D. S. Kimes

Dynamics of directional reflectance factor distributions for vegetation canopies

Directional reflectance factors that span the entire exitance hemisphere were measured for vegetation canopies and bare soils with different geometric structures. Two spectral bands were used—NOAA 6/7 AVHRR bands 1 (0.58–0.68 μm) and 2 (0.73–1.1 μm). Geometric measurements of leaf orientation distributions were taken when possible, and other structural and agronomic measurements were collected. For each cover type, these data were taken several different times on a clear day. Polar coordinate system plots of directional reflectance factors, along with 3-D computer graphic plots of scattered flux, were created. These field data were used in conjunction with literature data to study the dynamics of the directional reflectance factor distribution as a function of the geometric structure of the scene, solar zenith angle, and optical properties of the leaves and soil. Physical mechanisms causing the observed dynamics were proposed and were supported by a number of field and modeling studies. For complete homogeneous vegetation canopies, the major trend observed at all sun angles and spectral bands was a minimum reflectance near nadir and increasing reflectance with increasing off-nadir view angle for all azimuth directions. This trend is well known in the experimental and theoretical literature and is caused by the shading of lower canopy layers by components in the upper layers and by viewing different proportions of the layer components as the sensor view angle changes. In some cases the reflectance minimum was shifted slightly off-nadir in the foward scattering direction. The reflectance distributions tended to be azimuthally symmetric because the leaf transmittance was nearly equal to the leaf reflectance for most wavelengths. For sparse homogeneous canopies the anisotropic scattering properties of the soil significantly influenced the observed directional reflectance in the visible band. Soils have strong backscattering characteristics which can dominate the observed reflectance distribution for sparse canopies and small solar zenith angles. This knowledge is important in interpreting aircraft and satellite data, where the scan angle varies widely and can have different orientations with respect to the sun. Finally, the measured data and knowledge of the mechanics of the observed dynamics of the data can provide rigorous validation and verification tests for theoretical radiative transfer models.

Optical remote sensing of vegetation: Modeling, caveats, and algorithms

Abstract The state-of-the-art on radiative transfer modeling in vegetation canopies arul the application of such models to the interpretation and analysis of remotely sensed optical data is summarized. Modeling of top-of-the-atmosphere and top-of-the-canopy radiance field is developed as boundary value problems in radiative transfer. The parameterization of the constituent functions with simple models and/or empirical data is outlined together with numerical solution methods and examples of results of model validation. Caveats in the assignment of signal characteristics to surface properties are itemized and discussed with example results. Algorithms to estimate surface properties from remote observations are classified as spectral vegetation indices, model inversion, expert systems, neural networks, and genetic algorithms. Their applicability is also discussed.

Directional Reflectance Distributions of a Hardwood and Pine Forest Canopy

The directional reflectance distributions for both a hardwood and pine forest canopy at Beltsville, Maryland, were measured in June as a function of sun angle from a helicopter platform using a hand-held radiometer with AVHRR band 1 (0.58-0.68 ¿m) and band 2 (0.73-1.1 ¿m). Canopy characteristics were measured on the ground. The reflectance distributions are reported and compared to the scattering behavior of agricultural and natural grassland canopies. In addition, the three-dimensional radiative transfer model of Kimes was used to document the unique radiant transfers that take place in forest canopies due to their special geometric structure. Measurements and model simulations showed that the scattering behavior of relatively dense forest canopies is similar to the scattering behavior of agricultural crops and natural grasslands. Only in more sparse forest canopies with significant spacing between the tree crowns (or clumps of tree crowns) does the scattering behavior deviate from homogeneous agricultural and natural grassland canopies. This clumping of vegetation material has two effects on the radiant transfers within the canopy: A) it increases the probability of gap to the understory and/or soil layers that increases the influence of the scattering properties of these lower layers; and B) it increases the number of low transmitting clumps of vegetation within the scene causing increased backscatter and decreased forward scatter to occur relative to the homogeneous case. Both effects, referred to as phenomenon A and B, respectively, tend to increase backscatter relative to forward scatter.

Inferring hemispherical reflectance of the earth's surface for global energy budgets from remotely sensed nadir or directional radiance values

Abstract The importance of the hemispherical reflectance (albedo) of terrestrial surfaces to biospheric and atmospheric processes is briefly reviewed. It is proposed that satellite-borne instruments represent the only practical means of obtaining global estimates of surface albedo data at reasonable time resolution, the problem being how to relate the nadir or directional reflectance observations obtained from such sensors to the integrated hemispherical reflectance. This paper discusses results measured at ground level in which NOAA satellite 7/8 AVHRR data, Bands 1 (0.58–0.68 μm) and 2 (0.73–1.1 μm), were used to investigate 1) the relationships between directional reflectances (spanning the entire reflecting hemisphere) and hemispherical reflectance (albedo) and 2) the effect of solar zenith angle and cover type on these relationships. Eleven natural vegetation surfaces ranging from bare soils to dense vegetation canopies were considered in the study. The results show that errors in inferring hemispherical reflectance from nadir reflectance can be as high as 45% for all cover types and solar zenith angles. By choosing a time of observation such that the solar zenith angle is between 30 and 40° the same error is reduced to less than 20% in both bands. For both bands a view angle of 60° off-nadir and ±90° from the solar azimuth reduces this error to less than 11% for all sun angles and cover types. A technique using two specific view angles reduces this error to less than 6% for both bands and for all sun angles and cover types. These techniques may yield considerable dividends in terms of more reliable estimation of hemispherical reflectance of natural surfaces.

