The relationship between the backscattering coefficient and thebiomass of narrow and broad leaf crops

The influence of the shape and dimensions of plant constituents on the backscattering of agricultural vegetation is investigated. Multifrequency multitemporal polarimetric data, collected at C- and L-bands by means of airborne and satellite synthetic aperture radar (SAR), showed that the relations between the backscattering of crops and the vegetation biomass depend on plant type, and that there are different trends for “narrow” and “broad” leaf crops. In the latter crops, backscattering increases with an increase in the biomass, especially at L-band. This behavior is typical of media in which scattering is dominant, whereas on “narrow leaf” plants, the trend is flat or decreasing, denoting a major contribution of absorption. Theoretical simulations obtained with a discrete element radiative transfer model have confirmed that a different backscattering of crops with the same biomass may be due to plant geometry     

Volume decorrelation effects in polarimetric SAR interferometry

Volume decorrelation is an aspect of synthetic aperture radar interferometry that is currently at stake. It stems from the distribution in height of the backscattering cross section in a imaged scene, and it widely affects interferometric coherence images, e.g., in the presence of forests or buildings. The interest in its reduction lies on the fact that "resolving" volume decorrelation and fixing the exact position of the scattering centers in a resolution cell may lead to an estimation of the height of the observed distributed scatterers. Indeed, the determination of the volume scattering contribution is determinant in digital elevation model generation as well as in biomass estimation. However, volume decorrelation itself may be a source of information on the mechanisms that originate it. In this paper, a distinction is made between the behavior of volume decorrelation due to random volumes and stationary distributed targets. The two cases are then studied by means of polarimetry: the response of such targets to different polarizations is considered by applying a series of decompositions of the scattering matrix, and a systematic analysis of the interferometric coherence characteristics is reported.     

Simulation of interferometric SAR response for characterizing thescattering phase center statistics of forest canopies

A coherent scattering model for tree canopies is employed in order to characterize the sensitivity of an interferometric SAR (INSAR) response to the physical parameters of forest stands. The concept of an equivalent scatterer for a collection of scatterers within a pixel, representing the vegetation particles of tree structures, is used for identifying the scattering phase center of the pixel whose height is measured by an INSAR. Combining the recently developed coherent scattering model for tree canopies and the INSAR Δk-radar-equivalence algorithm, accurate statistics of the scattering phase-center location of forest stands are obtained numerically for the first time. The scattering model is based on a Monte Carlo simulation of scattering from fractal-generated tree structures, and therefore is capable of preserving the absolute phase of the backscatter. The model can also account for coherent effects due to the relative position of individual scatterers and the inhomogeneous extinction experienced by a coherent wave propagating through the random collection of vegetation particles. The location of the scattering phase center and the correlation coefficient are computed using the Δk-radar equivalence simply by simulating the backscatter response at two slightly different frequencies. The model is successfully validated using the measured data acquired by JPL TOPSAR over a selected pine stand in Raco, MI. A sensitivity analysis is performed to characterize the response of coniferous and deciduous forest stands to a multifrequency and multipolarization INSAR in order to determine an optimum system configuration for remote sensing of forest parameters     

星载双极化SAR冬小麦物候期识别方法

冬小麦是中国主要的粮食作物之一,准确及时地获取冬小麦物候信息是冬小麦长势监测和产量预估的必要条件。星载合成孔径雷达(SAR)是一种微波遥感设备,具有全天时、全天候的优势,可实现对周期性农作物物候期大范围监测。基于时间序列Sentinel-1A SAR数据,提出一种星载双极化SAR冬小麦物候期识别方法。该方法基于特征值分解和极化散射分析技术,提取不同物候期冬小麦的后向散射系数、极化熵、主导散射角等参数,实现冬小麦物候期识别。实验结果表明,物候期识别总体精确度达到79%。该方法在冬小麦生长监测方面具有实用推广价值。     

基于Freeman分解的植被参数反演新方法

基于极化Freeman分解的极化协方差矩阵参数,极化干涉SAR互协方差矩阵可简化建模为植被高度、消光系数和地面干涉相位的函数。基于此,该文建立了以极化干涉SAR互协方差矩阵估算值与互协方差矩阵观测值之差为目标函数、以3个植被参数为未知量的优化模型,提出了基于Freeman分解的植被参数反演新方法。该方法避免了三阶段植被参数估计方法所面临的体相关系数确定问题,提供了一种独立于三阶段植被参数估计的新思路。仿真结果验证了新方法的有效性。     

