Long-term cross calibration of HJ-1A CCD1 and Terra MODIS reflective solar bands.

Since its launch on September 6, 2008, HJ-1A has been in the orbit for 13 years. The CCD1 sensor on the HJ-1A has four reflected solar bands. Since the calibration frequency is limited to the annual site calibration, cross-calibration is an effective method to improve the calibration frequency. In this paper, we use 420 image pairs of HJ-1A CCD1 and Terra MODIS over the Dunhuang test site for gains calculation, where we take MODIS as the reference sensor. The spectral band adjustment factors (SBAFs) for cross-calibration are then calculated to compensate for the spectral mismatch. The cross-calibration results are also validated by the field calibration results. From 2008 to 2019, a total of six campaigns have been cross-calibrated on the same day. The gain difference between the site calibration and cross-calibration is less than 3%. The long-term cross-calibration results further indicate that due to the adjustment of HJ-1A CCD gain state in October 2009, an abrupt change occurred 405 days after launch. After 12 years of on-orbit operation, the attenuation rate has reached 23.51%, 21.89%, 8.11%, and 13.37%, respectively by the end of 2019 based on the cross-calibration results.

A Learning-Enhanced Two-Pair Spatiotemporal Reflectance Fusion Model for GF-2 and GF-1 WFV Satellite Data.

Since requirements of related applications for time series remotely-sensed images with high spatial resolution have been hard to be satisfied under current observation conditions of satellite sensors, it is key to reconstruct high-resolution images at specified dates. As an effective data reconstruction technique, spatiotemporal fusion can be used to generate time series land surface parameters with a clear geophysical significance. In this study, an improved fusion model based on the Sparse Representation-Based Spatiotemporal Reflectance Fusion Model (SPSTFM) is developed and assessed with reflectance data from Gaofen-2 Multi-Spectral (GF-2 MS) and Gaofen-1 Wide-Field-View (GF-1 WFV). By introducing a spatially enhanced training method to dictionary training and sparse coding processes, the developed fusion framework is expected to promote the description of high-resolution and low-resolution overcomplete dictionaries. Assessment indices including Average Absolute Deviation (AAD), Root-Mean-Square Error (RMSE), Peak Signal to Noise Ratio (PSNR), Correlation Coefficient (CC), spectral angle mapper (SAM), structure similarity (SSIM) and Erreur Relative Global Adimensionnelle de Synthèse (ERGAS) are then used to test employed fusion methods for a parallel comparison. The experimental results show that more accurate prediction of GF-2 MS reflectance than that from the SPSTFM can be obtained and furthermore comparable with popular two-pair based reflectance fusion models like the Spatial and Temporal Adaptive Fusion Model (STARFM) and the Enhanced-STARFM (ESTARFM).

[The field radiometric calibration and validation of ZY-3 multispectral sensor].

A field calibration campaign of ZY-3 multispectral sensor (MUS) was performed by the China Center for Resources Satellite Data and Application at the Dunhuang site. The reflectance-based method with two-point sites was used to obtain MUS absolute calibration coefficients in 2013. Compared to the calibration results in 2012, the calibration coefficients in 2013 changed by about 1%-8.5% in different bands. The results were also validated by intercalibration method using the Landsat 8 Operational Land Imager (OLI) data. It shows largely good consistency between field calibration and intercalibration. It was concluded that the absolute calibration coefficients were highly reliable.

[Research on the atmospheric correction for ZY-3 MUX image].

The resolution of the ZY-3 MUX data is 5.8 meter, which is used to the subject classification. It is very difficult to use the dark target method for the atmosphere correction due to the lack of near infrared band in ZY-3 MUX data. The present paper uses the atmospheric correction coefficient look-up table (LUT) constructed by the radiation transmission model 6S based on the aerosol optical depth retrieved from the MODIS data for the atmospheric correction of ZY-3 image. To validate the results, the paper compares the surface spectral curves of the gypsum mine and Gobi and the NDVI values from the corrected and TOA reflectance, the relative error of the atmosphere corrected and the ground-based surface reflectance is less than 6%; the atmospheric correction increases the difference between vegetation NDVI and other features NDVI, highlights vegetation monitoring application ability.