分层土壤后向散射及其在深层土壤湿度探测中的应用

该文定量地分析了频率、入射角、土壤介电常数等主要因素对电磁波穿透性能的影响。计算了分层土壤后向散射系数与地表参数,介电常数,系统工作频率,极化方式,入射角的关系,并从理论上得到验证,为深层土壤湿度反演提供了一个比较合理的模型。文中结论对低频段(0.1-1GHz)合成孔径雷达系统设计及深层土壤湿度反演具有实际应用价值。     

草原环境地表电磁散射的矩量法研究

为了满足草原及其附近目标雷达探测和遥感的需要,选用高斯型分布表示草和土壤表面的高度起伏情况,选取Topp 模型表示土壤层介电常数,采用双弥散模型表示草的介电常数,运用矩量法研究了草原环境地表的电磁散射特性,得到了散射系数的角分布曲线,讨论了入射角、入射波频率、草含水量、土壤湿度、土壤层和草层表面相关长度及均方根高度、草层厚度对散射系数的影响。结果表明,散射系数随散射角振荡地变化,在镜反射方向处有明显的散射增强效应;入射角和入射波频率对散射系数的影响较大,草含水量、土壤层和草层表面起伏相关长度和均方根高度对散射系数影响较小且较为复杂,土壤湿度、草层厚度对散射系数几乎没有影响。     

横向沙丘表面电磁散射的时域有限差分法研究

空对地海目标的监测、识别是用电磁波与处于地海环境中的目标相互作用的散射和辐射来获取信息、制导和目标截获的,为了满足地海环境中目标的监测、识别的需要,首先要研究地海环境的电磁散射特性;应用指数型分布粗糙面模拟横向沙丘表面的高度起伏情况,采用蒙特卡罗方法模拟横向沙丘迎风坡、背风坡表面以及沙丘之间的平坦沙漠表面,使用Herkelrath提出的土壤湿度与介电常数的通用式计算沙土的介电常数,运用FDTD计算方法研究了横向沙丘的电磁散射特性,得到了散射系数的角分布曲线;数值计算了沙丘坡顶高度,沙丘迎风坡与背风坡坡底到坡顶的水平距离,沙丘坡顶间间距,入射角度以及沙土湿度对散射系数的影响;计算结果表明,沙丘坡顶高度、沙丘迎风坡坡底到坡顶的水平距离、沙丘坡顶间间距、入射角度和沙土湿度对散射系数的影响较大,而沙丘背风坡坡底到坡顶的水平距离对散射系数的影响较为复杂。     

水稻,小麦后向散射特性的实验研究

对１９９０和１９９１年用Ｘ波段散射计测量的水稻和小麦后向散射系数在植物生长过程中随地物参数变化的结果进行了分析。结果表明：①Ｕｌａｂｒ对矮杆植被给出的经验模型与实验结果一致。②在水稻对微波的后向散射中，地面散射占主要部分。其后向散射系数可用植被参数Ｈ·Ｗ的线性模型来拟合。③由于麦田土壤含水量低，小麦后向散射系数一般比水稻低６ｄｂ左右。测量结果显示，在１８°入射角附近，小麦后向散射系数对土壤含水量较灵敏。在小麦生长过程中，测量的后向散射系数没有显示出明显的随生长期的规律性变化。     

粗糙地面与下方梯形目标复合电磁散射研究

利用MonteCarlo方法模拟了一维指数型粗糙地面,运用矩量法研究了粗糙地面与下方梯形截面导体柱的复合电磁散射特性,通过数值计算得到了复合散射系数随散射角的变化曲线,讨论了粗糙地面高度起伏均方根、土壤湿度、柱体埋藏深度、柱体大小、柱体倾角与复合散射系数依赖关系。结果表明粗糙面高度起伏均方根、土壤湿度对复合散射系数有显著影响,而柱体埋藏深度、柱体大小、柱体倾角对复合散射系数的影响较小。     

多薄膜层材料近旁轴激光波束散射及影响因素分析

研究了多种材料、涂层及多层介质薄膜近旁轴激光波束入射下的散射特征.数值计算不同材料,不同极化方式和入射角的激光波束单、双站散射系数.并分析不同材料物性参数、激光波束束腰半径和入射角对材料散射系数的影响.计算结果表明,金属较介质材料单、双站散射系数大,材料的介电常数、高度起伏和相关长度影响散射系数显著;对介质薄膜材料,多层介质薄膜较单层后向散射系数小9.21dh;改变入射角度时,离轴激光波束对介质单多层薄膜材料散射系数影响都较小;且波束束腰半径和入射波长相比拟时,激光波求散射较强,波束求腰半径远大于入射波长时,波束逐渐趋向于平面波.     

