Variability in Surface BRDF at Different Spatial Scales (30 m-500 m) Over a Mixed Agricultural Landscape as Retrieved from Airborne and Satellite Spectral Measurements

Over the past decade, the role of multiangle remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities represented by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained approx.1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75 off-nadir, and at spatial resolutions ranging from 3 m - 500 m. This unique dataset was used to examine the interaction of the spatial and angular characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution; and (3) the uncertain ties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure

Modelling bidirectional radiance measurements collected by the advanced solid-state array spectroradiometer over Oregon transect conifer forests

Thesis (M.A.)--Boston UniversityThe primary objective of this research is to test and validate a geometric-optical bidirectional reflectance canopy model developed by Li and Strahler, with respect to actual forest canopy reflectance measurments. This model treats forest canopies as scenes of discrete, three dimensional objects that are illuminated and viewed from different positions in the hemisphere. The shapes of the objects, their count densities and patterns of placement are the driving variables, and they condition the mixture of sunlit and shaded objects and background that is observed from a particular viewing direction, given a direction of illumination. This mixture, in turn, controls the brightness apparent to an observer or a radiometric instrument. The Advanced Solid-State Array Spectroradiometer (ASAS) is chosen to be the sensor having the ability of collecting measurements at various look angles and its imaged reflectance was used to validate the model. The modelled BRF's were compared to actual ASAS measured BRF's in sites with different canopy structures and densities. The comparision revealed execellent match between the modelled and measured reflectance, and great ability of the model in predicting the shape and magnitude of the BRDF, in almost all the sites investigated. It is concluded that the geometric optics approach provided a good way to model the bidirectional reflectance distribution function of natural vegetation canopies, that captures the most important features exhibited by bidirectional measurements of such canopies. Further modifications have been suggested that will improve the predicted BRF's, and yield better results. [TRUNCATED

Electromagnetic analysis of bidirectional reflectance from roughened surfaces and applications to surface shape recovery

Scattering from randomly rough surfaces is a well-established sub area of electrodynamics. There remains much to be done since each surface and optical processes that may occur in within the scattering medium, and countless other scenarios, is different. There are also illumination models that describe lighting in a scene on the macroscopic scale where geometrical optics can be considered adequate. Of particular interest for us is the intersection of the physical scattering theories and the illumination models. We present two contributions: 1) A minimum of two independent images are needed since any opaque surface can be uniquely specified in terms of its outward-normal vector field. This required the development of a global, nonlinear, alternating optimization scheme to compute parameter estimates. It is shown that high accuracy estimates can be obtained. 2)The smooth emergence of geometrical optics from physical optics using a full wave electromagnetic solution of the 1D scattering problem. It is shown here that the geometrical optics limit is arrived at in a smooth transition from physical optics starting with the electric field integral equation by varying the size of roughness structures on the surface and calculating the scattering cross length . Starting from roughness features smaller than the incident wavelength and also considering the size of the surface fluctuations relative to the size of the surface, the scattered light patterns show expected wave behavior that gradually transitions to geometrical ray optics as the size of surface roughness features increases well beyond the wavelength

