Atmospheric Lengthscales for Global VSWIR Imaging Spectroscopy

Abstract

Future global Visible Shortwave Infrared Imaging Spectrometers, such as the Surface Biology and Geology (SBG) mission, will regularly cover the Earth's entire terrestrial land area. These missions need high fidelity atmospheric correction to produce consistent maps of terrestrial and aquatic ecosystem traits. However, estimation of surface reflectance and atmospheric state is computationally challenging, and the terabyte data volumes of global missions will exceed available processing capacity. This article describes how missions can overcome this bottleneck using the spatial continuity of atmospheric fields. Contemporary imaging spectrometers oversample atmospheric spatial variability, so it is not necessary to invert every pixel. Spatially sparse solutions can train local linear emulators that provide fast, exact inversions in their vicinity. We find that estimating the atmosphere at 200 m scales can outperform traditional atmospheric correction, improving speed by one to two orders of magnitude with no measurable penalty to accuracy. We validate performance with an airborne field campaign, showing reflectance accuracies with RMSE of 1.1% or better compared to ground measurements of diverse targets. These errors are statistically consistent with retrieval uncertainty budgets. Local emulators can close the efficiency gap and make rigorous model inversion algorithms feasible for global missions such as SBG.

An Accuracy Assessment of the Surface Reflectance Product from the EMIT Imaging Spectrometer

“…The model inversion process optimizes the posterior probability of the state vector given the measurement. To date, the OE approach used by EMIT has been validated in airborne campaigns for terrestrial environments [12,20,21] and aquatic scenarios [22,23,24].…”

“…The EMIT data volumes require additional consideration. EMIT leverages the fact that the atmosphere changes over larger spatial scales more so than the instrument spatial sampling [21]. Consequently, it is only necessary to calculate the complete surface and atmosphere solution at a subset of spatial locations.…”

“…First, EMIT's atmospheric model does not represent the wide range of aerosol optical properties on Earth's surface. It uses a simple scattering aerosol derived from sulfate optical properties [21], which performs well across a wide range of environments. Second, there are other radiative transfer approximations not captured in the S d , such as the resampling of optical coefficients to instrument wavelengths (rather than conducting all calculations at the highest possible spectral resolution).…”

Effects of Atmospheric, Topographic, and BRDF Correction on Imaging Spectroscopy-Derived Data Products

“…Topography, especially in rugged mountainous terrain, additionally complicates reflectance retrievals, since the terrain orientation towards the sun changes with observation and illumination geometry and, thus, affects actual surface irradiance due to incidence angle-related irradiance variations, changes in diffuse sky irradiance, and changes in terrain irradiance. If not properly accounted for, topography effects lead to wavelength-dependent HCRF differences between pixels with similar surface properties but different orientation, and can alter the robustness of subsequently retrieved surface information [27], [28], [29]. Topographic compensation (or topographic correction) methods account for such illumination dynamics.…”

Unified Topographic and Atmospheric Correction for Remote Imaging Spectroscopy

“…Although this approach helps to even out the visual differences in terrain shading within the scene, it is far from optimal. In principle, topography affects both the color and intensity of downwelling illumination onto the pixel via the magnitudes of diffuse and direct flux per unit area (Thompson et al, 2022). This could modify the atmospheric correction solution, in particular the interpretation of aerosol scattering that causes similar distortions to the spectral shape.…”