不同入射角下的雷达后向散射系数图像模拟

选择了新疆渭库三角洲(库车县、新和县、沙雅县)为实验区,利用Ulaby和Chapp的后向散射模型分别模拟了HV极化和HH极化的入射角为20°、24°、30°、33°、37°和40°的雷达后向散射系数图像。分析了不同入射角下图像各点后向散射系数值的散点图以及统计特征,得出由于入射角度的变化,两种极化的图像后向散射系数值变化较大,其变化趋势均符合余弦函数曲线分布,且模拟SAR图像很好的保留了地面散射信息。     

Mapping spatio-temporal water level variations over the central Congo River using PALSAR ScanSAR and Envisat altimetry data

Previous studies using synthetic aperture radar (SAR) backscattering coefficients have been used to distinguish vegetation types, to monitor flood conditions, and to assess soil moisture variations over the wetlands. Here, we attempted to estimate spatio-temporal water level variations over the central Congo mainstem covered with aquatic plants using the backscattering coefficients from the Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) Scanning SAR (ScanSAR) images and water levels from Envisat altimetry data. First, permanent open water, forest, macrophytes, and herbaceous plants have been classified over the central Congo Basin based on statistics of the backscattering coefficient values. Second, we generated multi-temporal water level maps over part of the Congo mainstem based on the relationship between Envisat altimetry-derived river-level changes and PALSAR ScanSAR backscattering coefficient variations. Finally, the water level maps were validated with Ice, Cloud and land Elevation Satellite (ICESat) altimetry-derived water levels. We obtained overall root mean square difference (RMSD) of 67.27 cm at 100-m scale resolution of PALSAR ScanSAR. Our study shows that we can obtain reasonable estimates of water levels of the rivers covered with seasonally floating or emergent macrophytes from backscattering coefficients. Furthermore, it is expected that the generated water level maps can be used as a ‘true’ data set to perform pre-launch study of the Surface Water Ocean Topography (SWOT) mission to be launched in 2021.     

Modelling temporal variations in microwave backscattering from reed marshes

A full understanding of radar backscattering characteristics and their seasonal variations is one of the important ways to analyse the growth conditions in wetlands. This research simulated seasonal C-band and L-band synthetic aperture radar (SAR) backscattering from reed marshes using a refined version of the electromagnetic (REM) model, which was first validated by time series of multimode SAR observations at the experimental site used. Then, two factors including sensor parameters and vegetation structure, which influence the temporal evolution of the radar response from reed marshes, were assessed. The results demonstrate that the radar response is closely related to growth processes in the reed marsh. At the early growth stage when reed marshes are sparse, the double-bounce mechanism was dominant at all the incidence angles of C-band radar, but for L-band radar, strong specular reflection was produced from the smooth water if the incidence angle is lower than 25°. It was also found that the sensitivity to the density and height of reed marshes is greater for L-band radar than at the C-band, indicating that L-band backscattering may be useful for reed marsh biomass retrieval.     

Multi-polarization Envisat-ASAR images as a function of leaf area index (LAI) of White Poplar and Desert Date plantations

The relationship between leaf area index (LAI) of plantations and multi-polarization Synthetic Aperture Radar (SAR) data (Envisat-ASAR) was investigated for White Poplar (Populus tomentosa Carr) and Desert Date (Elaeagnus angustifolius) in Heihe district, northwest china. The study showed that, for homogeneous White Poplar plantations, HH and HV polarization data (where H and V represent horizontal and vertical polarizations, respectively, and the first of the two letters refers to the transmission polarization and the second to the received polarization) were sensitive to LAI and the r² (logistic relationship fits) values between HH polarization and LAI, 0.56 and 0.58 on 25 and 28 June images respectively, was much higher than that for the other polarizations of VV, VH and HV. For Desert Date plantations, the heterogeneity of the forests results in a more complex backscattering than that for White Poplar. Incidence angle also plays an important role in SAR backscattering, so a suitable SAR mode should be chosen to avoid scattering saturation when the LAI and incidence angle exceed certain values. The logistic polarization ratios of HH/HV and VV/VH showed varying correlation with LAI over White Poplar plantations, probably due to incidence angle.     

