水面船只SAR探测的极化方式研究

利用SIR-C SAR的C和L波段全极化数据,分析水面船只的极化散射特性和船只与背景海面雷达后向散射的信噪比特性,研究水面船只SAR探测的最优极化方式。结果显示,二面角散射是水面船只SAR成像的主要机理。线性极化中,HV极化具有最大的船只与背景海面雷达后向散射信噪比。与线性极化相比,圆极化的雷达后向散射信噪比更优。C波段和L波段的水面船只的极化散射特性存在较大的差异,L波段的信噪比大于C波段的信噪比。水面船只的雷达后向散射特性表明,L波段的圆极化是水面船只探测的最优极化方式。     

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.     

Simulated and measured X‐band radar reflectivity of land in mountainous terrain using a fan‐beam antenna

A computer program for meteorological radar siting, previously developed for pencil‐beam antenna, long‐range, C‐band radars, has been adapted for fan‐beam antenna, short‐range, X‐band radars. The simulator uses topographic information in the form of a raster digital elevation model and a surface backscattering cross‐section per unit area at grazing angles derived from the literature. It is independent of specific radar sites and radar systems. Its use will enhance optimized scanning strategies, antenna design tailored to mountainous terrain and knowledge of land‐clutter measurements at low grazing angles. The raster‐based approach used in implementing the program makes it compatible with any desired spatial resolution. Simplicity and short simulation times have been pursued as primary goals during the planning and implementation phases of the routines. A preliminary validation of the simulator using backscattering data acquired in the Alps is presented in this letter.     

Radiative transfer theory for polarimetric remote sensing of pine forest at P band

In this paper, the radiative transfer “RT” theory for clustered vegetation structures is developed and used to interpret polarimetric radar backseattering measurement data from pine forest. The RT theory has been widely used to calculate radar backscattering coefficients from layered geophysical media and to interpret the measurement data. However,the conventional RT theory ignores the relative phase information associated with structured scatterers. which may play an important role in the overall scattering behaviour. To take into account the clustered structures with the RT theory, the scattering function of each cluster is calculated by incorporating the phase interference of scattered fields from each component. Subsequently, the resulting phase matrix is used in the radiative transfer equations to calculate the polarimetric backscattering coefficients from layered random media embedded with vegetation clusters.A multi-scale structure model of pine forest, which includes trunks, primary and secondary branches, is used to interpret and simulate polarimetric radar response at P band “0·44Hz”. The theoretical calculations are shown to be in good agreement with the backscattering data measured at the Landes maritime pine forest during the MAESTRO 1 Campaign.     

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.     

Estimation of soil and crop parameters for wheat from airborne radar backscattering data in C and X bands

The study of radar backscattering signatures of wheat fields was investigated, using data collected on the Orgeval agricultural watershed (France) by the airborne scatterometer ERASME in C and X bands, HH and VV polarizations, at incidence angles from 15° to 45°, during two years for different soil moisture conditions with simultaneous ground-based measurements. A simple parameterization as water-cloud model with two driving parameters (the surface soil moisture and the plant water content) gives satisfactory results to estimate radar cross sections of wheat for a wide range of frequencies (C and X bands) and incidence angles (20° and 40°) within 1 dB in CHH and XHH and 2 dB in CVV and XVV. At the lower frequency (C band) the attenuated soil backscattering by the vegetation is dominant. It is shown that simple linear relations in C band between radar cross section and soil moisture are insufficient. A correction term for the vegetation attenuation is needed and is determined. Low contrast between the backscattering of dry and wet soil (around 6 dB) for a given vegetation density leads to a relatively high error in the estimation of soil moisture by radar (0.06 cm³ / cm³). At the higher frequency (X band), the radar backscattering is negatively correlated to the vegetation water content with a saturation of the radar cross section as the plant grows (about 6 dB of dynamic range between low and fully grown canopy) with no dependence on the soil signal. The achievable accuracy in the estimation of crop water content is the same at 20° and 40° and higher in XHH (about 0.5 kg/m²) than in XVV.     

