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.
Higher spatial and temporal resolution in Earth observation (EO) imagery is beneficial for many applications, including real-time hazard monitoring and agriculture. SI-traceable intercomparison between concurrent Earth imaging satellites can help harmonizing and improving spatial or temporal resolution of their data products. To that end, the Committee on Earth Observation Satellites (CEOS) initiated the Radiometric Calibration Network (RadCalNet) to provide automated surface and top-of-atmosphere TOA reflectance data from multiple participating ground sites to the worldwide user community. Here, we report results of the intercomparison between Landsat-8 Operational Land Imager (OLI) and National Oceanic and Atmospheric Administration-20 (NOAA-20) Visible Infrared Imaging Radiometer Suite (VIIRS) in the wavelength range from 400 nm to 2500 nm using RadCalNet as a common reference. The results of this study indicate that RadCalNet is a valuable tool for harmonization of EO imagery even in the case where the sensors have different temporal and spatial resolutions. Both OLI and VIIRS are calibrated to well-within their absolute radiometric calibration uncertainties and the two sensors agree with each other to better than 2% using RadCalNet sites as a common reference.
Combining images from multiple Earth Observing (EO) satellites increases the temporal resolution of the data; overcoming the limitations imposed by low revisit time and cloud coverage. However, this requires an inter-calibration process, to ensure that there is no radiometric difference in top-of-atmosphere (TOA) observations and to quantify any offset in the respective instruments. In addition, combining vicarious calibration processes to the inter calibration of instruments can provide a useful mechanism to validate and compare data from multiple sensors. The Radiometric Calibration Network (RadCalNet) provides automated surface and top-of atmosphere reflectance data from multiple participating ground sites that can be used for instrument vicarious calibration. We present comparative analysis of the Landsat 8 and Landsat 9 Operational Land ImagerOLI) sensors and validate the data by comparing them to measurements from RadCalNet sites as a quantitative inter-calibration approach. The presented process provides SItraceable inter calibration methodology and quantifies the offset and uncertainty in the OLI and MSI instruments to assess if the data can be reliably cross corelated and used by the scientific community.
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