基于高亮特征匹配的双视向SAR图像建筑物高度提取

由于城区场景的复杂性和SAR成像几何畸变的影响,基于单幅SAR图像的建筑物高度提取常常存在很大困难。针对这一问题,利用建筑物目标SAR成像形成的叠掩、二次散射、较强单次散射等散射机制对应的高亮特征非常典型,并且对方向性敏感的特点,提出了一种基于双视向SAR图像高亮特征与几何模型匹配的建筑物高度提取方法。首先分析了建筑物目标的SAR图像散射特征及对雷达视向的敏感性,然后构造了建筑物目标在双视向SAR图像上高亮特征几何模型,然后基于灰度均值、灰度概率分布、边界信息定义匹配函数,并利用多种群遗传算法进行优化求解,最终得到建筑物目标的高度信息。基于模拟和机载SAR图像的试验表明该方法的建筑物高度平均反演误差小于1m,可以有效提高建筑物高度反演的精度。     

基于遗传算法和雷达后向散射模型的地表参数反演研究

在地表自然裸露条件下,利用雷达后向散射系数反演地表粗糙度及地表土壤含水量已经开展了很多的研究,许多学者提出了很多相关的模型及反演技术。在已有散射模型的基础上,利用遗传算法反演地表参数,并且对反演效果进行了验证;然后分别基于AIEM模型和Oh模型对SIR-C雷达图像进行了反演计算,并对反演结果作了统计分析,从而为利用雷达图像反演地表信息提供了新的研究思路。     

Fully polarimetric airborne SAR and ERS SAR observations of snow: implications for selection of ENVISAT ASAR modes

Snow cover has a substantial impact on processes involved in the interaction between atmosphere and surface, and the knowledge of snow parameters is important in both climatology and weather forecasting. With the upcoming launch of Advanced Synthetic Aperture Radar (ASAR) instruments on Envisat, enhanced snow-mapping capabilities are foreseen. In this paper fully polarimetric C- and L-band airborne SAR data, ERS SAR and auxiliary data from various snow conditions in mountainous areas are analysed in order to determine the optimum ASAR modes for snow monitoring. The data used in this study are from the Norwegian part of the snow and ice experiment within the European Multi-sensor Airborne Campaign (EMAC'95) acquired in the Kongsfjellet area, located in Norway, 66°?N, 14°?E. Fully polarimetric C- and L-band SAR data from ElectroMagnetic Institute SAR (EMISAR), an airborne instrument operated by the Danish Center for Remote Sensing (DCR), were acquired in March, May, and July 1995. In addition, several ERS SAR, airborne photos, field and auxiliary data were acquired.

A larger separation between wet snow and bare ground in EMISAR C-VV polarisation data was found at high incidence angle (55°) compared to lower incidence angle (45°). Cross-polarized observations from bare ground, dry and wet snow in the incidence angle range 35° to 65° are below the specified Envisat ASAR noise floor of –20–22 dB. The backscattering angular dependency for wet snow and bare ground derived from EMISAR C-VV and ERS SAR data corresponds well, and agrees to some extent with volume and surface scattering model results. The C-band is more sensitive to variation in snow properties than the L-band.     

Simple modelling of radar backscattering coefficient over a bare soil: variation with incidence angle,frequency and polarization

As a basis for inversion algorithms, there is a need for the development of simple backscattering soil models which can account for the variations of incidence angle observed in the same picture or in multiangle systems. A correction factor for the variations of incidence angle is therefore coupled with a classical linear model of the variation of backscattering coefficient with surface soil moisture in a four-parameter model. The correction factor is based on the cosine-type behaviour of the backscattering coefficient as a function of incidence angle, which is observed for rough agricultural surfaces. This simple model is tested on radar measurements performed over a large range of radar configurations. The model is shown to reproduce correctly the observed variations of the radar signal with incidence angle and soil moisture. Its parameters have a physical sense and vary as expected, from literature, with frequency and polarization. When tested on data simulated by the analytical Integral Equation Model, the results of the cosine model are confirmed, as well as the variation of its calculated parameters with frequency and polarization. The inversion of the model with the angular correction factor shows that the cosine model allows the retrieval of soil moisture with a precision of about 20 per cent of the value at C band and at HV and HH polarization.     