The Impact of Surface Normals on Appearance

The appearance of an object is the result of complex light interaction with the object. Beyond the basic interplay between incident light and the object\u27s material, a multitude of physical events occur between this illumination and the microgeometry at the point of incidence, and also beneath the surface. A given object, made as smooth and opaque as possible, will have a completely different appearance if either one of these attributes - amount of surface mesostructure (small-scale surface orientation) or translucency - is altered. Indeed, while they are not always readily perceptible, the small-scale features of an object are as important to its appearance as its material properties. Moreover, surface mesostructure and translucency are inextricably linked in an overall effect on appearance. In this dissertation, we present several studies examining the importance of surface mesostructure (small-scale surface orientation) and translucency on an object\u27s appearance. First, we present an empirical study that establishes how poorly a mesostructure estimation technique can perform when translucent objects are used as input. We investigate the two major factors in determining an object\u27s translucency: mean free path and scattering albedo. We exhaustively vary the settings of these parameters within realistic bounds, examining the subsequent blurring effect on the output of a common shape estimation technique, photometric stereo. Based on our findings, we identify a dramatic effect that the input of a translucent material has on the quality of the resultant estimated mesostructure. In the next project, we discuss an optimization technique for both refining estimated surface orientation of translucent objects and determining the reflectance characteristics of the underlying material. For a globally planar object, we use simulation and real measurements to show that the blurring effect on normals that was observed in the previous study can be recovered. The key to this is the observation that the normalization factor for recovered normals is proportional to the error on the accuracy of the blur kernel created from estimated translucency parameters. Finally, we frame the study of the impact of surface normals in a practical, image-based context. We discuss our low-overhead, editing tool for natural images that enables the user to edit surface mesostructure while the system automatically updates the appearance in the natural image. Because a single photograph captures an instant of the incredibly complex interaction of light and an object, there is a wealth of information to extract from a photograph. Given a photograph of an object in natural lighting, we allow mesostructure edits and infer any missing reflectance information in a realistically plausible way

An atmospheric correction algorithm for FY3/MERSI data over land in China

Feng-Yun (FY-3) is the second generation of the Chinese Polar Orbiting Meteorological Satellites with global, three-dimensional, quantitative, and multispectral capabilities. Medium Resolution Spectral Imager (MERSI) has 20 channels onboard the FY-3A and FY-3B satellites, including five channels (four VIS and one thermal IR) with a spatial resolution of 250m. The top of the atmosphere signal are necessary to be radiometrically calibrated and corrected for atmospheric effects based on surface reflectance, especially in land surface remote sensing and applications. This paper presents an atmospheric correction algorithm for FY3/MERSI data over land in China, taking into account the directional properties of the observed surface by a kernel-based Bi-directional Reflectance Distribution Function (BRDF) model. The comparison with MODGA and ASD reflectance showed that there is a good agreement. Therefore, FY3/MERSI can serve a reliable and new data source for quantifying global environment change

Compression, Modeling, and Real-Time Rendering of Realistic Materials and Objects

The realism of a scene basically depends on the quality of the geometry, the illumination and the materials that are used. Whereas many sources for the creation of three-dimensional geometry exist and numerous algorithms for the approximation of global illumination were presented, the acquisition and rendering of realistic materials remains a challenging problem. Realistic materials are very important in computer graphics, because they describe the reflectance properties of surfaces, which are based on the interaction of light and matter. In the real world, an enormous diversity of materials can be found, comprising very different properties. One important objective in computer graphics is to understand these processes, to formalize them and to finally simulate them. For this purpose various analytical models do already exist, but their parameterization remains difficult as the number of parameters is usually very high. Also, they fail for very complex materials that occur in the real world. Measured materials, on the other hand, are prone to long acquisition time and to huge input data size. Although very efficient statistical compression algorithms were presented, most of them do not allow for editability, such as altering the diffuse color or mesostructure. In this thesis, a material representation is introduced that makes it possible to edit these features. This makes it possible to re-use the acquisition results in order to easily and quickly create deviations of the original material. These deviations may be subtle, but also substantial, allowing for a wide spectrum of material appearances. The approach presented in this thesis is not based on compression, but on a decomposition of the surface into several materials with different reflection properties. Based on a microfacette model, the light-matter interaction is represented by a function that can be stored in an ordinary two-dimensional texture. Additionally, depth information, local rotations, and the diffuse color are stored in these textures. As a result of the decomposition, some of the original information is inevitably lost, therefore an algorithm for the efficient simulation of subsurface scattering is presented as well. Another contribution of this work is a novel perception-based simplification metric that includes the material of an object. This metric comprises features of the human visual system, for example trichromatic color perception or reduced resolution. The proposed metric allows for a more aggressive simplification in regions where geometric metrics do not simplif