山地TM遥感影像大气辐射校正模型改进及地表反射率反演

基于光学遥感辐射传输理论,着重阐述了地形对天空散射光相互作用及邻近像元的影响,提出了一种改进的山地大气辐射校正模型及地表反射率反演方法;基于IDL编程实现模型算法,选择贵州黎平县丘陵森林覆盖典型研究区,结合Landsat-5TM和1∶50000DEM数据进行了实例验证、评价与分析。研究结果表明,本研究方法能够同时有效消除TM数据的大气与地形影响,提高地表反射率反演精度与数据质量,将进一步推动山地光学遥感数据的定量分析与应用。     

基于DART模型和随机森林估算山地叶面积指数

地形效应会使遥感影像中的地表反射率发生畸变,进而影响基于反射率估算的叶面积指数(Leaf Area Index,LAI)精度。为了减弱或消除地形对LAI反演的影响,基于三维辐射传输模型DART(Discrete Anisotropic Radiative Transfer)构建坡地反射率与LAI数据集作为训练数据。以反射率为输入,LAI为输出,利用随机森林算法进行训练,构建山地LAI反演模型。结合实际遥感影像数据实现山地LAI的估算,并利用实测数据对反演结果开展精度评价。同时,基于DART模型和随机森林构建了平地LAI反演模型作为参照以评价本文发展方法的有效性。结果表明：考虑了地形影响的山地LAI反演模型具有较强的估算能力,验证结果的精度(决定系数(R²)=0.57,均方根误差(RMSE)=0.77 m²/m²)优于平地反演模型(R2=0.46,RMSE=0.86 m2/m2);基于DART模型构建的山地反演模型能够捕捉到坡度和坡向对地表反射率的影响,其反演结果较好地还原了研究区LAI的空间分布,与地面真实情况接近。研究...     

山地森林地区遥感影像地形辐射校正研究

山区遥感影像反射率反演不但需要消除大气影响,而且必须消除地形影响.传统的地形校正方法通常属于经验统计方法,具有简单易用的优点,但本身也存在一些缺点,如理论上缺乏全面的物理分析,使用时具有较强的主观性,且不能与大气校正相耦合.相比之下,一些学者提出的基于辐射传输理论物理模型能在一定程度上克服这些缺点.本文针对森林地区,提出了一种基于辐射传输理论的地形校正及反射率反演模型.该模型与现有模型相比,考虑了树木冠层受地形影响的特殊性,因此适合于高植被覆盖的森林地区.最后以贵州省黎平县的ETM影像及DEM数据为例,对模型的有效性进行了验证.通过对比分析,证明该模型在森林地区的地形校正效果明显优于现有模型.     

基于模型的山地遥感图象辐射订正方法

对太阳直射、天空满散射和邻近地形的反射辐射进行了较为详细的分析,提出了崎岖山地真实反射率的恢复模型及相应的快速算法,从而实现了消除山地卫星影像中的地形的影响,恢复阴影所包含的细节。利用ＴＭ影像的实验表明,此方法可以有效地实现对影像的订正,为遥感图象的后处理提供更多的信息。     

森林覆盖区山地遥感地形校正的方法研究

基于山地遥感地形校正方法中的STS朗伯体模型和SCS模型,结合TM影像,提出了一种新的森林地形校正方法.该方法引入一个植被覆盖率参数用来估计亚像元中的各成分对辐亮度的影响,同时考虑了像元与像元之间的邻边效应影响.通过与其他现有的一些模型进行实地验证与检验,说明该方法能在一定的程度上解决不同覆盖程度的森林地形校正问题.     

长江口及邻近海域悬浮颗粒物对叶绿素a遥感反演算法的影响分析

利用水介质光辐射传输数值模型Hydrolight,结合前人对长江口及邻近海域水体的生物—光学模型研究,模拟不同光学水体的遥感反射率,并分析遥感反射率对悬浮颗粒物(SPM)的敏感性以及SPM对4种叶绿素a(Chla)反演算法(二波段、三波段、荧光基线高度(FLH)和综合叶绿素指数(SCI)算法)的影响。结果表明:由Hydrolight模拟得到的遥感反射率与现场同步实测的遥感反射率的均方根误差小于0.01sr-1,其中可实现遥感反射率在550~725nm波段较精确的模拟。遥感反射率对SPM的敏感性随着Chla浓度的升高而降低。二波段、三波段算法适合低SPM浓度水体的Chla浓度反演,FLH算法反演Chla浓度时易受SPM的影响,而SCI算法在中、高SPM浓度水体中消除SPM的影响进而反演Chla的潜力较好。     