Classification of low-salinity sea ice types by ranging scatterometer

Abstract

A helicopter-borne 8-channel ranging scatterometer HUTSCAT (Helsinki University of Technology Scatterometer) was used to investigate the backscattering behaviour of low-salinity sea ice at 5-4GHz and 9-8 GHz. The measurements were conducted during the BEPERS-88 Sea Ice Campaign in the Gulf of Bothnia, 6-12 March 1988. The backscattering properties of several sea ice types were examined at the two frequencies, using HH, VV, HV, and VH polarization modes. An incidence angle of 23° off nadir was used in order to investigate the feasibility of the ESA ERS-I (launched in July 1991) SAR for sea ice mapping. The capability of the new scatterometer to identify sea ice types was examined using the following radar output products at 8 channels: (a) the backscattering coefficient and (b) the characteristics of the radar return versus range spectrum (range resolution 65 cm).     

The use of a microwave backscatter model for retrieving soil moisture over bare soil

Abstract

Most attempts at predicting soil moisture from C-band microwave backscattering coefficients for bare soil are made by fitting experimental calibration relations obtained for limited ranges of incidence angle and soil surface roughness. In this paper, a more general approach is discussed using an inversion procedure to extend the use of a single experimental calibration relation to a wider range of incidence angle and surface roughness. A correcting function is proposed to normalize the backscattering coefficients to the conditions (incidence angle and surface roughness) of the calibration relation. This correcting function was derived from simulated data using the physical optics or KirchhofTs scatter model using the scalar approximation. Before discussing the inversion procedure, the backscattering coefficients calculated by the model have been compared with experimental data measured in the C-band, HH polarization and three incidence angles (Θ= 15°, 23°, 50°) under a wide range of surface soil moisture conditions (0.02H_v  0.35cm³ cm^-3) and for a single quite smooth soil surface roughness (0–011 _s  OOI4/n)m. The model was found to be experimentally validated from 15° to 23° of incidence and for surface soil moistures higher than 0-I0cm³cm^-3. For the inversion procedure, it is assumed to have a wider range of validity (15°  Θ 35° ) for ihc incidence angle. A sensitivity analysis of the model to errors on roughness parameter and incidence angle was performed in order to assess the feasability and suitability of the described inversion procedure.     

Optimal conditions for wet snow detection using RADARSAT SAR data

This paper presents simulation results of the backscattering coefficient, in order to discriminate between wet snow and dry snow covers sensed at 5.3 GHz by the RADARSAT Synthetic Aperture Radar (SAR) sensor. Snow-field measurements coinciding with the RADARSAT SAR overpasses are used to explore and set out optimal conditions for wet snow detection, as a function of the sensor incidence angles. The conditions concern wet snow surface characteristics, mainly the roughness represented by the surface slope m and the volumetric liquid water content, snwc (vol.%). Based on the 3-dB threshold value used in several wet snow detection algorithms, the results show that in order to be discriminated from dry snow covers, wet snow surfaces must be characterized as: (a) m≤0.058 and snwc≤1.1, if the sensor operates in the S1 mode (20-27° incidence angle range), and (b) m≤0.082 and snwc≤3.0, if the observations are made in the S7 mode (45-49° incidence angle range). For the identification of a very wet snow, it is also shown that the S7 mode of RADARSAT SAR sensor is more suitable than the S1 mode. The latter, however, provides better discrimination for low values of the snow liquid water content. Furthermore, for wet snow detection based on modeling, the present paper demonstrates the importance of using the appropriate methodology to assess the dielectric constant of the background medium.     

合成孔径雷达海面风场反演研究进展

合成孔径雷达高分辨率、全天候的观测能力使其成为大面积获取高分辨海面风场的重要手段,这有助于我们理解各种海洋现象的物理过程,尤其是在海岸带,合成孔径雷达反演风场更具优势。以合成孔径雷达风向确定方式为主线,详细阐述了国内外学者在合成孔径雷达风场反演方面的研究进展,主要包括：利用影像线性纹理特征进行风场反演、基于外部初始风向的风场反演方法以及利用影像本身所包含的其它信息进行的风场反演工作,诸如距离向入射角差异、多极化后向散射等,并对合成孔径雷达风场反演的发展给出自己的观点。     

Estimation of the moisture content of bare soil from RADARSAT-1 SAR using simple empirical models

Synthetic Aperture Radar (SAR) provides a remote sensing tool to estimate soil moisture. Mapping surface soil moisture from the grey level of SAR images is a demonstrated procedure, but several factors can interfere with the interpretation and must be taken into account. The most important factors are surface roughness and the radar configuration (frequency, polarization and incidence angle). This Letter evaluates the influence of these variables for estimation of bare soil moisture using RADARSAT-1 SAR data. First, the parameters of two linear backscatter models, the Ji and Champion models (Ji et al . 1995, Champion 1996), were tested and the constants recalculated. rms error based on the backscattering coefficient was reduced from 6.12 and 6.48 dB to 4.28 and 1.68 dB for the Ji and Champion models respectively. Secondly, a new model is proposed which had an rms error of only 1.21 dB. The results showed a marked increase in accuracy compared with the previous models.     