Electromagnetic scattering from grassland. II. Measurement andmodeling results

For pt.I see ibid., vol.38, no.1, p.339-48 (2000). The validity of a coherent, grassland scattering model is determined by comparing the model predictions with direct measurements of a representative grass canopy. A wheat field was selected as the test target, and polarimetric, multifrequency backscattering data were collected over an entire growing season, along with a complete set of ground-truth data. The L-band measured data demonstrated a strong dependence on azimuthal look direction in relation to the row direction of the wheat. The C-band measurements likewise showed an interesting backscattering response, wherein σ_νν⁰ actually increased with incidence angle for many cases. The coherent scattering model provides backscattering data that match and predict these measured data and most of the other measured data well. The model shows that at L-band, the incoherent scattering power alone is insufficient for predicting the measured results, as the coherent terms can dominate the total scattered energy. Additionally, the model, which accounts for this nonuniform illumination of the wheat elements, demonstrates the peculiar data observed for C-band. Likewise, it is demonstrated that the fidelity used to model grass constituents (e.g., curvature) is required to match the scattering measurements accurately     

InSAR for estimation of changes in snow water equivalent of drysnow

This paper describes the theoretical relation between interferometric phase and changes in snow water equivalent (SWE) and show results from experiments using ERS-½ tandem data. The main scattering contribution from a dry snow cover is from the snow-ground interface. However, the radar wave will be refracted in the snow. Thus, only small changes in the snow properties between two interferometric synthetic aperture radar (SAR) images will change the interferometric phase. This phase change is shown to introduce a significantly increase in the digital elevation model (DEM) height error, although no effects are observed on the degree of coherence. The phase change is also shown to affect the differential interferometric results and may wrongly be interpreted as range displacement. The presented theory and results implies that light snowfall and/or small changes in snow properties between interferometric SAR (InSAR) image acquisitions, may introduce significant height errors in DEM derived from glaciers, ice sheets, or bare ground, even in the case of high degree of coherence. Thus, meteorological observations in addition to degree of coherence must be considered when generating DEM in areas covered with snow or where snow fall is likely to have occurred     

光与雷达遥感协作及其农业应用

用遥感影像提取农作物信息是精细农业的基础.传统的光学遥感局限于大气无云的优质影像,而微波遥感在提取农作物信息方面尚未得到充分的利用.寻找一种能够克服这些局限的农作物遥感信息提取的方法是有意义的.探讨了一种光和雷达遥感协作的方法,并应用于土壤和植被信息的提取,验证其应用潜力.用Karam等(1992)的微波散射模型,并作了相应修改:1)考虑粗糙地表面后向散射;2)光学遥感作为模型变量直接输入.将这种协作方法应用到两个数据集的处理,一个来自亚利桑那Maricopa农业中心,一个来自日本国家农业-环境科学协会的Tsukuba试验基地.这些数据包括一些实测的土壤和植被的数据以及陆地卫星Landsat和欧洲遥感卫星ERS遥感影像.结果初步表明雷达影像和光学影像在提取土壤和植被信息时可以有效地结合起来,在特定地方的农业管理中有着较好的应用前景.     

MIMO雷达三维干涉诊断成像方法

2维合成孔径雷达(Synthetic Aperture Radar, SAR)和逆合成孔径雷达(Inverse Synthetic Aperture Radar, ISAR)成像是目标散射机理高分辨率分析和散射诊断测量的重要手段,现有被广泛采用的技术主要包括转台ISAR和导轨SAR成像技术。相比于传统的2维成像,3维成像可以提供目标局部散射中心在空间的3维位置和散射强度信息。因此,探索新的、可工程化实现与应用的目标3维成像技术是一项极具吸引力的工作。该文提出一种基于多输入多输出(Multiple-Input Multiple-Output, MIMO)阵列技术的3维干涉成像方法。首先,设计并试验了一种具有高孔径利用率和通过虚拟孔径实现干涉成像功能的MIMO阵列;其次,分析了MIMO阵列合成的两组虚拟孔径所成两幅2维雷达像的干涉相位与目标散射中心高度之间的关系,发展了MIMO雷达3维干涉成像算法;最后,通过数值仿真和原理样机实验验证了所提方法在目标散射机理分析和诊断测量应用中的可行性和有效性。      

Microwave Emission and Plant Water Content: A Comparison between Field Measurements and Theory

