Development of the Adjoint Model of a Canopy Radiative Transfer Model for Sensitivity Study and Inversion of Leaf Area Index

Many canopy reflectance models have been developed in the last decades and used for estimating land surface biogeophysical variables, such as leaf area index (LAI), from satellite observations through optimization procedures. In most studies, the derivative information of the canopy reflectance model has not been used effectively, which limits this approach for regional and global applications. The final solutions are often converged to the local minima. To address these issues, the adjoint model of a canopy radiative transfer model is developed in this study through the automatic differentiation technique. The developed adjoint model is used for sensitivity study, and a combination of the adjoint model with the trust region global optimization method is performed to retrieve LAI from the Enhanced Thematic Mapper Plus (ETM+). This study demonstrates that this method can be reliably used for inverting LAI efficiently and is suitable for global applications.     

Evaluation of a Canopy Reflectance Model for LAI Estimation through Its Inversion

A technique described earlier for estimating leaf area index (LAI) from bidirectional canopy reflectance (CR) data is applied and evaluated for three plant canopies-a naturally growing healthy soybean canopy and two orchardgrass canopies-one homogenous and the other spatially clumped or "tufted." This technique employs the inversion of a CR model which is chosen to be the SAIL model. The CR data were collected using a new ilstrument called the PARABOLA which is capable of acquiring the complete sky-and-ground looking hemisphere radiances in only 11 s. The model fit and LAI estimations for the soybean and uniform orchardgrass canopies are quite good. For the inhomogenous tufted orchardgrass canopy the LAI estimation is poor unless the maximum view zenith angle is restricted to 500. These results indicate that the biophysical parameter estimation from CR measurements may be applied with considerable confidence to homogenous herbaceous vegetation types but better CR models are needed to adequately represent discontinuous plant canopies.     

森林冠层氮含量遥感估算

使用高光谱数据估算叶片与冠层尺度的森林氮含量.首先采用基于高斯误差函数的BP神经网络Erf-BP建立叶片尺度氮含量的遥感估算模型;其次根据几何光学模型原理,推导冠层光谱与叶片光谱的尺度转化函数,将Hy-perion影像的冠层光谱转换到叶片尺度并反演叶片尺度的氮含量;最后,利用森林结构参数LAI得到研究区域冠层尺度氮含量.结果表明,隐含层包含8个神经元的Erf-BP模型最优,检验精度为76.8597%;利用尺度转化函数估算670 nm和865 nm冠层光谱与实测光谱决定系数为0.5203和0.4117;反演叶片尺度氮含量与实测数据的决定系数为0.7019;该方法为高精度快速估算叶片和冠层尺度森林氮含量提供参考.     

Remote Sensing of Angular Characteristics of Canopy Reflectances

The influence of the atmosphere on the remotely sensed angular distribution of canopy reflectance is studied by radiative transfer calculations with both a coupled atmosphere-canopy model and a pure atmosphere model with the canopy replaced by an equivalent bidirectional reflectance distribution function (BRDF). The canopy model, although one-dimensional, is able to reproduce typical canopy features like the "bowl shape" and the canopy "hot spot." In the decoupled mode, it can be used to compute canopy-equivalent BRDF's. The atmospheric perturbation of the angular reflectance pattern of a Lambertian, a mixed Lambertian/specular BRDF, and of the measured BRDF's of savannah and coniferous forest canopies is studied using one aerosol-free and two polluted atmospheres with surface visual ranges of V0 = 23 km and V0 = 5 km. It is shown that for surface albedoes > 10%, local extremes in the angular distribution of the surface reflectance and dependencies on the view azimuth angle are still detectable above the atmosphere and are nearly invariant to atmospheric perturbations. This result leads to the recommendation that off-nadir satellite observations in the near-infrared may contribute additional valuable information to crop identification. However, canopy reflectance variations with varying view zenith angles are dominated by atmospheric perturbations even for relatively clear atmospheres.     