横向沙丘表面与上方矩形截面柱复合电磁散射的FDTD研究

分别使用指数型分布和高斯型分布表示沙漠表面的高度起伏状况,采用蒙特卡罗方法模拟横向沙丘表面和沙丘与沙丘间平坦沙漠表面,运用Herkelrath提出的土壤湿度与介电常数的通用式计算沙土的介电常数,选用FDTD数值计算方法分析高度起伏均方根、入射角度、目标长度、目标宽度、目标高度、横向沙丘的高度和横向沙丘迎风坡坡底到坡顶的水平距离的变化对散射系数的影响,得到横向沙丘表面与上方目标的复合电磁散射特性。分析了粗糙面为指数型分布和高斯型分布时散射系数的角分布曲线的不同之处。     

多波段全极化微波散射计系统的设计与分析

基于先进的矢量网络分析仪，组建了一套用于地物后向散射特性测量的多波段（2－18GHZ）全极化散射计系统，本文对系统的硬件组成及软件设计给出了详细的介绍和分析，并根据绝对校准实验和实际测试结果对该系统的性能予以讨论。综合分析表明，利用矢量网络分析仪的时域门功能，合理选择设置参数，可实现地物散射系数的精确测量。     

太赫兹频段金属粗糙表面散射特性

根据基尔霍夫近似理论分析了金属粗糙表面在太赫兹频段的散射规律及影响因素，通过加工不同粗糙度的金属铝板样品，基于远红外激光器搭建的单频点散射特性测量系统及远红外傅里叶光谱仪（FTIR）的宽带反射率测量系统，对粗糙铝板的散射规律进行了实验测量与验证，发现实验测量结果与基尔霍夫近似计算结果具有良好的一致性，证明了峰值散射系数与粗糙度和频率的负相关性，以及与入射角度的正相关性。分析了近似光滑和较大粗糙度两种极限情况下的散射特性，给出了基尔霍夫近似理论在太赫兹频段的适用条件。相关结论为复杂目标散射特性的理论计算奠定了基础，对太赫兹频段雷达相关理论和技术的发展具有重要意义。     

微扰法结合最小二乘支持向量机反演土壤湿度

将最小二乘支持向量回归技术应用到土壤湿度反演研究.利用微扰法数值模拟不同雷达参数下裸露土壤微波后向散射特性.经过数据敏感性分析,选取雷达频率为L波段(1.4 GHz),双入射角(40°、50°),并设计多种反演方案,分别以单极化、双极化及同极化后向散射系数比值作为微波信号样本信息,经过适当的训练,利用最小二乘支持向量回归技术对土壤含水量进行了反演研究.结果表明:当采用多入射角、同极化后向散射系数比值作为微波信号样本信息时,反演结果具有较高的精度.同时,经过与人工神经网络结果比较,证明了该方法的有效性及抗噪声能力,为土壤湿度的实时反演研究提供了一种新方法.     

Quantitative analysis of RADARSAT SAR data over a sparse forest canopy

This article studies the behavior of the backscattering coefficient of a sparse forest canopy composed of relatively short black spruce trees. Qualitative analysis of the multiangular data measured by the RADARSAT synthetic aperture radar (SAR) sensor shows a good agreement with surface and vegetation volume scattering fundamental behaviors. For a quantitative analysis, allometric equations and measurements of tree components collected within the framework of the Extended Collaboration to Link Ecophysiology and Forest Productivity (ECOLEAP) project are used, in an existing multilayer radiative transfer model for forest canopies, to simulate the RADARSAT SAR data. In our approach, the fractional cover of trees estimated from aerial photographs is used as a weighting parameter to adapt the closed-canopy backscattering model to the sparse forest under study. Our objective is to analyze the sensitivity of the backscattering coefficient as a function of sensor configuration, soil wetness, forest cover, and forest structural properties in order to determine the suitable soil, vegetation, and sensor parameters for a given thematic application. For the entire incidence angle domain (20/spl deg/ to 50/spl deg/) of the sensor, simulations show that over a sparse forest composed of mature trees the monitoring of the ground surface is possible only under very wet soil conditions. Therefore, this article informs about the ability of the RADARSAT SAR sensor in monitoring wetlands.     