基于IDL的遥感影像大气与地形校正方法实现

介绍了利用交互式数据语言（Interactive Data Language,IDL）开发TM/ETM遥感影像大气与地形校正模型的详细过程,以2000年4月30日密云ETM影像为例,对大气与地形校正方法的有效性和实用性进行了验证。结果表明,该方法有效地消除了大气与地形影响,提高了地表反射率等地表参数的反演精度和数据质量,为进一步开展定量遥感研究提供了数据质量保障。     

卫星遥感数据的山地散射辐射的计算与改正

地形条件决定的天空散射辐射光遮蔽角是影响卫片像元地面天空散射辐射的主要因素,本文利用与卫片匹配的数字地面模型建立了一个卫星遥感数据的山地散射辐射计算与改正模式。     

Landsat8卫星影像大气校正及其植被指数与SEVI性能比较

遥感影像受大气的吸收散射以及地形起伏变化的影响,使得传感器接收到的辐射信号既包含了地物的信息,同时也包含了大气以及地形的信息。为了提高地表反射率的反演精度,需要去除遥感影像中大气和地形的影响。提出了一种基于查找表的Landsat8-OLI遥感影像的大气校正方法,该方法由6S辐射传输模型生成查找表,其中输入的参数包括大气水蒸汽含量、臭氧浓度和气溶胶光学厚度等MODIS大气参数产品。利用传统方法建立的大气参数查找表通常只考虑一部分因素,这对于以MODIS产品为输入参数的大气校正是不适用的。本文建立了一个包括大部分输入参数的高维大气校正查找表,对于Landsat-8 OLI传感器具有很高的通用性,通过进行光谱分析、与USGS地表反射率产品交叉验证等方式来验证模型的精度。验证结果表明该方法能有效地反演精确可靠的地表反射率。最后,采用目视解译、统计分析将校正结果与SEVI做对比分析,比较地形影响消减的效果。结果表明该模型与SEVI在地形消减的效果上作用相当。     

Landsat8卫星影像大气校正及其植被指数与SEVI性能比较

遥感影像受大气的吸收散射以及地形起伏变化的影响，使得传感器接收到的辐射信号既包含了地物的信息，同时也包含了大气以及地形的信息。为了提高地表反射率的反演精度，需要去除遥感影像中大气和地形的影响。提出了一种基于查找表的Landsat8-OLI遥感影像的大气校正方法，该方法由6S辐射传输模型生成查找表，其中输入的参数包括大气水蒸汽含量、臭氧浓度和气溶胶光学厚度等MODIS大气参数产品。利用传统方法建立的大气参数查找表通常只考虑一部分因素，这对于以MODIS产品为输入参数的大气校正是不适用的。本文建立了一个包括大部分输入参数的高维大气校正查找表，对于Landsat-8 OLI传感器具有很高的通用性，通过进行光谱分析、与USGS地表反射率产品交叉验证等方式来验证模型的精度。验证结果表明该方法能有效地反演精确可靠的地表反射率。最后，采用目视解译、统计分析将校正结果与SEVI做对比分析，比较地形影响消减的效果。结果表明该模型与SEVI在地形消减的效果上作用相当。     

Parametrized BRDF for atmospheric and topographic correction and albedo estimation in Jiangxi rugged terrain,China

A method is presented for bi‐directional reflectance distribution function (BRDF) parametrization for topographic correction and surface reflectance estimation from Landsat Thematic Mapper (TM) over rugged terrain. Following this reflectance, albedo is calculated accurately. BRDF is parametrized using a land‐cover map and Landsat TM to build a BRDF factor to remove the variation of relative solar incident angle and relative sensor viewing angle per pixel. Based on the BRDF factor and radiative transfer model, solar direct radiance correction, sky diffuse radiance and adjacent terrain reflected radiance correction were introduced into the atmospheric‐topographic correction method. Solar direct radiance, sky diffuse radiance and adjacent terrain reflected radiance, as well as atmospheric transmittance and path radiance, are analysed in detail and calculated per pixel using a look‐up table (LUT) with a digital elevation model (DEM). The method is applied to Landsat TM imagery that covers a rugged area in Jiangxi province, China. Results show that atmospheric and topographic correction based on BRDF gives better surface reflectance compared with sole atmospheric correction and two other useful atmospheric‐topographic correction methods. Finally, surface albedo is calculated based on this topography‐corrected reflectance and shows a reasonable accuracy in albedo estimation.     