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.     

C-band radar for determining surface soil moisture

A C band radar calibration method is presented. The experiment has been conducted in an agricultural area near Paris on three different types of surface: wheat stubble, sugar beet, and corn. It has been found that the sensitivity of radar backscattering coefficient δ₀ to surface soil moisture agrees well with the results obtained by Ulaby et al. (1979) when soil moisture values are expressed as percentage of the field capacity.     

极化分解技术在估算植被覆盖地区土壤水分变化中的应用

地表植被覆盖是影响雷达遥感估算土壤水分的主要因素之一。本文探讨了将极化分解技术与植被覆盖地区的一阶散射模型结合估算土壤水分变化的方法。雷达数据经极化目标分解技术分解后得到的双次散射项和一阶植被散射模型的植被-地表的双次散射项一一对应，再利用多时相雷达数据消除植被层后向散射的影响，从而估算出地表土壤水分变化量。最后应用全极化机载雷达数据（AirSAR）对该方法进行了检验，结果表明该方法能够较好的估算植被覆盖地表的土壤水分变化。     

Microwave electromagnetic modelling of Sahelian grassland

In this paper radar scattering models based on coherent and incoherent formulations for an African grassland (Sahelian) are examined. The coherent model is used to account for the structure of the grass plants and the results are compared with the same model assuming random placement and orientation of scatters, and the radiative transfer model. The validity of the three models applied to grass vegetation is determined by comparing the model predictions with Envisat Advanced Synthetic Aperture Radar (ASAR) data gathered in 2005 over Sahelian grassland. The Agoufou site, as defined in the African Monsoon Multidisciplinary Analysis (AMMA) project, is selected as the test target and a set of ground data was collected during 2004 and 2005. Through a comprehensive data comparison, it is shown that the coherent scattering model with a generator considering botanical information is the best model to predict the backscattering data that matches Envisat measurements well (correlation?=?0.92). At low incidence angles (<30°), the radar backscatter shows a strong dependence on soil moisture variations. The analysis of the different contributions leads to a study of the main scattering mechanisms. For high incidence angles, the backscattering coefficient at HH polarization shows a marked seasonal variation associated with grass presence.     

Soil moisture estimation over vegetated terrains using multitemporal remote sensing data

A new method for retrieving soil moisture content over vegetated fields, employing multitemporal radar and optical images, is presented. It is based on the integration of the temporal series of radar data within an inversion scheme and on the correction of the vegetation effects. The retrieval algorithm uses the Bayesian maximum posterior probability and assumes the existence of a relation among the soil conditions at the different times of the series. The correction of the vegetation effects models the variation, with respect to the initial time of the series, of the component of the backscattering coefficient due to the soil characteristics as function of the variations of the measured backscattering coefficient and of the biomass. The method is tested on the data acquired throughout the SMEX02 experiment. The results show that measured and estimated soil moistures are fairly well correlated and that the performances of multitemporal retrieval algorithm are better than those obtained by employing one radar acquisition, especially in terms of capability to detect soil moisture changes. Although the approach to correct the vegetation effects on radar observations needs to be further assessed on different sets of data, this finding demonstrates that the proposed method has a potential to improve the quality of the soil moisture retrievals.     

Correlation of precipitation estimates from spaceborne passive microwave sensors and weather radar imagery for BALTEX PIDCAP