Discrete scatter model for microwave radar and radiometer responseto corn: comparison of theory and data

As part of the Multisensor Aircraft Campaign, MACHYDRO, two microwave sensors, NASA's Airborne Synthetic Aperture Radar (AIRSAR) and Pushbroom Microwave Radiometer (PBMR) collected data over the same corn fields during the summer of 1990. During these flights, measurements were made on the ground of soil moisture and plant parameters. In this paper the measured canopy and soil parameters are used in a discrete scatter model to predict the response of both sensors (radar and radiometer). A distorted Born approximation is used to compute the scattering coefficient for the corn canopy. The backscatter coefficient gives the radar response and the radiometer response is obtained by integrating the bistatic coefficient over all scattering angles above ground. The objective of this analysis is to test the model and, in particular, to determine how well a single set of plant parameters and single model can yield agreement with both the radar and radiometer measurements. The model values are in reasonably good agreement with the measurements at horizontal polarization and reflect observed changes in soil moisture     

Quantitative retrieval of soil moisture content and surface roughness from multipolarized radar observations of bare soil surfaces

A semiempirical polarimetric backscattering model for bare soil surfaces is inverted directly to retrieve both the volumetric soil moisture content M/sub v/ and the rms surface height s from multipolarized radar observations. The rms surface height s and the moisture content M/sub v/ can be read from inversion diagrams using the measurements of the cross-polarized backscattering coefficient /spl sigma//sub vh//sup 0/ and the copolarized ratio p(=/spl sigma//sub hh//sup 0///spl sigma//sub vv//sup 0/). Otherwise, the surface parameters can be estimated simply by solving two equations (/spl sigma//sub vh//sup 0/ and p) in two unknowns (M/sub v/ and s). The inversion technique has been applied to the polarimetric backscattering coefficients measured by ground-based polarimetric scatterometers and the Jet Propulsion Laboratory airborne synthetic aperture radar. A good agreement was observed between the values of surface parameters (the rms height s, roughness parameter ks, and the volumetric soil moisture content M/sub v/) estimated by the inversion technique and those measured in situ.     

Effects of Vegetation Cover on the Radar Sensitivity to Soil Moisture

Measurements of the backscattering coefficient ?°, made for bare and vegetation-covered fields, are used in conjunction with a simple backscattering model to evaluate the effects of vegetation cover on the estimation accuracy of soil moisture when derived from radar observations. The results indicate that for soil moisture values below 50 percent of field capacity, the backscatter contribution of the vegetation cover limits the radar's ability to predict soil moisture with an acceptable degree of accuracy. However, for moisture values in the range between 50 and 150 percent of field capacity, the measured ?° is dominated by the soil contribution and the effects of vegetation cover become secondary in importance. It is estimated that in this upper soil moisture range, which is the primary range of interest in hydrology and agriculture, a radar soil moisture prediction algorithm would predict soil moisture with an error of less than ±15 percent of field capacity in 90 percent of the cases.     

The SIR-B Observations of Microwave Backscatter Dependence on Soil Moisture, Surface Roughness, and Vegetation Covers

An experiment was conducted from an L-band syntheticaperture perture radar aboard space shuttle Challenger in October 1984 to study the microwave backscatter dependence on soil moisture, surface roughness, and vegetation cover. The results based on the anlyses of an image obtained at 21° incidence angle show a positive correlation between scattering coefficient and soil moisture content, with a sensitivity comparable to that derived from the ground radar measurements [1]. The surface roughness strongly affects the microwave backscatter. A factor of 2 change in the standard deviation of surface roughness height gives a corresponding change of about 8 dB in the scattering coefficient. The microwave backscatter also depends on the vegetation types. Under the dry soil conditions, the scattering coefficient is observed to change from about -24 dB for an alfalfa or lettuce field to about -17 dB for a mature corn field. These results suggest that observations with a synthetic-aperture radar system of multiple frequencies ies and polarizations are required to unravel the effects of soil ture,oisre, surface roughness, and vegetation cover.     

