Groeneveld, D.; Ruggles, T.; Gao, B. Landsat-8/9 Atmospheric Correction Reliability Using Scene-Statistics. Preprints2024, 2024041745. https://doi.org/10.20944/preprints202404.1745.v1
APA Style
Groeneveld, D., Ruggles, T., & Gao, B. (2024). Landsat-8/9 Atmospheric Correction Reliability Using Scene-Statistics. Preprints. https://doi.org/10.20944/preprints202404.1745.v1
Chicago/Turabian Style
Groeneveld, D., Tim Ruggles and Bo-Cai Gao. 2024 "Landsat-8/9 Atmospheric Correction Reliability Using Scene-Statistics" Preprints. https://doi.org/10.20944/preprints202404.1745.v1
Abstract
Smallsats are becoming the predominant electro-optical Earth observation (EO) imaging platforms. While atmospheric correction of smallsat data enhances its utility, an established pathway to do so may constrain accuracy and utility. The alternative, Closed-form Method for Atmospheric Correction (CMAC), developed for smallsat application provides surface reflectance derived solely from scene statistics. In a prior paper, CMAC closely agreed with Land Surface Reflectance Code (LaSRC) software for correction of the four VNIR bands of Landsat-8/9 images for conditions of low to moderate atmospheric effect over quasi-invariant warehouse-industrial targets. Those results were accepted as surrogate surface reflectance to support analysis of CMAC and LaSRC reliability for surface reflectance retrieval in two contrasting environments: shortgrass prairie and barren desert. Reliability was defined and tested through a null hypothesis: the same top-of-atmosphere reflectance under the same atmospheric condition will provide the same estimate of surface reflectance. Evaluated against the prior surrogate surface reflectance, the results found decreasing error with increasing wavelength for both methods. From 58 comparisons across the four bands, LaSRC average absolute error ranged from 0.59% (NIR) to 50.30% (blue). CMAC error was well constrained from 0.01% (NIR) to 0.98% (blue) sustaining the null hypothesis for reliability.
Keywords
surface reflectance; retrieval; LaSRC; CMAC; scene statistics; near real-time; spectral diversity
Subject
Engineering, Aerospace Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