Radiative transfer model for heterogeneous 3-D scenes

A general mathematical framework for simulating processes in heterogeneous 3-D scenes is presented. Specifically, a model was designed and coded for application to radiative transfers in vegetative scenes. The model is unique in that it predicts (1) the directional spectral reflectance factors as a function of the sensors azimuth and zenith angles and the sensors position above the canopy, (2) the spectral absorption as a function of location within the scene, and (3) the directional spectral radiance as a function of the sensors location within the scene. The model was shown to follow known physical principles of radiative transfer. Initial verification of the model as applied to a soybean row crop showed that the simulated directional reflectance data corresponded relatively well in gross trends to the measured data. However, the model can be greatly improved by incorporating more sophisticated and realistic anisotropic scattering algorithms.

Attributes of neural networks for extracting continuous vegetation variables from optical and radar measurements

Efficient algorithms that incorporate different types of spectral data and ancillary data are being developed to extract continuous vegetation variables. Inferring continuous variables implies that functional relationships must be found among the predicted variable(s), the remotely sensed data and the ancillary data. Neural networks have attributes which facilitate the extraction of vegetation variables. The advantages and power of neural networks for extracting continuous vegetation variables using optical and/or radar data and ancillary data are discussed and compared to traditional techniques. Studies that have made advances in this research area are reviewed and discussed. Neural networks can provide accurate initial models for extracting vegetation variables when an adequate amount of data is available. Networks provide a performance standard for evaluating existing physically based models. Many practical problems occur when inverting physically based models using traditional techniques and neural ne...

Directional reflectance factor distributions for cover types of Northern Africa

Directional reflectance factors that spanned the entire exitance hemisphere were collected on the ground throughout the morning period for common cover types in Tunisia, Africa. NOAA 7/8 AVHRR bands 1 (0.58–0.68 μm) and 2 (0.73–1.1 μm) were used in data collection. The cover types reported were a plowed field, annual grassland, steppe grassland, hard wheat, salt plain, and irrigated wheat. Several of these cover types had geometric structures that are extreme as compared to those reported in the literature. Comparisons were made between the dynamics of the observed reflectance distributions and those reported in the literature. It was found that the dynamics of the measured data could be explained by a combination of soil and vegetation scattering components. The data and analysis further validated physical principles that cause the reflectance distribution dynamics as proposed by field and simulation studies in the literature. Finally, the normalized difference transformation [(Band 2 − Band 1)/(Band 1 + Band 2)], which is useful in monitoring vegetation cover, generally decreased the variation in signal with changing view angle. However, several exceptions were noted.

Remote sensing of row crop structure and component temperatures using directional radiometric temperatures and inversion techniques

Abstract A physically based sensor response model of a row crop was used as the mathematical framework from which several inversion strategies were tested for extracting row structure information and component temperatures using a series of sensor view angles. The technique was evaluated on ground-based radiometric thermal infrared data of a cotton row crop that covered 48% of the ground in the vertical projection. The results showed that the accuracies of the predicted row heights and widths, vegetation temperatures, and soil temperatures of the cotton row crop were on the order of 5 cm (± 10% of mean values), 1°, and 2°C, respectively. The inversion techniques can be applied to directional sensor data from aircraft platforms and even space platforms if the effects of atmospheric absorption and emission can be corrected. In theory, such inversion techniques can be applied to a wide variety of vegetation types and thus can have significant implications for remote sensing research and applications in disciplines that deal with incomplete vegetation canopies.

Directional radiometric measurements of row-crop temperatures

Abstract Incomplete vegetation canopies are complex remote-sensing targets. The directional variability of sensor response when viewing a cotton row crop with 48 per cent ground cover was documented for the thermal infrared region. The geometric structure of the canopy was described and radiometric temperatures of four components, sunlit and shaded vegetation and soil, were measured. These data were used to validate and verify a geometric, row projection model. The model predicts the thermal infrared response of a sensor as a function of sensor view angle, component temperature and geometry structure of the canopy. The field data showed sensor response differentials as great as 16.2°C when going from a zenith view angle of 0° to one of 80° in a plane normal to the row direction. The root-mean-square deviation between the model prediction and measured sensor response for all measurement periods and view angles (n = 90) was 0.96°C. The model serves as a sound mathematical basis for interpreting remotely-sen...

Irradiance measurement errors due to the assumption of a Lambertian reference panel

Abstract Total and diffuse global spectral irradiances, which are often required field measurements in remote sensing, are commonly obtained by measuring the radiance from a horizontal reference panel with assumed Lambertian properties. A technique is presented for determining the error in diurnal irradiance measurements that results from the non-Lambertian behavior of a reference panel under various irradiance conditions. Spectral biconical reflectance factors of a spray-painted barium sulfate panel, along with simulated sky radiance data for clear and hazy skies at six solar zenith angles, were used to calculate the estimated panel irradiances and true-irradiances for a nadir-looking sensor in two wavelength bands. The inherent errors in total spectral irradiance (0.68 μm) for a clear sky were 0.60, 6.0, 13.0, and 27.0% for solar zenith angles of 0°, 45°, 60°, and 75°. The technique can be used to characterize the error of a specific panel used in field measurements and thus eliminate any ambiguity of the effects of the type, preparation, and aging of the paint.