODTRAN code based on the calculated desert reflectance. The automatic reflectance-based approach was applied to the Landsat 8/OLI sensors, and the TOA radiances calibrated by our method were also compared with the observed TOA radiance calibrated with on-board calibrator. Preliminary results show a good consistent and the mean relative difference of the multispectral channels is less than 5%. Uncertainty analysis also show that the TOA radiance overall uncertainty is less than 4% due to the source including the atmospheric characteristics, surface characteristics, and the selected calibration model.

This paper addressed the retrieval of land surface temperature (LST) from combined mid-infrared and thermal infrared data of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-Orbiting Partnership (S-NPP). To efficiently remove the effect of the direct solar radiance, a relationship between direct solar radiance and water vapor content, view zenith angle and solar zenith angle is proposed to improve the retrieve accuracy. Then, a split-window algorithm from combined mid-infrared and thermal infrared data is used to correct for the atmospheric effects and retrieve the LST with the aid of emissivity provide by VIIRS product. Finally, comparison of the standard VIIRS LST product and the retrieved LST from the proposed algorithm, a good agreement was shown. Analysis indicated the root mean square error (RMSE) of the LST over these land cover types is 2.04K for desert and 1.84K for vegetation, respectively.

Fractional vegetation cover (FVC) is a major biophysical parameter in earth surface system. In this paper, FVC is retrieved with a simple linear model between FVC and Normalized Difference Vegetation Index (NDVI). However, the parameters NDVI∞and NDVI0, corresponding to the values of NDVI for bare soil and full vegetation covered surface, used in the simple model are estimated with a vegetation phenology model using time series MODIS NDVI data. The results of the estimated FVC with our proposed method in the study area have been showed in the results section, which is compared with the FVC estimated with a single date MODIS NDVI data. Validation has also been proved that the retrieved FVC has a good agreement with the ground-measured truth FVC.

This work addressed the estimation of the directional reflectance in Middle Infra-Red (MIR) channel from the data acquired by the Stretched Visible and Infrared Spin Scan Radiometer (SVISSR) onboard Chinese geostationary Meteorological satellite FengYun 2C (FY-2C). SVISSR/FY-2C sensor acquires image covering the whole disk with a temporal resolution of 30 minutes. The MIR directional reflectance retrieval procedure can be seen as follows. Firstly, the atmospheric profiles data provided by European Centre for Medium-Range Weather Forecasts (ECMWF) were used to correct atmospheric influence with the radiative transfer code (MODTRAN 4.0). Secondly, the bi-directional reflectance in SVISSR/FY-2C MIR channel 4 (3.8 micron) was estimated from the combined MIR and TIR channel with day-night SVISSR/FY-2C data. Finally, a BRDF model referred to as the RossThick-LiSparse-R model was used to estimate the directional reflectance in MIR channel from the time-series bi-directional reflectance data. The results have been demonstrated that the method can be applied well to estimate the directional reflectance in MIR channel of SVISSR/FY-2C sensor.

Digital photography is now the most widely used method to obtain the Fractional Vegetation Cover (FVC) in field measurements. Its accuracy is affected by shooting conditions and classification methods of digital images. In this paper, we chose summer maize as the study plant, used computer simulation method to control the shooting conditions strictly and generate simulated scene. Then a physically based ray-tracing (PBRT) algorithm was used to render the scene to obtain simulated images under different shooting conditions. Supervised classification and CIE L*a*b* color space threshold method were used to extract FVC values from the simulated images. Comparing the extracted FVC values with the scene's true FVC value, we evaluated the FVC accuracy of different shooting conditions and classification methods. The results can act as a guidance of digital photography to obtain the FVC.

Microwave staring correlation (MSC) imaging is a new type of active high-resolution microwave imaging technique. Image quality assessment is of vital for developing and monitoring any remote imaging system. This paper presented the image quality analysis for this imaging technique by theoretical analysis and simulation. MSC imaging method was introduced firstly. Then, image properties were analyzed and compared with SAR image. Speckle noise effect and side lobe of point target effect, which are intrinsic properties of SAR image, do not exist in MSC image. The quality metrics of MSC image were presented. IRW-Staring time ratio was proposed to describe the image property that image resolution improves with the number of received signals used in the image reconstruction procedure. Finally, the effects of different system parameters on the image quality were investigated via simulation experiments. The analysis results could be helpful for future imaging algorithm development and system design.

Gap fraction is a very important parameter to the indirect estimation of the true Leaf Area Index. In this paper, we combined the multispectral digital imageries (RGB color imagery and Near-Infrared imagery), which were obtained from a new device called Multispectral Canopy Imager (MCI), to estimate gap fraction. A new method incorporated with CIE L*a*b* color space has also been proposed to segment the multispectral digital imagery. The preliminary results of the estimated gap fraction have been showed in the conclusions section and been proved to be very well.

Fractional vegetation cover (FVC) is widely relevant for land surface process. In this paper, an algorithm is addressed on FVC retrieval, with the combination of MODIS and Huan Jing satellite (HJ), which is a newly launched constellation by China. In the developed model, we considered angular effect and utilized spatial and temporal information to a great extent. MODIS and HJ surface reflectance products provide data supply for the algorithm and play cooperative roles. A vegetation growth model was introduced to constrain the uncertainty of HJ data in a temporal scale. The uncertainty of using this algorithm was assessed by error propagation theory and field experiments. Retrieved FVC became more reasonable after consideration of the correlation among time series observations and the introduction of more observational data. A priori information is necessary to constrain the inversion process.