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The Multi-angle imaging spectroradiometer (MISR) land-surface (LS) bidirectional reflectance factor (BRF) product (MILS_BRF) has unique semi-simultaneous multi-angle sampling and global coverage. However, unlike on-satellite observations, the spatio-temporal characteristics of MILS_BRF data have rarely been explicitly and comprehensively analysed. Results from 5-yr (2011–2015) of MILS_BRF dataset from a typical region in central Northeast Asia as the study area showed that the monthly area coverage as well as MILS_BRF data quantity varies significantly, from the highest in October (99.05%) through median in June/July (78.09%/75.21%) to lowest in January (18.97%), and a large data-vacant area exists in the study area during four consecutive winter months (December through March). The data-vacant area is mainly composed of crop lands and cropland/natural vegetation mosaic. The amount of data within the principal plane (PP) ±30° (nPP) or cross PP ±30° (nCP), varies intra-annually with significant differences from different view zeniths or forward/backward scattering directions. For example, multiple off-nadir cameras have nPP but no nCP data for up to six months (September through February), with the opposite occurring in June and July. This study provides explicit and comprehensive information about the spatio-temporal characteristics of product coverage and observation geometry of MILS_BRF in the study area. Results provide required user reference information for MILS_BRF to evaluate performance of BRDF models or to compare with other satellite-derived BRF or albedo products. Comparing this final product to on-satellite observations, what was found here reveals a new perspective on product spatial coverage and observation geometry for multi-angle remote sensing.

Canopy radiation and scattering signal contains abundant vegetation information. One can quantitatively retrieve the biophysical parameters by building canopy radiation and scattering models and inverting them. Joint simulation of the three-dimensional (3D) models for multiband may combine the advantages of different spectral (frequency) domains. It is also a useful tool for validation in remote sesnsing because of the high precision of the 3D model. This manuscript presented a 3D joint simulation platform which was able to simulate the remote sensing responses of the 3D scene from visible to microwave bands. As a case study, we used the platform to simulate a virtual scene with populus, and did a sensitivity analysis on the radiation and scattering responses of different wavelengths to leaf area index (LAI). The application of the joint simulation platform was prospected.

Hotspot is a prominent feature of the reflectance distribution of a vegetation canopy consisting of finite size foliage. It depends on the geometric dimension and spatial organization of vegetation elements, and therefore has a potential for diagnosing canopy geometric structure. In the context of this study, we first reconcile different notations used by previous workers. This leads to geometrically quantifying the cross-correlation function, which is essential for the hotspot modeling. A comprehensive formulation for the hotspot effect at both leaf and canopy levels is then developed, by generally parameterizing some basic parameters such as mean area of shadows and overlap between shadows cast by scatterers. A rectangle model is proposed to account for the influence of noncircular shape of scatterers on the hotspot effect, and explicit expressions for both the cross-correlation function and the hotspot width are obtained. It is shown that for a leaflike object, the angular hotspot width progressively broadens with an increase of m, the ratio of mean leaf width to the length. For the whole canopy, the relative distribution of the hotspot intensity mainly depends on this ratio. That is, the cross-correlation function decreases more rapidly for smaller m as the viewing direction diverges from the illumination direction. As a result, canopy reflectance increases with m, particularly in the region around the hotspot point where the reflectance distribution strongly relies on the ratio m. For m = π / 4 , the rectangle model produces nearly same result as the disk model. This indicates this rectangle model is more realistic and flexible than those based on circle-shaped scatterers (leaves) or their shadows, which is the common assumption underlying in most existing hotspot models.

By combining geometrical optics and transport theory, a bidirectional reflectance model for multicomponent vegetation canopies is explicitly developed in this article. A precise expression of the overlap function is derived for vertically cylindric phytoelements randomly distributed in the canopy, and a mathematical model for describing the vertical distribution of leaf area density is presented and fitted with measured data. In addition, the size, shape, orientation, and nonrandom distribution of leaves and vertical inhomogeneity of the canopy are properly taken into account in this model. The model also reproduces the measured distributions of reflectance from a wheat canopy quite well. The significant effect of stems on the canopy reflectance is identified by comparison with the result of the corresponding leaf canopy model. The results of sensitivity analysis prove that, even for crop canopies like wheat in this study, the influence of stems cannot be neglected if the ratio of stem silhouette area to the total foliage area is greater than 10%. Since this multicomponent model is a hybrid one, it could serve as a primary model to develop more accurate reflectance models for inhomogeneous vegetation canopies, such as forest, in further studies.

An explicit analytical model for calculating vegetation canopy reflectance is developed in this paper, based on radiative transfer theory through separating the roles of incident direct and diffuse radiation, singly and multiply scattered radiation by foliage and soil. Using principles of scattering from a point source, the contributions of diffuse sky radiation to both first-order and multiple scattering reflectance are accurately specified. In addition, this analytical model incorporates the effects of nonrandom spatial dispersion of foliage, noncircular shape and nonhorizontal orientation of leaves on the canopy hotspot and then on reflectance distributions. Although the reflectance by multiple scattering is simply estimated with the two-stream approximation (Nilson, 1991), the angular distributions of canopy reflectance produced by the model agree well with those measured above soybean and wheat canopies. Some original results from model sensitivity analysis are sketched as follows: (1) leaf shape and orientation have a considerable influence on the canopy hotspot except for planophile canopies or in near nadir viewing directions. The contributions of soil reflectance and multiple scattering increase with the modal inclination angle of leaves; (2) the foliage spatial dispersion pattern changes the magnitude and angular distribution of the canopy reflectance strongly in the RED band; (3) when the ratio of diffuse sky radiation to the total incident radiation is less than 20%, its contribution to canopy reflectance is less than 6% and 8% on average for RED and NIR bands, respectively. This provides a means to approximately calculate the two components signifying the role of diffuse sky radiation and then to conditionally simplify this reflectance model, and therefore improve its practical applicability; (4) the sensitive regions of different structural parameters are usually different and generally change with waveband and leaf orientation. This implies that only by using the reflectance data in its sensitive region, can a specified parameter be accurately estimated by model inversion. Finally, further improvements needed for analytical approaches are briefly discussed.