Radar imaging of Kelvin arms of ship wakes

The wave pattern generated by a moving ship is formed by two dominant features: the turbulent wake and a 'V'-shaped pattern trailing the ship, consisting of the two Kelvin arms. In this paper we investigate the radar imaging mechanism of Kelvin arms, which are formed by the cusp waves. A composite surface model for the radar backscattering at the ocean surface is used. The radar signatures of Kelvin arms can be attributed to tilt and hydrodynamic modulation of Bragg waves by the cusp waves. The proposed model allows the computation of the normalized radar backscattering cross-section (NRCS) as a function of radar frequency, polarization, incidence angle, wind speed and direction, and wavelength, direction, and slope of the cusp waves. By using this imaging model, radar signatures of cusp waves are calculated for several spaceborne Synthetic Aperture Radars (SARs): (1) the SEASAT L-band HH-polarized SAR, (2) the ERS-1/-2 VV-polarized SAR, (3) the RADARSAT C-band HH-polarized SAR, and (4) the X-, C- and L-band multipolarization SARs of the Space Radar Laboratory flown on the space shuttle during the SIRC/X-SAR mission in 1994. The results of the simulations are compared with SEASAT and SIR-C/X-SAR imagery of ship wake patterns. It is shown that the dependence of the observed radar signatures of Kelvin arms on radar look direction is consistent with the proposed imaging theory and that the measured relative mean NRCS values induced by Kelvin arms can be fairly well reproduced by the proposed model. The simulations indicate that ship wake signatures should be more clearly visible on SEASAT L-band SAR than on ERS-1/-2 or RADARSAT C-band SAR images. The radar signatures of Kelvin arms are strongest at low wind speeds and are not very sensitive to wind direction.     

Estimating the characteristics of vegetation canopies with airborne radar measurements

Abstract

Possible use of synthetic aperture radars (SAR) for monitoring agricultural canopies is investigated in this paper. Data have been acquired on the Orgcval watershed during the AGRISCATT'88 campaign. Four radar experiments were carried out with the airborne scattcrometer ERASME (C and X bands, HH and VV polarizations, multi-incidence angles). Simultaneous ground measurements (soil moisture, leaf area index, water content of the canopy) were conducted on 11 wheat fields. Backscattering coefficients of the canopies arc interpreted in the framework of semi-empirical ‘water-cloud’ models. A simple paramctrization of the angular effect of soil roughness is introduced, allowing the simultaneous use of multi-incidence angle radar data. With a unique set of parameters for each radar configuration ‘ frequency and polarization’ the water-cloud model appears to describe adequately the backscattering of all the fields, over the range of incidence angles. It is shown that in this case, attenuation is the dominant effect of the vegetation and an inversion algorithm is proposed for estimating the water content of vegetation. This algorithm requires measurements at two different incidence angles and various combinations of radar configurations are then tested.     

基于多阶散射模型的玉米后向散射特性分析

合成孔径雷达(Synthetic Aperture Radar,SAR)由于其特有的全天时、全天候成像及对农作物的穿透探测能力,已成为农作物信息获取的重要手段。该文建立基于Matrix Doubling 算法的玉米多阶散射模型,以全极化雷达遥感数据Radarsat-2为数据源进行模型验证,在模型基础上,根据玉米关键生长期的几何参数,分析了玉米的时域散射特征;玉米不同生长期由于结构上的差异,散射特征差别很大:在玉米出苗期,小角度情况下C波段VV-HV适用于土壤湿度的提取;在玉米成熟期,大角度情况下C波段HH-HV较适合玉米叶片含水量的分析。     

Potential of SAR sensors TerraSAR-X, ASAR/ENVISAT and PALSAR/ALOS for monitoring sugarcane crops on Reunion Island