An Image based Measurement System for Anisotropic Reflection

This paper introduces an image based method for measuring bidirectional reflectance distribution functions (BRDF). The measurement system uses a CCD camera connected to a workstation to capture images from the material under investigation. The evaluation of the BRDF is performed in an image processing step, gathering BRDF values with a broad range of incident and reflected angles, followed by a fitting process, where these values are approximated by a chosen reflectance model. Absolute BRDF values are obtained by the usage of a diffuse reflectance standard. It is shown that the proposed measurement system produces very reasonable results compared to accurate measurements. Thus, it is an easy and cost efficient way to measure material properties needed for physically based rendering algorithms.     

Integration and Case Analysis of BRDF Model based on Linear Kernel\|driven Model#br#

Anisotropic reflectance is the intrinsic characteristic of an object surface.over the past few decades,various BRDF models have been developed for investigating the relationship between the vegetation canopy and reflectance anisotropy.This helps to retrieve biophysical parameters from the anisotropic reflectance patterns of vegetation canopy.In this study,for the purpose of assisting potential users to use these models,and to improve the understanding of the BRDF modeling,several BRDF models that are widely used in the remote sensing community have been integrated with the current version of the MaKeMAT (Multi\|angular Kernel\|driven Model Analysis Tool),based on the Interactive Data Language (IDL).This work retains all functions of the current version of the MaKeMAT model,meanwhile,adds some new functions by integrating these physical BRDF models.Undoubtedly,this work facilitates the potential users to process BRDF data and make further analysis in their work by operating a simpler visual interface.This helps to build a rapid communication between the kernel\|driven BRDF models and the physical BRDF models.Our initial results show that this model\|integration practice is a valuable reference for potential users to devise a similar technique.Our case study in coupling these physical BRDF models with the kernel\|driven models present a high correlation between them,with the determination of coefficients (R²) reaching 0.899~0.989 in the red and NIR bands.     

Variability in surface BRDF at different spatial scales (30 m-500 m) over a mixed agricultural landscape as retrieved from airborne and satellite spectral measurements

Over the past decade, the role of multiangle remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities impacted by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained ~ 1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75° off-nadir, and at spatial resolutions ranging from 3 m to 500 m. This unique dataset was used to examine the interaction of the spatial and angular characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a land cover type-specific a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution; and (3) the uncertainties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure.     

Multi-temporal MODIS-Landsat data fusion for relative radiometric normalization, gap filling, and prediction of Landsat data

A semi-physical fusion approach that uses the MODIS BRDF/Albedo land surface characterization product and Landsat ETM+ data to predict ETM+ reflectance on the same, an antecedent, or subsequent date is presented. The method may be used for ETM+ cloud/cloud shadow and SLC-off gap filling and for relative radiometric normalization. It is demonstrated over three study sites, one in Africa and two in the U.S. (Oregon and Idaho) that were selected to encompass a range of land cover land use types and temporal variations in solar illumination, land cover, land use, and phenology. Specifically, the 30 m ETM+ spectral reflectance is predicted for a desired date as the product of observed ETM+ reflectance and the ratio of the 500 m surface reflectance modeled using the MODIS BRDF spectral model parameters and the sun-sensor geometry on the predicted and observed Landsat dates. The difference between the predicted and observed ETM+ reflectance (prediction residual) is compared with the difference between the ETM+ reflectance observed on the two dates (temporal residual) and with respect to the MODIS BRDF model parameter quality. For all three scenes, and all but the shortest wavelength band, the mean prediction residual is smaller than the mean temporal residual, by up to a factor of three. The accuracy is typically higher at ETM+ pixel locations where the MODIS BRDF model parameters are derived using the best quality inversions. The method is most accurate for the ETM+ near-infrared (NIR) band; mean NIR prediction residuals are 9%, 12% and 14% of the mean NIR scene reflectance of the African, Oregon and Idaho sites respectively. The developed fusion approach may be applied to any high spatial resolution satellite data, does not require any tuning parameters and so may be automated, is applied on a per-pixel basis and is unaffected by the presence of missing or contaminated neighboring Landsat pixels, accommodates for temporal variations due to surface changes (e.g., phenological, land cover/land use variations) observable at the 500 m MODIS BRDF/Albedo product resolution, and allows for future improvements through BRDF model refinement and error assessment.     

