In precision agriculture, vegetation and soil are monitored by multispectral sensors that can observe outside the visible bands. In contrast to satellites and manned aircraft, unmanned aerial vehicles (UAVs) allow anyone to easily acquire near-real time data at a reasonable price. However, UAV images do not account for the anisotropic reflectance and solar irradiance from the ground surface, so extracting the reflectance of vegetation is difficult. To solve this problem, this study developed a bidirectional reflectance distribution function (BRDF) that expresses the anisotropic reflectance of the Earth’s surface as a function of the geometric relationship with the UAV sensor and the Sun. To compensate for the effect of changes in solar incident energy due to clouds and solar irradiance, the solar irradiance was measured and corrected on the ground rather than in the air to avoid errors due to the flight attitude. Before processing by the BRDF and correcting for the solar irradiance, the UAV obtained striated orthomosaic images for which the vegetation indices were affected by the position and attitude of the Sun and the UAV sensor. After the correction, consistent values were calculated for the vegetation indices throughout the images. The accuracy of the UAV data was analyzed by comparison with Sentinel 2A. Reflectance differences are 0.02% to 6.37% from the image without correction. After applying the correction, it reduced to 0.27%, 0.61%, 0.16%, and 0.65% from the blue, green, red, and near-infrared bands, respectively. This study is valuable for obtaining accurate values for vegetation indices under a wide range of weather and geometric conditions at different sites because UAVs to collect images are a rare case under optimal conditions.
This paper presents a radiometric cross calibration of KOMPSAT-3 AEISS based on Landsat-8 OLI. Cross calibration between the two sensors using simultaneous image pairs, acquired during an underfly event over the Libya 4 pseudo invariant calibration site (PICS) site. The spectral profile of the target comes from the near-simultaneous EO-1 Hyperion data over these sites for apply Spectral Band Adjustment Factor (SBAF). The results indicate that the Top Of Atmosphere (TOA) reflectance measurements for KOMPSAT-3 agree with Landsat-8 to within 5% after the application of SBAF. To validate radiometric coefficient, comparison TOA reflectance executed in north Virginia, USA. The difference in TOA reflectance was calculated to within a maximum ±1.55%. There was a huge improvement when the standard deviation altered from 0.1 to 0.01, when applying the SBAF. The result of radiometric coefficient presented here appear to be a good standard for maintaining the optical quality of the KOMPSAT-3, for which prelaunch, onboard, and vicarious calibration data are lacking.
This paper presents a vicarious radiometric calibration of the Korea Multi-Purpose Satellite-3 (KOMPSAT-3) performed by the Korea Aerospace Research Institute (KARI) and the Pukyong National University Remote Sensing Group (PKNU RSG) in 2012 and 2014. Correlations between top-of-atmosphere (TOA) radiances and the spectral band responses of the KOMPSAT-3 sensors at the Zuunmod, Mongolia and Goheung, South Korea sites were significant for multispectral bands. KOMPSAT-3 calibration coefficients for all bands estimated in 2012 continued to agree well with calibration coefficients estimated in 2014 (within 1.5%). The average difference in TOA reflectance between KOMPSAT-3 and Landsat-8 image over the Libya 4, Libya site in the red-green-blue (RGB) region was under 3%, whereas in the NIR band, the TOA reflectance of KOMPSAT-3 was lower than the that of Landsat-8 due to the difference in the band passes of two sensors. The KOMPSAT-3 sensor includes a band pass near 940 nm that can be strongly absorbed by water vapor and therefore displayed low reflectance. To overcome this, we need to undertake a detailed analysis using rescale methods, such as the spectral bandwidth adjustment factor (SBAF).
This paper presents absolute radiometric calibration coefficients (gains) that explain the relationship between the digital number (DN) and at-sensor radiance for the multispectral camera (MSC) on Korea's first high-resolution satellite (KOMPSAT-2). Absolute radiometric calibration was performed using a reflectance-based method. In addition, the suitability of vicarious results from radiance- and reflectance-based validations was analyzed with reference to IKONOS and QuickBird images. The latter are spectrally similar to KOMPSAT-2 images and have been validated in a large number of studies. For all bands, the R2 values of fitted lines for the gain ranged from 0.82 to 0.94, representing an improvement compared to previous findings for the KOMPSAT-2 MSC. To analyze the suitability of the vicarious results, same-pixel at-sensor radiances across different spectral bands were compared. In all bands, except the red band of QuickBird, the at-sensor radiances of KOMPSAT-2 MSC were highly correlated with those of IKONOS and QuickBird. In addition, same-pixel comparisons of reflectance across different spectral bands showed that the slopes of the least-squares lines for each band were similar to the results of the radiance comparison. The standard deviation among top of atmosphere (TOA) reflectances was within 0.019 for all bands. To calculate the tasseled cap transformation (TCT) coefficients for the KOMPSAT-2 MSC, an empirical method was applied using radiometric normalization. The results were similar to those obtained using the TCT coefficients for IKONOS and QuickBird in the brightness, greenness, and wetness components. The TCT images showed similar patterns. The absolute radiometric calibration coefficients presented here appear to be a good standard for maintaining the optical quality of the KOMPSAT-2 MSC, for which prelaunch, on-board, and vicarious calibration data are lacking.
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