Session
Weekday Session 8: Advanced Technologies I
Location
Utah State University, Logan, UT
Abstract
The future of remote sensing is imaging smallsats; however, assuring their data utility requires atmospheric correction (AC). Current methods are difficult to apply and often fail to provide accurate surface reflectance retrieval even for the most common levels of atmospheric aerosol loading; this impediment is increasing annually due to wildfires induced by climate change. Closed-form Method for Atmospheric Correction (CMAC), developed for smallsats using Sentinel-2 data, is applicable to all imaging satellites. CMAC uses only scene statistics for automated near real-time AC while bypassing ancillary data that delays existing methods by days. In this paper, data from two research-grade satellite systems, Landsat-8/9 and Sentinel-2, were test corrected by CMAC for 323 individual image/area-of-interest combinations and compared to two bespoke industry-accepted software packages, LaSRC and Sen2Cor. The CMAC Sentinel-2 calibration was adjusted to Landsat-8/9 spectral responses using single points per band as a test for rapid calibration of smallsats. The results verified CMAC accurately retrieved the same surface reflectance distribution as LaSRC, but without limitations imposed through radiative transfer. CMAC-corrected data were more accurate than both Sen2Cor and LaSRC over a much wider range of atmospheric effect. These results are verifiable through cloud-based test-corrections and publicly available data-analysis spreadsheets.
CMAC Smallsat Atmospheric Correction With Scene Statistics: Superior Accuracy in Near Real-Time
Utah State University, Logan, UT
The future of remote sensing is imaging smallsats; however, assuring their data utility requires atmospheric correction (AC). Current methods are difficult to apply and often fail to provide accurate surface reflectance retrieval even for the most common levels of atmospheric aerosol loading; this impediment is increasing annually due to wildfires induced by climate change. Closed-form Method for Atmospheric Correction (CMAC), developed for smallsats using Sentinel-2 data, is applicable to all imaging satellites. CMAC uses only scene statistics for automated near real-time AC while bypassing ancillary data that delays existing methods by days. In this paper, data from two research-grade satellite systems, Landsat-8/9 and Sentinel-2, were test corrected by CMAC for 323 individual image/area-of-interest combinations and compared to two bespoke industry-accepted software packages, LaSRC and Sen2Cor. The CMAC Sentinel-2 calibration was adjusted to Landsat-8/9 spectral responses using single points per band as a test for rapid calibration of smallsats. The results verified CMAC accurately retrieved the same surface reflectance distribution as LaSRC, but without limitations imposed through radiative transfer. CMAC-corrected data were more accurate than both Sen2Cor and LaSRC over a much wider range of atmospheric effect. These results are verifiable through cloud-based test-corrections and publicly available data-analysis spreadsheets.