Theoretical limits to the estimation of the leaf area index on thebasis of visible and near-infrared remote sensing data

The Leaf Area Index (LAI) of a plant canopy is an important environmental parameter required by various applications. It would be highly desirable to be able to estimate this parameter on the basis of satellite remote sensing data in the optical spectral range. However, LAI affects the propagation of light in a plant canopy (and therefore its measurable reflectance factor) exclusively through a boundary condition of the equation of radiation transfer. It is shown that LAI may be retrievable accurately and reliably only when the canopy is optically thin enough to allow a significant illumination of the underlying soil, and when the optical properties of this soil are such that the radiance field emerging from this level is sufficiently different from that which would be exhibited by a deeper canopy. The combinations of radiative conditions (soil and plant properties) necessary for the reliable and accurate retrieval of the LAI on the basis of remote sensing reflectance data acquired above the canopy in the red and near-infrared spectral regions are investigated and documented with the help of simulation studies. These results show the retrievability of LAI from remote sensing data in optimal situations, however     

Plant Canopy Specular Reflectance Model

A model is derived for the amount of light specularly reflected and polarized by a plant canopy. The model is based on the morphological and phenological characteristics of the canopy and upon the Fresnel equations of optics. The theory demonstrates that the specular reflectance of the plant canopy is a function of the angle of incidence and potentially contains information to help discriminate between species. The theory relates the specular reflectance to botanical condition of the canopy-to factors such as development stage, plant vigor, and leaf area index (LAI).     

Principles of the radiosity method versus radiative transfer forcanopy reflectance modeling

The radiosity method is introduced to plant canopy reflectance modeling. The authors review the physics principles of the radiosity method which originates in thermal radiative transfer analysis when hot and cold surfaces are considered within a given enclosure. The radiosity equation, which is an energy balance equation for discrete surfaces, is described and contrasted with the radiative transfer equation, which is a volumetric energy balance equation. Comparing the strengths and weaknesses of the radiosity formulation with those of the radiative transfer formulation for canopy reflectance modeling, it is concluded that both methods are complementary to each other. Results of a sample calculation are given for a simplified canopy model with 4000 leaves     

敦煌辐射校正场地表反射率稳定性分析

辐照度基法确定卫星各波段的定标系数时,要求精确测量辐射定标场的地表反射率和漫射辐射度与总辐射度的比值。中国科学院通用光学定标与表征技术重点实验室分别于2013年6~8月及2014年8月期间,协同其他单位在敦煌校正场运用辐照度基法进行场地辐射定标,实测过程中使用ASD、SVC光谱辐射计,运用野外参考板反射率因子法确定敦煌校正场的地表反射率。详细阐述地表反射率测量方式及数据处理方法,根据实地观测数据,分析当前场区的地表反射率并与历史数据相互比对。结果显示,敦煌校正场地表反射率在时间和空间上均保持良好的稳定性。     

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.     

Forest canopy closure from classification and spectral unmixing ofscene components-multisensor evaluation of an open canopy

Three types of remote sensing data, color infrared aerial photography (CIR), compact airborne spectrographic imager (CASI) imagery, and airborne visible/infrared imaging spectrometer (AVIRIS) imagery, have been used to estimate forest canopy closure for an open-canopy forest environment. The high-spatial-resolution CIR and CASI images were classified to generate forest canopy closure estimates. These estimates were used to validate the forest canopy closure estimation accuracy obtained using the AVIRIS image. Reflectance spectra extracted from the spectral-mode CASI image were used to normalize the raw AVIRIS image to a reflectance image. Classification and spectral unmixing methods have been applied to the AVIRIS image. Results indicate that both the classification and the spectral unmixing methods can produce reasonably accurate estimates of forest canopy closure (within 3 percent agreement) when related statistics are extracted from the AVIRIS image and relatively pure reflectance spectra are extracted from the CASI image. However, it is more challenging to use the spectral unmixing technique to derive subpixel-scale components whose reflectance spectra cannot be directly extracted from the AVIRIS image     