This paper describes the evaluation of a combined radar and passive microwave dataset obtained during the PIDCAP study of the Baltic Sea Experiment (BALTEX), where three-dimensional volumes of data from the Gotland radar were obtained timed according to the overpasses of the DMSP-satellites F10 and F13. Both satellites are equipped with a Special Sensor Microwave/Imager (SSM/I), suitable for precipitation retrievals. We compare radar precipitation estimates, convolved to the native resolution of the SSM/I, at different altitudes with polarization and scattering indices ( S 85 ) derived from the SSM/I. For all 22 overpasses investigated here radar precipitation estimates at 3-4 km altitude correlate well with the SSM/I-derived S 85 (average correlation coefficient = 0.70). Although more directly linked to surface precipitation, polarization indices have been found to be less correlated with radar data, due to limitations inherent in the remote sensing of precipitation at higher latitudes. A stratification of the dataset into frontal and convective events revealed significant variations in these relationships for different types of precipitation events, thus reflecting different cloud microphysical processes associated with precipitation initialization. The relationship between S 85 and radar rain estimates at higher altitudes varies considerably for different convective and frontal events. The sensitivity of S 85 to radar-derived rain rate ranges from 3.1 K mm m 1 h m 1 for a strong convective event to about 25 K mm m 1 h m 1 for the frontal and about 70 mm m 1 h m 1 for the small-scale convective events. For extrapolated surface precipitation estimates, sensitivities decrease to 14 mm m 1 h m 1 and 25 mm m 1 h m 1 for frontal and small-scale convective precipitation, respectively.     

The effect of scintillation on the active microwave remote-sensing sensors

Recently, space-borne radar systems have been used to collect data for many different remote sensing applications. Some of the applications demand very high accuracy in the measured backscattering cross-sections. Microwave signals passing through the ionosphere may be, at times, affected by the scintillation effect, thus the backscattering cross-section. It is the purpose of this paper to discuss the gigahertz scintillation phenomenon and to assess the potential impact on active microwave observations.     

弱海流与波作用引起的海面雷达后向散射系数扰动特征

从波- 流作用产生的海面雷达后向散射系数扰动模型出发, 根据弱海流假定对模型进行了简化, 计算了弱海流与波作用引起的海面雷达后向散射系数扰动相对流场分布、流速幅值、海面风速、波流夹角、雷达波长、雷达入射角变化的数值结果, 分析了有关特征, 为研究微波雷达对海面流场变化效应的探测能力提供了有价值的参考。     

Preliminary analysis of ERS-1 wind scatterometer data over land surfaces

This Letter presents preliminary observations made with the ERS-1 wind scatterometer over land surfaces. A global backscattering coefficient image, synthesized from the original raw data indicates a strong correlation between the radar signal and the distribution of the main vegetation types throughout the world. In particular, tropical vegetation formations are well identified. The effects of angular and multitemporal variations on the backscattering coefficient σ⁰ are shown for different terrestrial surfaces. Illustrations are given for the African continent which presents numerous vegetation types along a north-south latitudinal gradient. Results indicate the strong capability of the ERS-1 scatterometer to discriminate and monitor vegetation change at a global scale.     

SAR polarimetric features of agricultural areas

The potential of synthetic aperture radar (SAR) in monitoring soil and vegetation parameters is being evaluated in extensive investigations, worldwide. A significant experiment on this subject, the Multi-sensor Airborne Campaign (MAC 91), was carried out in the summer of 1991 on several sites in Europe, based on the NASA/JPL polarimetric synthetic aperture radar (AIR-SAR). The site of Montespertoli (Italy) was imaged three times during this campaign at P-, L-, and C-band and at different incidence angles between 20° and 50°. Calibrated full polarimetric data collected over the agricultural area of this site have been analysed and a critical analysis of the information contained in linear and circular co-polar and cross-polar data has also been carried out. Here a guideline for the formulation of crop discrimination algorithms is suggested. It has been found that P-band data are rather effective only in discriminating broad classes of agricultural landscape, while finer detail can be obtained by integrating data at L- and C-bands. Indeed at L-band well developed ‘broad leaf’ crops can be separated from the others, whereas at C-band discrimination seems feasible in the case of moderate growth as well. Finally the sensitivity of backscattering coefficient to soil moiture and vegetation biomass is discussed.     

