Vicarious Methodologies to Assess and Improve the Quality of the Optical Remote Sensing Images: A Critical Review

Over the past decade, number of optical Earth observing satellites performing remote sensing has increased substantially, dramatically increasing the capability to monitor the Earth. The quantity of remote sensing satellite increase is primarily driven by improved technology, miniaturization of components, reduced manufacturing, and launch cost. These satellites often lack on-board calibrators that a large satellite utilizes to ensure high quality (e.g., radiometric, geometric, spatial quality, etc.) scientific measurement. To address this issue, this work presents “best” vicarious image quality assessment and improvement techniques for those kinds of optical satellites which lacks on-board calibration system. In this article, image quality categories have been explored, and essential quality parameters (e.g., absolute and relative calibration, aliasing, etc.) have been identified. For each of the parameters, appropriate characterization methods are identified along with its specifications or requirements. In cases of multiple methods, recommendation has been made based-on the strengths and weaknesses of each method. Furthermore, processing steps have been presented, including examples. Essentially, this paper provides a comprehensive study of the criteria that needs to be assessed to evaluate remote sensing satellite data quality, and best vicarious methodologies to evaluate identified quality parameters such as coherent noise, ground sample distance, etc

Sentinel-2/MSI and LANDSAT8/OLI Radiometry Intercomparison Using RadCalNet Dataset and DIMITRI-toolbox

The Radiometric Calibration Network (RadCalNet) has been established by the Committee on Earth Observation Satellites (CEOS) Working Group on Calibration and Validation (WGCV) Infrared and Visible Optical Sensors Subgroup (IVOS) in 2013 and is open to public since July 2018. The RadCalNet consists of four international test sites providing automated in situ measurements and estimates of propagated top-of-atmosphere (TOA) reflectance (Bouvet et al. 2019). This work based on the work of Alhammoud et al. (2019) for the Sentinel-2/MSI validation; and on the work of Jing et al. (2019) to correct the directional effect. In this study we extend Alhammoud et al. (2019) analysis over RadCalNet up to 2021, instead of 2018. In addition, we will present the results of a cross-mission intercomparison over RadCalNet sites for MSI-A, MSI-B and OLI-8 using DIMITRI-Toolbox. The results confirm the viewing angle effect in the Sentinel-2 data at the RVUS and LCFR sites. The correction of the directional effect improves the results over the ratios of the individual orbits by up to 5% -10%, while the average ratios has been improved by barely about 1%. However the intercomparison results illustrate the relevance of RadCalNet dataset for the vicarious validation activity. Alhammoud et al. Sentinel-2 Level-1 Radiometry Assessment Using Vicarious Methods from DIMITRI Toolbox and Field Measurements From RadCalNet Database. IEEE JSTAR, 2019, Vol: 12(9) Bouvet et al. RadCalNet: A Radiometric Calibration Network for Earth Observing Imagers Operating in the Visible to Shortwave Infrared Spectral Range. Remote Sens. 2019, 11, 2401. https://doi.org/10.3390/rs11202401 Jing et al. Evaluation of RadCalNet Output Data Using Landsat 7, Landsat 8, Sentinel 2A, and Sentinel 2B Sensors. Remote Sens. 2019, 11, 541