A New Ward BRDF Model with Bounded Albedo

Due to its realistic appearance, computational convenience, and efficient Monte Carlo sampling, Ward's anisotropic BRDF is widely used in computer graphics for modeling specular reflection. Incorporating the criticism that the Ward and the Ward‐Dür model do not meet energy balance at grazing angles, we propose a modified BRDF that is energy conserving and preserves Helmholtz reciprocity. The new BRDF is computationally cheap to evaluate, admits efficient importance sampling, and thus sustains the main benefits of the Ward model. We show that the proposed BRDF is better suited for fitting measured reflectance data of a linoleum floor used in a real‐world building than the Ward and the Ward‐Dür model.     

Real‐Time Linear BRDF MIP‐Mapping

We present a new technique to jointly MIP‐map BRDF and normal maps. Starting with generating an instant BRDF map, our technique builds its MIP‐mapped versions based on a highly efficient algorithm that interpolates von Mises‐Fisher (vMF) distributions. In our BRDF MIP‐maps, each pixel stores a vMF mixture approximating the average of all BRDF lobes from the finest level. Our method is capable of jointly MIP‐mapping BRDF and normal maps, even with high‐frequency variations, at real‐time while preserving high‐quality reflectance details. Further, it is very fast, easy to implement, and requires no precomputation.     

Shadowing Dynamic Scenes with Arbitrary BRDFs

We present a real-time relighting and shadowing method for dynamic scenes with varying lighting, view and BRDFs. Our approach is based on a compact representation of reflectance data that allows for changing the BRDF at run-time and a data-driven method for accurately synthesizing self-shadows on articulated and deformable geometries. Unlike previous self-shadowing approaches, we do not rely on local blocking heuristics. We do not fit a model to the BRDF-weighted visibility, but rather only to the visibility that changes during animation. In this manner, our model is more compact than previous techniques and requires less computation both during fitting and at run-time. Our reflectance product operators can re-integrate arbitrary low-frequency view-dependent BRDF effects on-the-fly and are compatible with all previous dynamic visibility generation techniques as well as our own data-driven visibility model. We apply our reflectance product operators to three different visibility generation models, and our data-driven model can achieve framerates well over 300Hz.     

A General BRDF Representation Based on Tensor Decomposition

Generating photo‐realistic images through Monte Carlo rendering requires efficient representation of light–surface interaction and techniques for importance sampling. Various models with good representation abilities have been developed but only a few of them have their importance sampling procedure. In this paper, we propose a method which provides a good bidirectional reflectance distribution function (BRDF) representation and efficient importance sampling procedure. Our method is based on representing BRDF as a function of tensor products. Four‐dimensional measured BRDF tensor data are factorized using Tucker decomposition. A large data set is used for comparing the proposed BRDF model with a number of well‐known BRDF models. It is shown that the underlying model provides good approximation to BRDFs.     

Generating Reflected Directions from BRDF Data

Monte-Carlo path tracing algorithms for computer graphics require that given an incident light ray at a surface an outgoing direction can be computed with a distribution given by the magnitude of the bidirectional reflectance distribution function (BRDF). For analytic reflectance functions this can be done using various techniques including inverting the function, or tabulating some representation of the inverse. However, measured BRDF data sets are too large for this to be practical. We present a method to generate reflection rays distributed according to the magnitude of the BRDF. The method relies on a wavelet-based representation of the BRDF. This representation is efficient and compact, allowing large, anisotropic measured BRDF data sets to be represented with a few thousand coefficients. In particular, we exploit the wavelet representation to quickly compute integrals over ranges of the BRDF.