37 GHz和94 GHz的大气微波衰减比较分析

毫米波更接近云粒子的尺度,因此毫米波及短厘米波段雷达已被应用于云层的探测,美国与加拿大的云卫星计划(CloudSat)将要上3 mm云雷达(CPR),如何与已在天上的TRMM/PR结合,获得从薄云到浓厚云的垂直结构信息,是一个值得关注的课题。但是,毫米波云雷达探测,必须考虑的问题之一是大气衰减订正。主要比较分析了在37 GHz和94 GHz大气的衰减特性,目的是对星载94 GHz云雷达进行大气的衰减订正。计算分析了在不同云、大气条件下37 GHz和94 GHz
的大气衰减,得出如下结论:①大气气体的微波吸收在测云波段产生明显的衰减,其中水汽衰减效应变化很大;即将上天的空间94 GHz测云雷达必须有水汽衰减订正方案。②37 GHz和94 GHz雷达测云,由于大气和云衰减不同和雷达反射率的很大差异,导致雷达回波信号强弱不同。③对云层较薄、含水量较少的云,在不计雷达参数的情况下,37 GHz雷达回波信号不如94 GHz测云雷达,也就是说94 GHz对薄云有更强的探测能力;对云层较厚、含水量大的云,由于强衰减的作用,94 GHz雷达回波信号小于37 GHz雷达。④从大气衰减的不利因素方面考虑,空间94 GHz雷达测高层薄云的效果最好;测低层薄云时需要考虑气体衰减订正;因浓厚云的强衰减作用,探测其中下部的能力大大减弱,不仅要进行衰减订正,而且要借助其它信息来反演整个云层的含水量垂直分布。⑤为了获得从极薄到极浓厚云的垂直分布探测能力,未来测云雷达系统最好采用双波长甚至三波长(如94、37和13 GHz)。     

Linking physical remote sensing models with crop growth simulation models,applied for sugar beet

Abstract

In recent years, remote sensing and crop growth simulation models have become increasingly recognized as potential tools for growth monitoring and yield estimation of agricultural crops. In this paper, a methodology is developed to link remote sensing data with a crop growth model for monitoring crop growth and development. The Cloud equations for radar backscattering and the optical canopy radiation model EXTRAD were linked to the crop growth simulation model SUCROS: SUCROS-Cloud-EXTRAD. This combined model was initialized and re-parameterized to fit simulated X-band radar backscattering and/or optical reflectance values, to measured values. The developed methodology was applied for sugar beet. The simulated canopy biomass after initialization and re-parameterization was compared with simulated canopy biomass with SUCROS using standard input, and with measured biomass in the field, for 11 fields in different years and different locations. The seasonal-average error in simulated canopy biomass was smaller with the initialized and re-parameterized model (225-475 kg ha^?1), than with SUCROS using standard input (390-700 kg ha^?1), with ‘end-of-season’ canopy biomass values between 5500 and 7000kgha^?1. X-band radar backscattering and optical reflectance data were very effective in the initialization of SUCROS. The radar backscattering data further adjusted SUCROS only during early crop growth (exponential growth), whereas optical data still adjusted SUCROS until late in the growing season (at high levels of leaf area index (LAI), 3-5).     

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。     

Calibration and modelling of MAESTRO 1 polarimetric SAR data of a forest area in Les Landes,France

Abstract. The results of an analysis of polarimetric P, Land C-band SAR data from the JPL AIRSAR of a forest area of maritime pine in Les Landes, southwest France, are described and discussed. The data were acquired in connection with the MAESTRO I Campaign organized by ESA and JRC/lspra. Cross-talk and channel imbalance distortions are removed in a calibration process using the SAR data itself and trihedral corner reflectors positioned at the scene. Two calibration methods have been implemented and compared: the iterative Klein algorithm and the non-iterative Quegan algorithm. Quegan's method shows the largest reduction of the cross-talk, and the most stable and easily interpreted results. Also, absolute calibration using the integral method has been performed. The results presented show that P band (and to some extent L band) is very sensitive to trunk biomass using single-polarization radar data, at least at the incidence angles in the range from 38° to 52°, whereas C band is less sensitive. Also, the cylinder model by Durden et al. of the baekseattering from a forest has been implemented and the results show good agreement with the SAR data. The dominant scattering mechanisms have been determined using the model at P and L bands.