Radiometric cross-calibration of KOMPSAT-3 with Landsat-8 (original) (raw)
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Remote Sensing, 2014
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Absolute Radiometric Calibration of KOMPSAT-3A
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016
This paper presents a vicarious radiometric calibration of the Korea Multi-Purpose Satellite-3A (KOMPSAT-3A) performed by the Korea Aerospace Research Institute (KARI) and the Pukyong National University Remote Sensing Group (PKNU RSG) in 2015.The primary stages of this study are summarized as follows: (1) A field campaign to determine radiometric calibrated target fields was undertaken in Mongolia and South Korea. Surface reflectance data obtained in the campaign were input to a radiative transfer code that predicted at-sensor radiance. Through this process, equations and parameters were derived for the KOMPSAT-3A sensor to enable the conversion of calibrated DN to physical units, such as at-sensor radiance or TOA reflectance. (2) To validate the absolute calibration coefficients for the KOMPSAT-3A sensor, we performed a radiometric validation with a comparison of KOMPSAT-3A and Landsat-8 TOA reflectance using one of the six PICS (Libya 4). Correlations between top-of-atmosphere (T...
Radiometric Calibration and Uncertainty Analysis of KOMPSAT-3A Using the Reflectance-Based Method
Sensors, 2020
In recent years, Korea has sustained consistent access to remote sensed data by launching Korea Multi-Purpose Satellite-3A (KOMPSAT-3A, K3A)—an updated version of the high-resolution KOMPSAT series. This KOMPSAT-3A required calibration and validation (Cal/Val) before and after its launch to enable proper functional characterization and to maintain the veracity of data collected. The Korea Aerospace Research Institute (KARI) executed the initial prelaunch calibration in the laboratory and we performed the Cal/Val of KOMPSAT-3A during the Launch and Early Operation Phase (LEOP) in the field. Two suitable sites in Korea and Mongolia with stable weather, almost uniform terrain, and near Lambertian diffusion, provided the necessary tarp reflectance to calculate the absolute radiometric calibration coefficients. The surface reflectance was determined using 12 and four well-calibrated reference reflectance tarps employing the FieldSpec® 3(Analytical Spectral Devices Inc., Boulder, CO, USA)...
The Ground-Based Absolute Radiometric Calibration of Landsat 8 OLI
Remote Sensing, 2015
This paper presents the vicarious calibration results of Landsat 8 OLI that were obtained using the reflectance-based approach at test sites in Nevada, California, Arizona, and South Dakota, USA. Additional data were obtained using the Radiometric Calibration Test Site, which is a suite of instruments located at Railroad Valley, Nevada, USA. The results for the top-of-atmosphere spectral radiance show an average difference of −2.7, −0.8, 1.5, 2.0, 0.0, 3.6, 5.8, and 0.7% in OLI bands 1-8 as compared to an average of all of the ground-based measurements. The top-of-atmosphere spectral reflectance shows an average difference of 1.6, 1.3, 2.0, 1.9, 0.9, 2.1, 3.1, and 2.1% from the ground-based measurements. Except for OLI band 7, the spectral radiance results are generally within ±5% of the design specifications, and the reflectance results are generally within ±3% of the design specifications. The results from the data collected during the tandem Landsat 7 and 8 flight in March 2013 indicate that ETM+ and OLI agree to each other to within ±2% in similar bands in top-of-atmosphere spectral radiance, and to within ±4% in top-of-atmosphere spectral reflectance. OPEN ACCESS Remote Sens. 2015, 7 601
Reflectance-based calibration and validation of the landsat satellite archive
2016
REFLECTANCE-BASED CALIBRATION AND VALIDATION OF THE LANDSAT SATELLITE ARCHIVE SANDEEP KUMAR CHITTIMALLI 2016 The primary objective of this project was to consistently calibrate the entire Landsat series to a common reflectance scale by performing cross-calibration corrections from Landsat-8 OLI to Landsat1 MSS. A consistent radiance-based calibration was already performed from Landsat-8 OLI through Landsat-1 MSS using bright targets and dark targets. The MSS radiance-based calibration results showed an uncertainty of about ±5%. Typically to convert from radiance to reflectance a solar model is used. Unfortunately, there are numerous solar models, all with various levels of accuracies. It was also seen that there is a data format inconsistency for different types of MSS data that impact the radiometric uncertainty of the products when compared to Landsat-8 OLI data. One of the advances Landsat-8 OLI has over to earlier missions is a solar model independent reflectance calibration. He...