A subspace model-based approach to face relighting under unknown lighting and poses

We present a new approach to face relighting by jointly estimating the pose, reflectance functions, and lighting from as few as one image of a face. Upon such estimation, we can synthesize the face image under any prescribed new lighting condition. In contrast to commonly used face shape models or shape-dependent models, we neither recover nor assume the 3-D face shape during the estimation process. Instead, we train a pose- and pixel-dependent subspace model of the reflectance function using a face database that contains samples of pose and illumination for a large number of individuals (e.g., the CMU PIE database and the Yale database). Using this subspace model, we can estimate the pose, the reflectance functions, and the lighting condition of any given face image. Our approach lends itself to practical applications thanks to many desirable properties, including the preservation of the non-Lambertian skin reflectance properties and facial hair, as well as reproduction of various shadows on the face. Extensive experiments show that, compared to recent representative face relighting techniques, our method successfully produces better results, in terms of subjective and objective quality, without reconstructing a 3-D shape.     

Determining land-surface parameters from the ERS wind scatterometer

The ERS-1 wind scatterometer (WSC) has a resolution cell of about 50 km but provides a high repetition rate (less than four days) and makes measurements at multiple incidence angles. In order to retrieve quantitative geophysical parameters over land surfaces using this instrument, a method is presented that applies a mixed-target modeling approach to estimate subpixel fractional vegetation cover at a regional scale. The model represents the footprint area as a combination of part dense, homogeneous vegetation and part bare soil (with homogeneous roughness and dielectric properties). Inversion of this model is then carried out using a retrieval procedure that incorporates a priori information in a quantitative manner The method is applied to the estimation of fractional cover over an area in Africa using WSC data from 1992 to 1995. Retrieved parameters are also compared to ground measurements made in the area during the 1992 HAPEX-Sahel campaign. The procedure illustrates the applicability of WSC data for measuring geophysical parameters over land and offers the potential of deriving a physically-based alternative to empirical indices for estimating regionally-variable parameters     

Estimation of subpixel vegetation cover using red-infraredscattergrams

The bulk properties of discontinuous vegetation canopies are estimated at subpixel scales by applying the method of moments to a linear stochastic geometric model of canopy-soil reflectance and one set of multispectral observations without ground truth. The procedure involves the formulation of conditional moments for subsets of pixels that possess similar properties and can be identified through their common orientation in red-infrared scattergrams. The analysis is facilitated by assuming geometric similarity among the canopy elements and by formulating a sampling scale ratio in terms of the bulk geometric scales of the canopy and the pixel. Three versions of the method are demonstrated using two simulated scenes and an actual forested watershed for which aerial radiometric data and corresponding ground truth were obtained     

Modeling of atmospheric effects on the angular distribution of abackscattering peak

Atmospheric radiative transfer calculations with extremely high angular resolution of the radiance distribution are used to analyze the effects of atmospheric multiple scattering and absorption on the angular distribution of a narrow retroreflection peak such as the canopy hot spot, or Heiligenschein. Using a realistic aerosol-loaded atmospheric model, the results demonstrate that the angular width of the model hot spot (for half widths between 1° and 4° and various types of vegetative canopies) is, to within about 10%, invariant to atmospheric perturbations for total optical depths of the atmosphere up to 1.0 at 0.55 μm and up to 0.9 at 0.86 μm. This result is a consequence of the angular filter effect of the surface bidirectional reflectance distribution function and the comparatively broad angular signature of atmospheric backscattering. However, the contrast ratio of the backscattering peak is strongly influenced by atmospheric extinction. As a consequence for satellite remote sensing, the results indicate that the canopy hot spot can be classified as an angular reflectance signature with an angular width that remains invariant to atmospheric scattering and absorption     

Target adjacency effect estimation using ground spectrum measurement and Landsat-5 Satellite data

