Extreme Case of Spectral Band Difference Correction Between the Osiris-Rex-Navcam2 Dscovr-Epic Imagers
| Autor: | Conor O. Haney, David R. Doelling, Rajendra Bhatt, Arun Gopalan, Benjamin R. Scarino |
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| Rok vydání: | 2019 |
| Předmět: |
010504 meteorology & atmospheric sciences
Pixel Calibration (statistics) Computer science 0211 other engineering and technologies Hyperspectral imaging 02 engineering and technology Spectral bands 01 natural sciences Space exploration SCIAMACHY Radiance Radiometric calibration 021101 geological & geomatics engineering 0105 earth and related environmental sciences Remote sensing |
| Zdroj: | IGARSS |
| DOI: | 10.1109/igarss.2019.8900496 |
| Popis: | Earth-viewed images acquired during a recent asteroid-intercept mission present a unique opportunity for radiometric calibration of visible imagers onboard a space exploration probe. Measurements from the CERES-consistent DSCOVR-EPIC imager act as a reference in providing spatially, temporally, and angularly matched radiance values for deriving OSIRIS-REx-NavCam sensor calibration gains. The calibration is accomplished using an optimized all-sky tropical ocean ray-matching technique, which employs complex pixel remapping, navigation correction, and angular geometry consideration. Of critical consideration in this specific inter-calibration event is the extreme difference in spectral response function (SRF) width between the NavCam and EPIC imagers, which could cause a rather large bias. The NASA-LaRC SCIAMACHY-based online spectral band adjustment factor (SBAF) calculation tool provides an empirical solution to such potential spectral-difference-induced biases through a high-spectral-resolution hyperspectral convolution approach. The adjustments produced from this tool can effectively reduce the calibration gain bias of NavCam2 by nearly 6%, thereby adjusting the NavCam2 sensor to within 3.2% of its pre-launch calibration. These results highlight the capability of the SBAF tool to account for exceptionally disparate SRFs. |
| Databáze: | OpenAIRE |
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