Landsat-8 Operational Land Imager Radiometric Calibration and Stability

Abstract

Abstract:The Landsat-8 Operational Land Imager (OLI) was radiometrically calibrated prior to launch in terms of spectral radiance, using an integrating sphere source traceable to National Institute of Standards and Technology (NIST) standards of spectral irradiance. It was calibrated on-orbit in terms of reflectance using diffusers characterized prior to launch using NIST traceable standards. The radiance calibration was performed with an uncertainty of ~3%; the reflectance calibration to an uncertainty of ~2%. On-orbit, multiple calibration techniques indicate that the sensor has been stable to better than 0.3% to date, with the exception of the shortest wavelength band, which has degraded about 1.0%. A transfer to orbit experiment conducted using the OLI's heliostat-illuminated diffuser suggests that some bands increased in sensitivity on transition to orbit by as much as 5%, with an uncertainty of OPEN ACCESS Remote Sens. 2014, 6 12276 ~2.5%. On-orbit comparisons to other instruments and vicarious calibration techniques show the radiance (without a transfer to orbit adjustment), and reflectance calibrations generally agree with other instruments and ground measurements to within the uncertainties. Calibration coefficients are provided with the data products to convert to either radiance or reflectance units.

Comparison of the Continuity of Vegetation Indices Derived from Landsat 8 OLI and Landsat 7 ETM+ Data among Different Vegetation Types

“…It is important to study continuity among sensors from the same series of satellites by considering of the important parameters including sensor characteristics, over-pass time, scanning system, angular affect and etc. A few studies related to the continuity of Landsat 8 have been conducted, including preflight and post-launch calibrations [28][29][30][31][32][33]. Most of these studies have shown that the continuity between the Landsat-8 OLI and Landsat-7 ETM+ is good.…”

“…Most of these studies have shown that the continuity between the Landsat-8 OLI and Landsat-7 ETM+ is good. Markham conducted a pre-launch and on-orbit radiometric characterization and calibration of Landsat 8 and found that the uncertainty of radiance calibration performance was within 2%, while for the reflectance calibration it was within 3% [29]. Li compared the consistency of four spectral indices for four land cover types in southeast Asia and found the correlation coefficients (R 2 ) to be a maximum of 0.96 for measurements over a two-day period [33].…”

Radiometric Non-Uniformity Characterization and Correction of Landsat 8 OLI Using Earth Imagery-Based Techniques

“…The first panel, known as the "working" panel, is deployed about every eight days to characterize OLI's detectors. The second panel, known as the "pristine" panel, is deployed approximately bi-yearly to track changes in the working panel due to UV degradation from solar exposure [5].…”

“…The visible/near-infrared (VNIR) and panchromatic (PAN) bands (1-5 and 8) utilize silicon p-intrinsic-n (SiPIN) detectors, while the SWIR bands (6,7,9) use mercury-cadmium-telluride (HgCdTe) detectors for imaging [3]. Single and double backup detector arrays are present in each FPM for each SiPIN and HgCdTe band, respectively [4,5]. In addition to FPM-level staggering, the detectors in each FPM are staggered in even-odd sets, as shown in Figure 1b.…”

Landsat 15-m Panchromatic-Assisted Downscaling (LPAD) of the 30-m Reflective Wavelength Bands to Sentinel-2 20-m Resolution

“…For example, recent research suggests that the integration of the Landsat-8 and Sentinel-2 data would be beneficial for applications including agricultural mapping and monitoring [5][6][7], phenological studies [8], and glacier extent mapping [9]. There are a number of pre-processing issues that need to be addressed before the well calibrated Landsat-8 [10,11] and Sentinel-2A [2,12] data can be used together or treated as effectively being sensed from the same sensor. These include handling the different sensor spectral response functions and correction for atmospheric effects [13,14], correction of surface reflectance anisotropy [15,16], and handling image tiling and geolocation differences [17][18][19].…”