Abstract

In 2013, the Committee on Earth Observation Satellites (CEOS) Working Group on Calibration and Validation (WGCV) Infrared and Visible Optical Sensors Subgroup (IVOS) established the Radiometric Calibration Network (RadCalNet), consisting of four international test sites providing automated in situ measurements and estimates of propagated top-of-atmosphere (TOA) reflectance. This work evaluates the ‘reliability’ of RadCalNet TOA reflectance data at three of these sites—RVUS, LCFR, and GONA—using Landsat 7 ETM+, Landsat 8 operational land imager (OLI), and Sentinel 2A/2B (S2A/S2B) MSI TOA reflectance data. This work identified a viewing angle effect in the MSI data at the RVUS and LCFR sites; when corrected, the overall standard deviation in relative reflectance differences decreased by approximately 2% and 0.5% at the RVUS and LCFR sites, respectively. Overall, the relative mean differences between the RadCalNet surface data and sensor data for the RVUS and GONA sites are within 5% for ETM+, OLI, and S2A MSI, with an approximately 2% higher difference in the S2B MSI data at the RVUS site. The LCFR site is different from the other two sites, with relative mean differences ranging from approximately -10% to 1%, even after performing the viewing angle effect correction on the MSI data. The data from RadCalNet are easy to acquire and use. More effort is needed to better understand the behavior at LCFR. One significant improvement on the accuracy of the RadCalNet data might be the development of a site-specific BRDF characterization and correction.

Highlights

  • The increasing number of Earth observing satellite sensors requires accurate SI-traceable radiometric calibrations to ensure data consistency between them

  • Columnar water vapor, columnar ozone, aerosol optical depth at 550 nm, and Angstrom coefficient measurements serve as inputs to a Radiative Transfer Model (RTM) that predicts the corresponding

  • The selected image datasets were downloaded from the sensor operator; ETM+, operational land imager (OLI), and MSI image data were downloaded through the US Geological Survey (USGS) EarthExplorer portal

Read more

Summary

Introduction

The increasing number of Earth observing satellite sensors requires accurate SI-traceable radiometric calibrations to ensure data consistency between them. Launch date Spectral bands (used in this study) Pixel size (m) Conversion to TOA reflectance equation *

Data Selection
Cloud and Cloud Shadow Filtering
Image ROI Reflectance Extraction
Image View Angle Effect Corrections
RadCalNet Reflectance Extraction
Reflectance difference Analysis
TOA Reflectance Comparison Uncertaity Analysis
Comparison of RVUS Results

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.