Wenhan Qin

Radiation transfer model intercomparison (RAMI) exercise

The community involved in modeling radiation transfer over terrestrial surfaces designed and implemented the first phase of a radiation transfer model intercomparison (RAMI) exercise. This paper discusses the rationale and motivation for this endeavor, presents the intercomparison protocol as well as the evaluation procedures, and describes the principal results. Participants were asked to simulate the transfer of radiation for a variety of precisely defined terrestrial environments and illumination conditions. These were abstractions of typical terrestrial systems and included both homogeneous and heterogeneous scenes. The differences between the results generated by eight different models, including both one-dimensional and three-dimensional approaches, were then documented and analyzed. RAMI proposed a protocol to quantitatively assess the consequences of the model discrepancies with respect to application, such as those motivating the development of physically based inversion procedures. This first phase of model intercomparison has already proved useful in assessing the ability of the modeling community to generate similar radiation fields despite the large panoply of models that were tested. A detailed analysis of the results also permitted to identify apparent “outliers” and their main deficiencies. Future undertakings in this intercomparison framework must be oriented toward an expansion of RAMI into other and more complex geophysical systems as well as the focusing on actual inverse problems.

3-D Scene Modeling of Semidesert Vegetation Cover and its Radiation Regime

To explore the potential of multiangle remote sensing for estimating biophysical or ecological parameters over a variety of landscapes, a modeling tool that is capable of handling three-dimensional (3-D) heterogeneous structures, deriving ecological parameters from the vegetation structure, and effectively working on different scene scales is very desirable. A 3-D scene modeling approach for these purposes is presented in this paper. This 3-D model fulfills its goal by taking advantage of radiosity theory and computer graphics techniques. It consists of two major modules: a modified extended L-systems (MELS) method to generate a 3-D realistic scene and a radiosity-graphics combined method (RGM) to calculate the radiation regime based on the 3-D structures rendered with MELS. The 3-D simulation tool is then evaluated using field measurements of both plant structure and spectra collected during the NASA Earth Observing Satellite Prototype Validation Exercise Jornada field campaign near Las Cruces, NM. The modeled scene reflectance is compared with measurements from three platforms (ground, tower, and satellite) at various scales (from the size of individual shrub component to satellite pixels of kilometers). The agreement with measured reflectances is excellent at all sampling scales tested. As an example of the models application, we use the model output to examine the validity of a linear mixture scheme over the Jornada semidesert scene. The result shows that the larger the sampling size (at least larger than the size of the shrub component), the better the hypothesis is satisfied because of the unique structure of the Jornada scene: dense plant clumps (shrub component) sparsely scattered on a predominantly bare soil background. A range of possible applications of this 3-D scene model is highlighted, and further work needed for 3-D modeling is also discussed.

The potential of hyperspectral bidirectional reflectance distribution function data for grass canopy characterization

Hyperspectral bidirectional reflectance distribution function (BRDF) data of Konza prairie grassland acquired in the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) on the ground with two SE-590 instruments and remotely with the airborne advanced solid-state array spectroradiometer (ASAS) are analyzed and compared to BRDF data of dense ryegrass obtained in the laboratory and field with the European goniometric facility (EGO) and the Swiss field-goniometer system (FIGOS). The soil underlying the relatively sparse Konza prairie grass disturbed the spectral BRDF effects of the vegetation components. After a correction of the soil influence based on the bidirectional canopy gap probability, the Konza data from SE-590 and ASAS sensors showed a consistently strong dependence of spectral BRDF effects from nadir reflectance as was observed in the EGO and FIGOS data. BRDF effects were inversely related to reflectance intensities, low reflectances being associated with pronounced BRDF effects and high reflectances with low BRDF effects. This relationship is due to multiple scattering effects and is influenced by the canopy optical properties and architecture parameters such as leaf area index (LAI), leaf angle distribution (LAD), and the gap fraction. The BRDF data of the Konza prairie grass from both ground and aircraft measurements showed a strong relationship between LAI and spectral BRDF variability. Reflectance data with high spectral resolution in the red edge range from 675 to about 900 nm wavelength, acquired from the two viewing directions with maximum and minimum reflectance intensities proved to be useful for deriving vegetation canopy architecture characteristics from hyperspectral BRDF data. BRDF data with high spectral resolution from the airborne ASAS sensor and from planned commercial remote sensing satellites are therefore an ideal testbed for a further exploration of this promising approach.

An Extended 3-D Radiosity–Graphics Combined Model for Studying Thermal-Emission Directionality of Crop Canopy

Radiosity-graphics combined model (RGM) has been proposed to calculate the radiation regime and bidirectional reflectance distribution function of complex 3D scene, which is limited in visible and near-infrared wavelength (0.3-3 mum) region. In this paper, RGM is extended to thermal region (named as TRGM) based on thermal-radiosity theory and thermal-emission directionality of vegetation canopy. The TRGM has been implemented on Microsoft Windows platform, and a parameterization scheme for crop canopies is introduced in this paper. It is then evaluated by comparing with two row-crop directional thermal emission models and one thermal radiative-transfer model. Field experiment data has been used to validate the TRGM for row structural wheat and maize canopies. The root mean square error of directional brightness temperature (DBT) is smaller than 1.0degC for the wheat canopy and 0.5degC for the maize canopy while the canopy DBTs vary more than 4degC. Model sensitivity analyses have also been conducted to illustrate influences of component temperature distribution, component emissivity, incident atmospheric radiation, and canopy structure on the crop canopy DBT.

