Surface Reflectance Field Research Articles

Quantifying the direct radiative effect of absorbing aerosols for numerical weather prediction: a case study.

We conceptualize aerosol radiative transfer processes arising from the hypothetical coupling of a global aerosol transport model and a global numerical weather prediction model by applying the US Naval Research Laboratory Navy Aerosol Analysis and Prediction System (NAAPS) and the Navy Global Environmental Model (NAVGEM) meteorological and surface reflectance fields. A unique experimental design during the 2013 NASA Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) field mission allowed for collocated airborne sampling by the high spectral resolution Lidar (HSRL), the Airborne Multi-angle SpectroPolarimetric Imager (AirMSPI), up/down shortwave (SW) and infrared (IR) broadband radiometers, as well as NASA A-Train support from the Moderate Resolution Imaging Spectroradiometer (MODIS), to attempt direct aerosol forcing closure. The results demonstrate the sensitivity of modeled fields to aerosol radiative fluxes and heating rates, specifically in the SW, as induced in this event from transported smoke and regional urban aerosols. Limitations are identified with respect to aerosol attribution, vertical distribution, and the choice of optical and surface polarimetric properties, which are discussed within the context of their influence on numerical weather prediction output that is particularly important as the community propels forward towards inline aerosol modeling within global forecast systems.

Impacts of dust aerosol and adjacency effects on the accuracy of Landsat 8 and RapidEye surface reflectances

The atmospheric correction of satellite data is challenging over desert agricultural systems, due to the relatively high aerosol optical thicknesses (τ550), bright soils, and a heterogeneous surface reflectance field. Indeed, the contribution of reflected radiation from adjacent pixels scattered into the field of view of a target pixel is considerable and can significantly affect the fidelity of retrieved reflectances. In this study, uncertainties and quantitative errors associated with the atmospheric correction of multi-spectral Landsat 8 and RapidEye data were characterized over a desert agricultural landscape in Saudi Arabia. Surface reflectances were retrieved using an implementation of the 6SV atmospheric correction code, and validated against field collected spectroradiometer measurements over desert, cultivated soil, and vegetated surface targets. A combination of satellite and Aerosol Robotic Network (AERONET) data were used to parameterize aerosol properties and atmospheric state parameters. With optimal specification of τ550 and aerosol optical properties and correction for adjacency effects, the relative Mean Absolute Deviation (MAD) for all bands combined was 5.4% for RapidEye and 6.8% for Landsat 8. However uncertainties associated with satellite-based τ550 retrievals were shown to introduce significant error into the reflectance estimates. With respect to deriving common vegetation indices from corrected reflectance data, the Normalized Difference Vegetation Index (NDVI) was associated with the smallest errors (3–8% MAD). Surface reflectance errors were highest for bands in the visible part of the spectrum, particularly the blue band (5–16%), while there was more consistency within the red-edge (~5%) and near-infrared (5–7%). Results were generally better constrained when a τ550-dependent aerosol model for desert dust particles, parameterized on the basis of nearby AERONET site data, was used in place of a generic rural or background desert model. This adaptation was particularly pertinent for the Landsat bands in the shortwave infrared. Failure to correct for adjacency effects increased the overall surface reflectance MAD to around 18%. The impact was especially significant for the visible bands over vegetated surface targets, as evidenced by relative MADs increasing to >200%. In comparison, a relatively minor adjacency effect was observed within the near-infrared and over the more reflective bare soil and desert sites. Overall, the impact of adjacency effects was substantial (20–25% MAD) for all of the studied vegetation indices. This investigation fills a research gap in the quantification of uncertainties and evaluation of achievable accuracy levels in high spatial resolution surface reflectance imagery over desert agriculture and highlights the need for accurate and regionally representative atmospheric correction techniques.

Sand dune ridge alignment effects on surface BRF over the Libya-4 CEOS calibration site.

The Libya-4 desert area, located in the Great Sand Sea, is one of the most important bright desert CEOS pseudo-invariant calibration sites by its size and radiometric stability. This site is intensively used for radiometer drift monitoring, sensor intercalibration and as an absolute calibration reference based on simulated radiances traceable to the SI standard. The Libya-4 morphology is composed of oriented sand dunes shaped by dominant winds. The effects of sand dune spatial organization on the surface bidirectional reflectance factor is analyzed in this paper using Raytran, a 3D radiative transfer model. The topography is characterized with the 30 m resolution ASTER digital elevation model. Four different regions-of-interest sizes, ranging from 10 km up to 100 km, are analyzed. Results show that sand dunes generate more backscattering than forward scattering at the surface. The mean surface reflectance averaged over different viewing and illumination angles is pretty much independent of the size of the selected area, though the standard deviation differs. Sun azimuth position has an effect on the surface reflectance field, which is more pronounced for high Sun zenith angles. Such 3D azimuthal effects should be taken into account to decrease the simulated radiance uncertainty over Libya-4 below 3% for wavelengths larger than 600 nm.

