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Soil-Adjusted Vegetation Index (SAVI) is found to be undesirable to estimate Leaf Area Index (LAI) with heterogeneous canopy structure in low vegetation cover. In this article, three new vegetation indices (VIs), such as Normalized Hotspot-Signature Vegetation Index 2 (NHVI2), Hotspot-Signature Soil-Adjusted Vegetation Index (HSVI), and Hotspot-Signature 2-Band Enhanced Vegetation Index (HEVI2), are proposed for a better quantitative estimation of LAI and soil-noise resistance than with SAVI. To obtain these new indices, the angular index called Normalized Difference between Hotspot and Darkspot (NDHD) is introduced which represents the distribution of foliage in vegetation canopy. The validity of new VIs is statistically verified using simulated data and field measurements. The Discrete Anisotropic Radiative Transfer (DART) model is used to simulate both the homogeneous and heterogeneous canopy for analyzing vegetation isolines behaviors, soil-noise resistance, and LAI estimation. In situ measurements of LAI and bidirectional reflectance factor from the Boreal Ecosystem-Atmosphere Study (BOREAS) are also used to test the robustness of the new VIs for the estimation of LAI. By considering the distribution of the foliage, the accuracy of LAI estimation of SAVI for heterogeneous canopy improved almost 16% using exponential regression analysis. With the improvement of multiangular remote-sensing and Bidirectional Reflectance Distribution Function (BRDF) models in the future, hotspot-signature VIs have the potential to provide a more accurate LAI estimation for heterogeneous canopy in strong soil-noise interference area. [ABSTRACT FROM AUTHOR]

Canopy radiation and scattering signals contain abundant vegetation information. Many biophysical parameters can be quantitatively retrieved with the help of canopy radiation and scattering models. Joint simulation of three-dimensional (3-D) models for multiband that combines the advantages of different spectral (frequency) domains could be a useful tool for validation in remote sensing. This manuscript presents a 3-D joint simulation platform (3-DMultiSim) that simulates spectral responses from visible to microwave bands. We validated our platform with the corn field experimental data at the Huailai testing site of the Chinese Academy of Sciences. The correlation coefficients between the validation data and the simulation results were higher than 0.92, while the relative mean deviation was 15%. For the thermal infrared band, the correlation coefficient was 0.91, but the variation of the simulated directional bright temperature from 2 π space was less than 0.4 °C. The reason may be due to the model limitation at high leaf area index (LAI). For the microwave bands, the simulation data and the validation data had the best consistency at L band, whereas the same trend but bigger deviation at X - and C-band. As an application of the platform, we performed sensitivity analyses of the radiation and scattering responses to LAI and incident-observation geometries at multiband. The simulation results were analyzed quantitatively. Further applications of the joint simulation platform are proposed. [ABSTRACT FROM PUBLISHER]

In order to assess atmospheric effects on the directional reflectance of land surface, we have developed a new approach coupling the 3-D radiosity-based land-surface model [radiosity applicable to porous individual objects (RAPID)] with the atmospheric radiative transfer (RT) model [vector linearized discrete ordinate RT (VLIDORT)]. RAPID is used to generate a lookup table of bidirectional reflectance distribution function (BRDF) elements required by VLIDORT for the surface boundary condition. To test the RAPID–VLIDORT model, we used five natural 3-D scenes along with five aerosol optical depths (AODs). Results for top-of-atmosphere radiances show semiempirical analytical BRDF models are insufficiently accurate to represent bidirectional reflectance factors (BRFs) in hotspot regions and over wide angular variations. The large impact of AOD on BRF hotspot also underlines the importance of precise atmospheric corrections for multiangular remote sensing of the earth’s surface. [ABSTRACT FROM PUBLISHER]

The diffuse and specular components of leaf reflection are both important to determine the leaf optical properties as well as to describe the leaf bidirectional reflectance distribution function (BRDF). However, the specular component is usually ignored in practice in numerous canopy reflectance models that describe the interaction between solar light and vegetated scene components. To evaluate the impact of leaf-specular reflection on canopy bidirectional reflectance factor (BRF) characteristics, we introduce a leaf BRDF model into the radiosity-graphics combined model (RGM; a 3-D scene model) to calculate canopy BRFs with nondiffuse leaves. The modified RGM is validated by comparing simulated BRFs against in situ measured BRFs over real maize canopies. The results show that ignorance of leaf-specular reflection can result in up to 50% of relative error in the blue band (435.8 nm). A series of maize canopies with different leaf angle distributions (LADs) is reconstructed to investigate the effect of five major biophysical/geometrical parameters such as leaf area index, LAD, leaf surface property, view direction, and solar zenith angle on leaf-specular reflection contributions to the canopy BRF. It is demonstrated that increasing the incident solar zenith angle and decreasing the mean leaf angle impact the angular distribution of the canopy BRF more significantly than other factors. The cumulative hemispherical relative and absolute errors of canopy BRF caused by the leaf-specular reflection are often too large to be ignored, even for canopies with rough surface leaves. Moreover, the relative error of BRF in visible waveband shows that, in general, leaf-specular reflection has a large impact than that in near-infrared waveband. However, such impact can be sufficiently accounted for by even just consideration of the first-order leaf-specular reflection in canopy reflectance calculation, leading to a substantial improvement in simulation accuracy for most vegetation canopies. [ABSTRACT FROM PUBLISHER]

This paper is the first part of a three-part article series. Simulations of directional brightness temperature over both simple canopies with triangular leaves and the row-planted wheat and corn were used to analyze the thermal emission hot-spot effect on crop canopies. Two models, Cupid and TRGM, were successively used to simulate the thermal hot-spot signatures under conditions which cannot be easily captured in reality. The investigation includes the planting row structure, the leaf area index (LAI), the leaf angle distribution (LAD), the component temperature distribution as well as variations in the microclimate. The results show that there are typically three types of directional emission shapes in the solar principle plane: the bowl, dome and bell shape. Regardless of the shape, the hot spot is significant and can be accurately fitted (R^2=0.98 and RMSE=0.04\,^\circ\C) with a function of the phase angle (\xi), the hot-spot amplitude (\Delta THS) and the half width of the hot spot (\xi0), which can be quantified with the half width in the RED band. The planting row structure can reduce the \Delta THS by a maximum amount (about 1.2 ^\circC) when compared with an unstructured horizontal canopy. The \Delta THS is linearly related to the component temperature differences between sunlit and shadowed parts. The linear equation can be used to predict the component temperature differences from \Delta THS. The accuracy is very good for the horizontal canopies with triangular leaves (RMSE<0.4\,^\circ\C and R^2>0.99), and acceptable for the virtual wheat and corn canopies (RMSE<1.8\,^\circ\C and R^2>0.81). [ABSTRACT FROM PUBLISHER]