On the estimation of leaf size and crown geometry for tree canopies from hotspot observations

A computer-graphics based model for radiation interception in vegetation canopies is used to investigate the feasibility of estimating leaf size and crown size, for deciduous and coniferous trees, from canopy reflectance in the hotspot region. For deciduous trees, as represented by aspen trees, it appears that under certain conditions one can estimate leaf size; we specify optimal Sun-view geometry, wavelength, and index, which can minimize the impacts of other structural parameters (e.g., leaf area index, leaf angle distribution, and interplant spacing) for the most accurate estimation of leaf size. However, for coniferous trees an accurate estimation of crown size seems unlikely, except possibly for sparsely spaced canopies.

A realistic structure model for large-scale surface leaving radiance simulation of forest canopy and accuracy assessment

The radiosity-graphics model (RGM) is an important branch of computer simulation modelling for the vegetation bidirectional reflectance distribution function (BRDF). As the radiosity method is based on a global solving technique, the RGM can only deal with limited numbers of polygons, and has only been used for small-scale flat terrain scenes. However, the land surface is generally rugged, so it is necessary to extend the RGM to simulate the surface leaving radiance of the forest canopy at a large scale with complex topography. The methodology adopted in this paper is: (1) virtual forest scene generation combined with a digital elevation model; (2) scene division method, shadowing effect correction and multiple scattering calculation; (3) merging the simulated sub-scene bidirectional reflectance factors (BRFs) to get the whole-scene BRF. The paper compares this new method with other models by choosing a large-scale conifer forest scene with a GAUSS terrain from RAMI3 (http://rami-benchmark.jrc.it). Multi-angle imaging spectroradiometer (MISR) data are used to validate the extended RGM in a Picea crassifolia forest area at a satellite pixel scale in the field campaign in Gansu Province, China. The root mean square error and correlation coefficient between the simulated BRF and the MISR BRF are 0.018 and 0.98, respectively. The uncertainty and error sources of the large-scale RGM model are thoroughly analysed.

Characterizing leaf geometry for grass and crop canopies from hotspot observations: A simulation study

Abstract The potential of canopy reflectance distributions in the hotspot region for characterizing leaf geometry (leaf size and shape) of grass and crop canopies is explored with computer simulations. In this article, a computer graphics method—Lindenmayer-systems (L-systems)—is used to render a series of leaf (grass) and architecturally realistic row-planted crop (corn-like) canopies that have a variety of geometrical structures. A radiosity–graphics combined model is then employed to calculate the radiation regime in a canopy, including canopy directional reflectance. An effectiveness ratio ( E ratio) is proposed, which is able to evaluate the performance of a given measure or index in estimation of the parameter of interest under the influence of a number of “noise” factors (other geometric and optical parameters of the canopy) at various noise levels. This E ratio is then applied to evaluate reflectance and normalized reflectance in the hotspot region for leaf geometry characterization. The result from simulated hotspot reflectance demonstrates that for both canopies, leaf geometry is estimable by using normalized reflectance within ±4–8° (or ±2–4°) around the hotspot direction in the principal cone (or principal plane). However, the center position and angular width of the optimal sampling region are affected by the number of noise factors [such as leaf area index, leaf angle distribution for leaf canopies, plus row structure for row-plant crop canopies] and their variation ranges. In most cases, normalized spectral reflectance in the near-infrared at a high solar zenith angle in the PC produces the most reliable results. The reason for better estimation of leaf geometry for grass and crop canopies than forests from hotspot observations is also discussed in this article.

Thermal Emission Hot-Spot Effect of Crop Canopies—Part I: Simulation

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 (R2 = 0.98 and RMSE = 0.04°C) with a function of the phase angle (ξ), the hot-spot amplitude (ΔTHS) and the half width of the hot spot (ξ0)> which can be quantified with the half width in the RED band. The planting row structure can reduce the ΔTHS by a maximum amount (about 1.2°C) when compared with an unstructured horizontal canopy. The ΔTHS 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 ΔTHS. The accuracy is very good for the horizontal canopies with triangular leaves (RMSE <; 0.4°C and R2 > 0.99), and acceptable for the virtual wheat and corn canopies (RMSE <; 1.8°C and R2 > 0.81).

Evaluation of Atmospheric Effects on Land-Surface Directional Reflectance With the Coupled RAPID and VLIDORT Models

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.

The Potential of Combined Lidar and SAR Data in Retrieving Forest Parameters using Model Analysis

3D Lidar waveform and 3D radar backscatter models based on Radiative Transfer theory were used to simulate waveform and backscattering of various plots with different stand ages and structures, which were generated using forest growth model. The inversion models for estimating forest Above Ground Biomass (AGB) and Average Stand Height (ASH) were derived from the combined simulated database of large footprint Lidar waveforms and L-band polarimetric SAR backscattering using stepwise analysis method. The inversion procedures were then applied to NASA LVIS and ALOS PALSAR data to retrieve forest parameters for the study area. The study area is a 10km by 10km area located at International Papers Northern Experiments Forest, Maine, USA, where field measurements that include stem coordinate, DBH, species and canopy position were recorded within a 200m by 150 m stand. Heights and AGB of total 7956 trees were estimated by applying species-specific allometric equations to stand measurements. AGB and height were then scaled up to the area according to the LVIS footprint size and location at 149 20m*20m plots, which were used to verify the inversion model developed using simulated database. The study concludes that Lidar waveform indices and SAR backscattering are complementary for forest parameters retrieving, which improved the limitation of signature saturation for regional biomass mapping using SAR data only. The comparison between inversed forest parameters and field measurements shows good consistency.