Analysis of the Backscattering Coefficient of Salt-Affected Soils Using Modeling and RADARSAT-1 SAR Data

Salt significantly changes the backscattering coefficient of wet soil. This is easily observed on RADARSAT-1 synthetic aperture radar (SAR) images acquired over a salty depression located in the Egyptian desert. The aim of this paper is to use backscattering models to understand the behavior of the backscattering coefficient over salt-affected soils and to evaluate the possibility of monitoring the salt content. Simulations conducted over salt-affected soils show a lower sensitivity of these models to soil moisture compared to nonaffected soils. Besides, there is no model suitable to represent the variation of the backscattering coefficient due to changes in soil salinity. These results are discussed with regard to the magnitude of the two components of the dielectric constant (epsiv' and epsiv'). Based on a series of relationships, we propose a parametric formulation that allows us to determine the salinity acting on RADARSAT-1 SAR images without any use of backscattering models     

Retrieving snowpack properties and accumulation estimates from a combination of SAR and scatterometer measurements

This study combines two satellite radar techniques, low-resolution C-/Ku-band scatterometer and high-resolution C-band synthetic aperture radar (SAR) for glaciological studies, in particular mass-balance estimations. Three parameters expressing the mean backscattering and its dependency on azimuth and incidence angle are used to describe and classify the Antarctic ice sheets backscattering behavior. Simple linear regression analyses are carried out between ground truth accumulation data and the SAR backscattering coefficient along continuous profile lines. From this we parameterize the accumulation rate separately for certain snow pack regimes. We find that SAR data can be used to map mass-balance changes, however only within limited areas. Applying this method therefore generally requires accurate ground truth for regional calibration together with additional information regarding mean air temperature or elevation. This investigation focuses on the area of Dronning Maud Land, Antarctica. We present the first high-resolution accumulation map based on SAR data for the surrounding area of the EPICA deep ice core drilling site Kohnen, which is compared to reliable ground truth records as well as to a surface-mass-balance map interpolated from these at low resolution.     

Backscattering properties of boreal forests at the C- and X-bands

The backscattering properties of boreal forests are studied using empirical airborne and spaceborne radar data from Finland. Airborne measurements were carried out in the summer of 1992 by the HUTSCAT scatterometer at the Teijo test area in southern Finland. The HUTSCAT scatterometer is an eight-channel helicopter-borne profiling radar operating at the C- and X-bands. The ranging capability of the HUTSCAT scatterometer was employed in the semiempirical modeling of forest backscatter. The backscatter profile information was used in the analysis of the canopy transmissivity and the canopy backscattering coefficient by distinguishing backscattering contributions from the canopy and the ground. Additionally, ERS-1 C-band satellite SAR measurements were obtained for the Teijo test area and for the reference test area in Sodankyla in northern Finland. The radar results were compared with operational ground-based forest assessment data on forest compartments (stands) of the area. The key parameter investigated was the stem (bole) volume per hectare. The results obtained show the behavior of the canopy transmissivity and the canopy backscatter as a function of stem volume (directly related to the forest biomass). The influence of seasonal and diurnal changes on, and the effects of the changes in soil moisture to the backscattering coefficient were also investigated     

Radar measurement of soil moisture content

The effect of soil moisture on the radar backscattering coefficient was investigated by measuring the 4-8 GHz spectral response from two types of bare-soil fields: slightly rough and very rough, in terms of the wavelength. An FM-CW radar system mounted atop a 75-ft truck-mounted boom was used to measure the return at 10 frequency points across the 4-8 GHz band, at 8 different look angles (0degthrough70deg), and for all polarization combinations. A total of 17 sets of data were collected covering the range 4-36 percent soil moisture content by weight. The results indicate that the radar response to soil moisture content is highly dependent on the surface roughness, microwave frequency, and look angle. The response seems to be linear, however, over the range 15-30 percent moisture content for all angles, frequencies, polarizations, and surface conditions.