This paper addresses the estimation of adjacency effect in ground spectrum and Landsat-5 pixels. The adjacency effect influences the digital number value of a pixel by adding surface surrounding scatter signals and path scatter signals at the sensor. Along with the increasing use of satellite high-resolution imagery and quantitative remote sensing, much attention has been paid to the experimental measurement and estimation of the natural phenomena of adjacency effects. Based on the theory of radiation transfer, a procedure was designed to measure the reflectance from the surface target materials and the materials in a box which is 1.5 m above the surface to avoid upwelling reflectance. At every 3/spl times/3 sites, the measurement was carried out during 10:30 to 13:30 of local time at the Guanting Remote Sensing Test Site in north Beijing. The results show that the adjacency effect becomes stronger from visible, near infrared to shortwave infrared wavelength; the adjacency effect weakens with the increase of distance between testing site. At last, the adjacency effect of Landsat-5 image was corrected, and the quality of the resulting image was improved.     

Light Interception and Leaf Area Estimates from Measurements of Grass Canopy Reflectance

Grassland is a major component of the Earth's available land. The vast area and remoteness of this ecosystem makes it difficult to assess its condition and monitor productivity by traditional niethods. Remote sensing potentially offers a rapid nondestructive approach for monitoring such ecosystems. A study was carried out in a tallgrass prairie site near Manhattan, Kansas, during the 1983 and 1984 seasons to investigate the feasibility of estimating light interception and green leaf area index (LAI) from measurements of canopy multispectral reflectance. Greenness (G, i) index was found to be strongly correlated with intercepted photosynthetically active radiation ( PAR). Two methods, a direct regression (RGR) and an indirect approach (IND), were used to estimate LAI from Goi index. The LAI values estimated by RGR method were consistently lower than the measured ones; however, good agreement was obtained between the LAI values estimated by IND method and the measured LAI. This suggests that Goi transformation of canopy spectral reflectance is more closely related to the fraction of intercepted PAR by green foliage than the quantity of green LAI.     

Modeling lidar waveforms in heterogeneous and discrete canopies

This study explores the relationship between laser waveforms and canopy structure parameters and the effects of the spatial arrangement of canopy structure on this relationship through a geometric optical model. Studying laser waveforms for such plant canopies is needed for the advanced retrieval of three-dimensional (3D) canopy structure parameters from the vegetation canopy lidar (VCL) mission. For discontinuous plant canopies, a hybrid geometric optical and radiative transfer (GORT) model describing the effects of 3D canopy structure parameters of discrete canopies on the radiation environment has been modified for use with lidar. The GORT model is first used to describe the canopy lidar waveforms as a function of canopy structure parameters and then validated using scanning lidar imager of canopies by echo recovery (SLICER) data collected in conifer forests in central Canada during the boreal ecosystem-atmosphere study (BOREAS). Model simulations show that the clumping in natural vegetation, such as leaves clustering into tree crowns causes larger gap probability and smaller waveforms for discontinuous plant canopies than for horizontally homogeneous plant canopies. Ignoring the clumping effect can result in significantly lower values for the estimated foliage amount in the profile and in turn lower estimated biomass. Because of clumping, only the gap probability and apparent vertical projected foliage profile can be directly retrieved from the canopy lidar data. The retrieval is sensitive to the ratio of the volume backscattering coefficients of the vegetation and background, and this ratio depends on canopy architecture as well as foliage spectral characteristics     

Shinnery oak bidirectional reflectance properties and canopy modelinversion

The authors present field measurements and the results of a three-dimensional canopy model inversion for sand shinnery oak. Spectral bidirectional radiance measurements in three spectral channels, 0.65-0.67 μm, 0.81-0.84 μm, and 1.62-1.69 μm, encompassing both the complete land surface and sky hemispheres, were acquired for a sand shinnery oak plant community in west Texas. The changes in canopy reflectance that occur with variations in solar zenith angle and view direction and for two seasons of the year were evaluated. A three-dimensional radiation interaction model (TRIM) was then inverted to estimate oak leaf area index (LAI) and canopy density, expressed as percentage of cover, from the bidirectional reflectance data