Microwave radiation from a canopy cover depends primarily on the vegetation's thermal and dielectric properties; the latter are dependent on plant biometrical parameters and water content. Emission measurements carried out by means of ground-based X-and Ka-band radiometers have shown that crop coverage of soil can be detected through the spectral signatures of bare soil and vegetation. Moreover, measured brightness temperature and the radiative transfer theory for a scattering medium allow estimation of the scattering and absorption properties of the canopy. These parameters have been computed for corn and alfalfa using experimental data and a simple model in which anisotropic scattering is considered by means of transformed parameters w' and r'. We found that the single scattering albedo w' is always lower than 0.1, whereas the optical depth T' is very high. The latter has been correlated to plant water content by means of a logarithmic function.     

基于激光散射图像小麦叶片叶绿素检测研究

为了实现叶绿素含量的无损检测研究,采用激光后向散射图像技术来测量小麦叶片光学特性参量的方法,进行了理论分析和实验验证。利用670nm和970nm的半导体激光器和视频成像系统获得了小麦叶片的激光后向散射图像,通过漫反射理论分析了叶片组织表面的漫射光分布和在这两个波长下绿叶、黄叶、干叶的激光后向散射图像的变化特征,取得了其光学特性参量数据(约化散射系数和吸收系数),并与叶片的叶绿素相对含量值建立对应的函数关系。结果表明,小麦叶片的光学特性参量与叶绿素相对含量值呈现线性相关,其中利用约化散射系数建立的叶绿素相对含量值预测模型中,预测集样本的相关系数为0.9095,预测均方根误差为5.9;利用吸收系数建立的叶绿素相对含量值预测模型中,预测集样本的相关系数为0.8366,预测均方根误差为7.5,说明激光后向散射图像技术测定植物叶绿素含量是可行的。这一结果对激光散射图像实现农作物长势诊断是有帮助的。     

海洋环境对雷达海杂波后向散射特性影响分析

为分析海洋环境对雷达海杂波后向散射特性的影响,建立了一种基于修正复合模型方法的雷达海杂波后向散射关系模型。雷达入射余角较大时,主要散射形式为镜面散射;入射余角较小时,主要散射形式为Bragg散射。考虑了逆顺风条件下后向散射系数的差异性,改进了原有模型Bragg散射的方向海谱部分,增加了风向因子。利用模型对不同入射角条件下海洋环境因素与后向散射系数的关系进行了仿真计算。计算结果表明,当海面作为雷达波的反射面时,雷达后向散射特性十分复杂,风速、风向、海浪、降水、海面油污等海洋环境因素都会对其产生影响。其中,风速和有效波高对海面后向散射的影响最大,风向次之,降水再次之,而海面油污的影响最小。      

Measurement and modeling of the millimeter-wave backscatterresponse of soil surfaces

The millimeter-wave (MMW) backscatter response of bare-soil was examined by conducting experimental measurements at 35 and 94 GHz using a truck-mounted polarimetric scatterometer and by developing appropriate models to relate the backscattering coefficient to the soil's surface and volume properties. The experimental measurements were conducted for three soil surfaces with different roughnesses under both dry and wet conditions. The experimental measurements indicate that in general the backscattering coefficient is comprised of a surface scattering component σ^s and a volume scattering component σ ^v. For wet soil conditions, the backscatter is dominated by surface scattering, while for dry conditions both surface and volume scattering are significant, particularly at 94 GHz. Because theoretical surface scattering models were found incapable of predicting the measured backscatter, a semiempirical surface scattering model was developed that relates the surface scattering component of the total backscatter to the roughness parameter ks, where k=2π/λ and s is the rms height, and the dielectric constant of the soil surface. Volume scattering was modeled using radiative transfer theory with the packed soil particles acting as the host material and the air voids as the scattering particles. The combined contribution of surface and volume scattering was found to provide good agreement between the model calculations and the experimental observations     

多次散射中心横向位置属性及图像表征

多次散射结构是不可忽视的重要散射来源,其等效视在散射中心往往偏离目标区域,目前的解译和识别方法不具备对SAR图像中的多次散射中心现象进行散射机理和散射结构溯源的能力。为深入挖掘多次散射中心位置的本质,本文以散射中心的理论为基础,正向建立了具有明确物理含义的散射中心模型,揭示了多次散射中心横向位置与复杂多次射线路径的联系,解释了多普勒频率的形成机制,并探讨了其在雷达目标识别中的应用。首先,本文从电磁散射物理过程出发,推导了任意阶次射线场的解析表达式;其次,结合正向物理推导获取的雷达回波信号表达式与逆傅里叶变换,表征了目标在单站雷达上的图像特征,实现了散射中心三维空间位置在单站雷达图像中的直接映射;最后,通过仿真,构建了多次散射射线光程、回波信号相位表征、雷达图像散射中心位置三者之间的物理关联。     