Multi-temporal TerraSAR-X, ASAR/ENVISAT and PALSAR SAR data acquired at various incidence angles and polarizations were analyzed to study the potential of these new spaceborne SAR systems for monitoring sugarcane crops. The sensitivity of different radar parameters (wavelength, incidence angles, and polarization) to sugarcane growth stages was analyzed to determine the most suitable radar configuration for better characterisation of sugarcane fields and in particular the monitoring of sugarcane harvest.Correlation between backscattered signals and crop height was also carried out. Radar signal increased quickly with sugarcane height until a threshold height, which depended on radar wavelength and incidence angle. Beyond this threshold, the signal increased only slightly, remained constant, or even decreased. The threshold height is higher with longer wavelengths (L-band in comparison with C- and X-bands) and higher incidence angles (~ 40° in comparison with ~ 20°).The radar backscattering coefficients (σ°) were also compared to the Normalized Difference Vegetation Index (NDVI) calculated from SPOT-4/5 images. Results showed a high correlation between the behaviors of σ° and NDVI as a function of sugarcane crop parameters. A decrease in NDVI for fully mature sugarcane fields due to drying of the sugarcane (water stress) was also observed in the radar signal. This decrease in radar signal was of the same order as the decrease in radar signal after the sugarcane harvest. In general, it is more suitable to monitor the sugarcane harvest using high incidence angles regardless of the radar wavelength. SAR data in L- and C-bands showed an ambiguity between the signals of ploughed fields and those of fields in vegetation because of the high sensitivity of the radar signal at these wavelengths to surface roughness of bare soils. Indeed, sometimes the radar signal of ploughed fields was of the same order as that of harvested or mature sugarcane fields. Results showed better discrimination between ploughed fields and sugarcane fields in vegetation (sugarcane canopy) when using TerraSAR-X data (X-band).Concerning the influence of radar polarization, results showed that the co-polarizations channels (HH and VV) were well correlated, but had slightly less potential than cross-polarization channels (HV and VH) for the detection of the sugarcane harvest. Finally, SAR data at high spatial resolution were shown to be useful and necessary for better analysis of SAR images when the fields were of small size.     

Evaluation of RADARSAT-1 data for identification of burnt areas in Southern Europe

This study presents the combined analysis of RADARSAT products of different spatial resolutions acquired under different incidence angles for mapping burnt scars on forested areas of Central Portugal. Prior to the SAR data analysis, a number of pre-processing procedures were carried out. Noise was eliminated by adaptive texture preserving filtering. A specific algorithm for the geocoding of SAR images, based on a range-Doppler approach, enabled precise geocoding of the SAR data by means of a single very accurate ground control point. A novel incidence-angle-normalization for SAR imagery was applied to analyze the backscatter coefficient to a given incidence angles. Further, a backscatter coefficient analysis was performed according to the slope on forested areas and fire disturbed areas. A qualitative and quantitative investigation of the backscattering as related to the slope angle and time changes was performed. As a result of this analysis, the scenes that allowed maximizing the discrimination of burnt areas were selected as the input for the neural network classification. The investigation on the effect of the SAR incidence angle in burnt area discrimination determined that low incidence angles are required for discriminating burnt areas in hilly regions. It was also demonstrated that topography influences the level of discrimination of burnt areas since areas affected by forest fires on face-slopes presents higher backscatter coefficient than those back-slopes. Therefore, SAR data can play a significant role for burnt area mapping in Europe in those areas where optical data cannot be used due to persistent cloud cover.     

基于ENVISAT/ASAR的神经网络反演人工林叶面积指数研究

对我国西北黑河地区的人工林,进行了基于ENVISAT/ASAR数据构造神经网络的反演杨树林叶面积指数研究。首先,分析了白杨树林、沙枣树林的叶面积指数(LAI)与ENVISAT/ASAR不同极化后向散射系数的相关关系,研究表明人工林的空间分布均一性是影响雷达后向散射和LAI关系的首要因素,其次,不同的入射角对后向散射也具有明显的差异。基于上述分析,通过神经网络算法,利用不同时相、不同入射角的ENVISAT/ASAR雷达影像对白杨树林LAI进行了反演研究,对验证样本、训练样本、所有样本实测值与预测值进行了比较验证,其决定系数R²分别为0.61\,0.91和0.82,表明基于ENVISAT/ASAR雷达数据利用神经网络算法反演人工林叶面积指数的可行性。