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Radiometric Calibration of the Landsat MSS Sensor Series
IEEE Transactions on Geoscience and Remote Sensing, 2000
Multispectral remote sensing of the Earth using Landsat sensors was ushered on July 23, 1972, with the launch of Landsat-1. Following that success, four more Landsat satellites were launched, and each of these carried the Multispectral Scanner System (MSS). These five sensors provided the only consistent multispectral space-based imagery of the Earth's surface from 1972 to 1982. This work focuses on developing both a consistent and absolute radiometric calibration of this sensor system. Cross-calibration of the MSS was performed through the use of pseudoinvariant calibration sites (PICSs). Since these sites have been shown to be stable for long periods of time, changes in MSS observations of these sites were attributed to changes in the sensors themselves. In addition, simultaneous data collections were available for some MSS sensor pairs, and these were also used for cross-calibration. Results indicated substantial differences existed between instruments, up to 16%, and these were reduced to 5% or less across all MSS sensors and bands. Lastly, this paper takes the calibration through the final step and places the MSS sensors on an absolute radiometric scale. The methodology used to achieve this was based on simultaneous data collections by the Landsat-5 MSS and Thematic Mapper (TM) instruments. Through analysis of image data from a PICS location and through compensating for the spectral differences between the two instruments, the Landsat-5 MSS sensor was placed on an absolute radiometric scale based on the Landsat-5 TM sensor. Uncertainties associated with this calibration are considered to be less than 5%.
Remote Sensing
Radiometric calibration of satellite imaging sensors should be performed periodically to account for the effect of sensor degradation in the space environment on image accuracy. In this study, we performed vicarious radiometric calibrations (relying on in situ data) of multispectral imaging sensors on the Korea multipurpose satellite-3 and-3A (KOMPSAT-3 and-3A) to adjust the existing radiometric conversion coefficients according to time delay integration (TDI) adjustments and sensor degradation over time. The Second Simulation of a Satellite Signal in the Solar Spectrum (6S) radiative transfer model was used to obtain theoretical top of atmosphere radiances for both satellites. As input parameters for the 6S model, surface reflectance values of well-characterized pseudo-invariant tarps were measured using dual ASD FieldSpec ® 3 hyperspectral radiometers, and atmospheric conditions were measured using Microtops II ® Sunphotometer and Ozonometer. We updated the digital number (DN) of the radiance coefficients of the satellites; these had been used to calibrate the sensors during in-orbit test periods in 2013 and 2015. The coefficients of determination, R 2 , values between observed DNs of the sensors, and simulated radiances for the tarps were more than 0.999. The calibration errors were approximately 5.7% based on manifested error sources. We expect that the updated coefficients will be an important reference for KOMPSAT-3 and-3A users.
Remote Sensing
This work describes a proposed radiometric cross calibration between the Landsat 8 Operational Land Imager (OLI) and Sentinel 2A Multispectral Instrument (MSI) sensors. The cross-calibration procedure involves (i) correction of the MSI data to account for spectral band differences with OLI and (ii) normalization of Bidirectional Reflectance Distribution Function (BRDF) effects in the data from both sensors using a new model accounting for the view zenith/azimuth angles in addition to the solar zenith/view angles. Following application of the spectral and BRDF normalization, standard least-squares linear regression is used to determine the cross-calibration gain and offset in each band. Uncertainties related to each step in the proposed process are determined, as is the overall uncertainty associated with the complete processing sequence. Validation of the proposed cross-calibration gains and offsets is performed on image data acquired over the Algodones Dunes site. The results of th...
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