Data‐driven Local Coordinate Systems for Image‐Based Rendering

Abstract Image‐based representations of an object profit from known geometry. The more accurate this geometry is known, the better corresponding pixels in the different images can be aligned, which leads to less artifacts and better compression performance. For opaque objects the per‐pixel data can then be interpreted as a sampling of the BRDF at the respective surface point. In order to parameterize this sampled data a coordinate frame has to be defined. In previous work this coordinate frame was either the global frame or a local frame derived from the base geometry. Both approaches lead to misalignments between sample vectors: Features of basically very similar BRDFs will be shifted to different regions in the sample vector leading to poor compression performance. In order to improve alignment between the sampled BRDFs in image‐based rendering, we propose an optimization algorithm which determines consistent coordinate frames for every sample point on the object surface. This way we efficiently align the features even of anisotropic reflection functions and reconstruct approximate local coordinate frames without performing an explicit 3D‐reconstruction. The optimization is calculated efficiently by exploiting the Fourier‐shift theorem for spherical harmonics. In order to deal with different materials in a scene, the technique is combined with a clustering algorithm. We demonstrate the utility of our method by applying it to BTFs and 6D surface reflectance fields. Categories and Subject Descriptors (according to ACM CCS): I.3.3 [Picture/Image Generation]: Digitizing and scanning I.3.7 [Three‐Dimensional Graphics and Realism]: Color, shading, shadowing, and texture

Using 1-D models to interpret the reflectance anisotropy of 3-D canopy targets: issues and caveats

This paper evaluates 1) to what extent one-dimensional (1-D) models can be used to represent the magnitude and directionality of the surface reflectance field of heterogeneous canopy targets at different spatial resolutions, and 2) whether this usage results in significant biases in the estimation of the corresponding state variables. It will be seen that when both the 1-D and three-dimensional (3-D) models account for all features of the measured radiation field, then-in the absence of further information regarding the nature and structure of the target-the use of a 3-D model may amount to an over-interpretation of the available data. The simplified surface structure formulation contained within the 1-D model, on the other hand, may affect the values of the state variables that such models will retrieve. This is because the shape of the reflectance anisotropy of the 3-D target is almost always different from that of a structurally homogeneous (1-D) canopy with the same state variable values but no foliage clumping. By consequence the 1-D canopies that are capable of mimicking the bell (or bowl) shaped reflectance anisotropy of 3-D targets will tend to feature lower leaf area index, higher soil albedo and, in particular, predominantly erectophile (or plagiophile) leaf normal distributions.

Rendering Deformable Surface Reflectance Fields

Animation of photorealistic computer graphics models is an important goal for many applications. Image-based modeling has emerged as a promising approach to capture and visualize real-world objects. Animating image-based models, however, is still a largely unsolved problem. In this paper, we extend a popular image-based representation called surface reflectance field to animate and render deformable real-world objects under arbitrary illumination. Deforming the surface reflectance field is achieved by modifying the underlying impostor geometry. We augment the impostor by a local parameterization that allows the correct evaluation of acquired reflectance images, preserving the original light model on the deformed surface. We present a deferred shading scheme to handle the increased amount of data involved in shading the deformable surface reflectance field. We show animations of various objects that were acquired with 3D photography.

Image-based 3D photography using opacity hulls

We have built a system for acquiring and displaying high quality graphical models of objects that are impossible to scan with traditional scanners. Our system can acquire highly specular and fuzzy materials, such as fur and feathers. The hardware set-up consists of a turntable, two plasma displays, an array of cameras, and a rotating array of directional lights. We use multi-background matting techniques to acquire alpha mattes of the object from multiple viewpoints. The alpha mattes are used to construct an opacity hull. The opacity hull is a new shape representation, defined as the visual hull of the object with view-dependent opacity. It enables visualization of complex object silhouettes and seamless blending of objects into new environments. Our system also supports relighting of objects with arbitrary appearance using surface reflectance fields, a purely image-based appearance representation. Our system is the first to acquire and render surface reflectance fields under varying illumination from arbitrary viewpoints. We have built three generations of digitizers with increasing sophistication. In this paper, we present our results from digitizing hundreds of models.