The seasonal behavior of interferometric coherence in boreal forest

The capability of SAR interferometry has been previously demonstrated in various applications. In particular, the use of interferometric coherence has shown promising results in forest monitoring, however, mainly in discriminating forested and nonforested areas. The authors have collected ERS-1 and ERS-2 Tandem data from two boreal forest test sites in Finland. The data have been processed into interferometric coherence and intensity images. These images have been used to a) compare the behavior of interferometric coherence and intensity for various land-use and forest classes and b) extensive analysis on the behavior of interferometric coherence in boreal forests as a function of stem volume. Based on the observations and the use of a boreal forest semi-empirical backscattering model, they have developed an empirical model that describes interferometric coherence of boreal forests using backscattering information. The results indicate that coherence is more sensitive to the stem volume than the C-band backscattering intensity. However, the intensity and coherence data contain complementary information and therefore, the use of both data sources is beneficial in the observation of boreal forest     

A three-dimensional radar backscatter model of forest canopies

A three-dimensional forest backscatter model, which takes full account of spatial position of trees in a forest stand is described. A forest stand was divided into cells according to arbitrary spatial resolution. The cells may include “crown”, “trunk”, and “gap” components, determined by the shape, size and position of the trees. The forest floor is represented by a layer of “ground” cells. A ray tracing method was used to calculate backscattering components of 1) direct crown backscatter, 2) direct backscattering from ground, 3) direct backscattering from trunk, 4) crown-ground scattering, and 5) trunk-ground scattering. Both the attenuation and time-delay of microwave signals within cells other than “gap” were also calculated from ray tracing. The backscattering Mueller matrices of these components within the same range intervals were incoherently added to yield the total backscattering of an image pixel. By assuming a zero-mean, multiplicative Gaussian noise for image speckle, the high-resolution images were aggregated to simulate a SAR image with a given spatial resolution and number of independent samples (looks). A well-characterized 150 m×200 m forest stand in Maine, USA, was used to parameterize the model. The simulated radar backscatter coefficients were compared with actual JPL SAR data. The model gives reasonable prediction of backscattering coefficients averaged over the entire stand with agreement between model and data within 1.35 dB for all channels. The correlations between simulated images and SAR data (10 by 15 pixels) were positive and significant at the 0.001 level for all frequencies (P, L, and C bands) and polarizations (HH, HV, and VV)     

具有极化特征的植被相干散射模型及参数反演

重点研究了具有极化特征的植被相干散射模型及参数反演算法。基于目标分解理论,推导了植被及地表回波的极化干涉相干系数与植被高度、衰减系数、地形相位等参数之间的数学关系,以衰减系数作为极化分量的函数,建立了具有明显极化特征的植被及地表相干散射模型。在此基础上,以全极化干涉相干系数作为输入参量,考虑模型对极化的依赖性,采用三阶段法对植被的物理参量进行反演,获得了地形相位和植被高度。在环境可控的微波暗室内构建了极化干涉半实物合成孔径雷达系统对模型进行实验验证,获取了南洋杉和土壤所构成场景的极化干涉回波数据,实验结果表明:采用该模型在场景的地体幅度比小于-10dB的情况下,植被反演高度与实际高度的误差仅为0.03m,说明了模型的有效性。     

Backscattering from a randomly rough dielectric surface

A backscattering model for scattering from a randomly rough dielectric surface is developed. Both like- and cross-polarized scattering coefficients are obtained. The like-polarized scattering coefficients contain single scattering terms and multiple scattering terms. The single scattering terms are shown to reduce to the first-order solutions derived from the small perturbation method when the roughness parameters satisfy the slightly rough conditions. When surface roughnesses are large but the surface slope is small, only a single scattering term corresponding to the standard Kirchhoff model is significant. If the surface slope is large, the multiple scattering term will also be significant. The cross-polarized backscattering coefficients satisfy reciprocity and contain only multiple scattering terms. The difference between vertical and horizontal scattering coefficients increases with the dielectric constant and is generally smaller than that predicted by the first-order small perturbation model. Good agreements are obtained between this model and measurements from statistically known surfaces