About the Transferability of Topographic Correction Methods From Spaceborne to Airborne Optical Data

Abstract

In rugged terrain, topography substantially influences the illumination and observation geometry and thus the bidirectional reflectance distribution function (BRDF) of a surface. While this problem has been known and investigated for spaceborne optical data since the 1980s, it has led to several well-known topographic correction methods. To date, the methods developed for spaceborne data were equivalently applied to airborne data with distinctly higher spatial resolution, illumination/observation angle configurations and finally (instantaneous) field of view ((i)FOV). On the one hand, this paper evaluates, whether such a transfer of methods from spaceborne to airborne acquisitions is reasonable. On the other hand, a new Lambertian/statistical-empirical (LA+SE) correction method is introduced. While in the spaceborne case the modified Minnaert (MM) and the statistical-empirical (SE) methods performed best, MM led to the statistically and visually best compromise for the airborne data. Our results suggest further, that with a higher spatial resolution various effects come into play (FOV widening; changing the fraction of geometric, volumetric and isotropic scattering, etc.), compromising previously successful methods, such as the statistical-empirical (SE) method.

Spatial resolution, spectral metrics and biomass are key aspects in estimating plant species richness from spectral diversity in species‐rich grasslands

“…Similarly, varying observation geometries between the sun, target pixel and sensor, the so‐called bidirectional reflectance distribution function (BRDF), can heavily affect the measured spectral information (Müller et al., 1998; Schaepman‐Strub et al., 2006), which can result in a few species causing high spectral diversity. We tried to reduce BRDF effects by using a high amount of image overlap, which produces near‐nadir view geometries (Assmann et al., 2019) but did not further minimize BRDF effects (Li et al., 2012; Vögtli et al., 2021; Wierzbicki et al., 2018). Yet, we think that it may be valuable to address these issues in future studies.…”

Near-Infrared Radiance of Vegetation is More Sensitive Than Vegetation Indices for Monitoring NPP of Winter Wheat Under Water Stress

“…The BRDF model takes into account the solar geometric effect, which makes the corrected data more consistent with the real surface reflectance characteristics. The BRDF model not only takes into account the directionality of the solar radiation, but also takes into account the variation of the observation direction [50]. This is very important for the comparison and analysis of remote sensing data under different observation conditions.…”

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

“…[31] provide a detailed overview of the most common approaches. Most of these topographic compensation methods were developed for spacebased systems with spatial resolutions of 30 m or more, but can be adapted to high-spatial-resolution airborne systems with resolutions of few meters or less [32]. While in most algorithms, the atmospheric and topographic compensation are sequential operations, i.e., a post-hoc topographic compensation, recent approaches obtained promising results from a joint atmospheric and topographic compensation [33].…”

“…Recently, several studies separately compared different atmospheric [25], topographic [32], or anisotropy [52] compensation schemes. To our knowledge, however, thus far no study provided a systematic assessment of atmospheric, topographic, and anisotropy effects in high-resolution imaging spectroscopy data in order to identify their impact on derived surface information.…”