Paper
4 October 2023 Intercomparison of Landsat OLI and Terra ASTER solar reflective calibrations using the Radiometric Calibration Network data from Railroad Valley, Nevada
Author Affiliations +
Abstract
This paper presents an intercomparison study between the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Landsat 8 Operational Land Imager (OLI) using data from the Radiometric Calibration Network (RadCalNet). The study evaluates the radiometric performance and agreement between ASTER and Landsat 8 OLI, focusing on their spectral bands relevant for vegetation analysis and land cover classification. The analysis includes the assessment of data quality, uncertainties, and factors influencing the measurements. The results demonstrate the usability of RadCalNet in evaluating the accuracy and reliability of remote sensing data. The findings contribute to our understanding of the strengths and limitations of ASTER and Landsat 8 OLI, supporting informed decision-making in environmental monitoring and resource management. Overall, the intercomparison study provides valuable insights into the capabilities and limitations of ASTER and Landsat 8 OLI, highlighting the importance of RadCalNet in assessing the radiometric performance of remote sensing sensors. The results from the Railroad Valley RadCalNet show that the site is suitable for sensors with spatial resolutions as small as 15 m. The comparison between ASTER and OLI demonstrates that the recent update to the ASTER radiometric calibration provides results that are in agreement with Landsat 8 OLI to well within the absolute radiometric uncertainties of both sensors.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
M. Yarahmadi, K. J. Thome, B. N. Wenny, J. Czapla-Myers, M. Tahersima, N. Voskanian, and S. Eftekharzadeh "Intercomparison of Landsat OLI and Terra ASTER solar reflective calibrations using the Radiometric Calibration Network data from Railroad Valley, Nevada", Proc. SPIE 12685, Earth Observing Systems XXVIII, 1268515 (4 October 2023); https://doi.org/10.1117/12.2677409
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KEYWORDS
Landsat

Sensors

Reflectivity

Radiometric calibration

Vegetation

Near infrared

Remote sensing

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