Abstract
Radiometric calibration of the medium-resolution satellite data is critical for monitoring and quantifying changes in the Earth's environment and resources. Many medium-resolution satellite sensors have irregular revisits and, sometimes, have a large difference in illumination viewing geometry compared with a reference sensor, posing a great challenge for routine cross-calibration practices. To overcome these issues, this study proposed a cross-calibration method to calibrate medium-resolution multispectral data. The Chinese Gaofen-4 (GF-4) panchromatic and multispectral sensor (PMS) data with large viewing angles were used as the test data, and Landsat-8 operational land imager (OLI) data were used as the reference data. A bidirectional reflectance distribution function (BRDF) correction method was proposed to eliminate the effects of differences in illumination viewing geometry between GF-4 and Landsat-8. The validation using concurrent image shows that the mean relative error (MRE) of cross calibration is less than 6.65%. Validation using ground measurements shows that our calibration results have an improvement of around 14.8% compared with the official released calibration coefficients. The time series cross calibration reveals that, without the requirements of simultaneous nadir observations (SNOs), our calibration activities can be carried out more often in practice. Gradual and continuous radiometric sensor degradation is identified with the monthly updated calibration coefficients, demonstrating the reliability and importance of the timely cross calibration. Besides, the cross-calibration approach does not rely on any specific calibration site, and the difference in illumination viewing geometry can be well considered. Thus, it can be easily adapted and applied to other optical satellite data.
Highlights
R ADIOMETRIC calibration is the conversion from satellite recorded digital numbers to values with absoluteManuscript received October 23, 2020; revised February 1, 2021; accepted March 1, 2021
There are several difficulties in the cross calibration of GF-4 data: 1) the spectral characteristics of GF-4 panchromatic and multispectral sensor (PMS) are different from those of existing satellite sensors, leading to different reflectance between the GF-4 PMS and other sensors; 2) the viewing geometries of GF-4 is quite different from the polar-orbiting satellite sensors commonly used for cross calibration (e.g., Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS)), and the bidirectional reflectance distribution function (BRDF) effects need to be considered when ray-matched observations are scarcely available; and 3) different from other medium-resolution satellites, GF-4 PMS is a task-based sensor without continuous observations over the same region or with the same repeating cycle, and traditional methods that require observations over certain calibration sites cannot be applied to such sensors
To mitigate the effect of differences in the spectral and illumination viewing geometry of GF-4 PMS and reference sensors and, to achieve the near-real-time calibration of GF-4 data, we proposed a data harmonization method, which includes band conversion and BRDF correction to estimate the observation of GF-4 PMS by Landsat-8 operational land imager (OLI)
Summary
R ADIOMETRIC calibration is the conversion from satellite recorded digital numbers to values with absolute. There are several difficulties in the cross calibration of GF-4 data: 1) the spectral characteristics (bandwidth and RSR) of GF-4 PMS are different from those of existing satellite sensors, leading to different reflectance between the GF-4 PMS and other sensors; 2) the viewing geometries of GF-4 is quite different from the polar-orbiting satellite sensors commonly used for cross calibration (e.g., Landsat and MODIS), and the BRDF effects need to be considered when ray-matched observations are scarcely available; and 3) different from other medium-resolution satellites, GF-4 PMS is a task-based sensor without continuous observations over the same region or with the same repeating cycle, and traditional methods that require observations over certain calibration sites cannot be applied to such sensors. To mitigate the effect of differences in the spectral and illumination viewing geometry of GF-4 PMS and reference sensors and, to achieve the near-real-time calibration of GF-4 data, we proposed a data harmonization method, which includes band conversion and BRDF correction to estimate the observation of GF-4 PMS by Landsat-8 OLI. It is suitable for choosing the Landsat-8 OLI data as the reference data to calibrate the GF-4 PMS data
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