Improved airborne PolSAR calibration algorithm based on time-variant attitude compensation

The polarimetric synthetic aperture radar (PolSAR) usually has to be calibrated before practical application, so as to compensate for polarimetric distortion. The varying platform attitude is one of the factors causing distortion but has rarely been considered in existing polarimetric calibration algorithms. With the resolution of PolSAR systems improving and the synthetic aperture time prolonging, this factor cannot simply be ignored. The varying attitude will distort the polarimetric information by rotating the polarimetric orientation angle, and such distortion changes with azimuth time. In this article, we modified the conventional polarimetric system model to take account of the time-variant impact of the unstable platform attitude. A calibration algorithm is proposed to compensate the time-variant attitude impact on the raw return data. The proposed calibration algorithm is tested on the data collected by Institute of Electronics, Chinese Academy of Sciences P-band PolSAR system. Results show that it can achieve better performance by reducing crosstalk error than two conventional methods.     

Terrain topographic inversion using single-pass polarimetric SAR image data

1IntroductionFullypolarimetricSARimagerytechnologyisoneofthemostimportantadvance-mentsforspace-borneremotesensing.Ithasbeenextensivelyappliedtoterrainsurfaceclassification.The22-D(Dimensional)complexscatteringamplitudefunctionsFpq(p,q=v,h),and44-DrealMuellermatrixMij(i,j=1,…,4)canbemeasured[1].Co-polarizedorcross-polarizedbackscatteringsignatureisthefunctionoftheincidencewavewiththeellipticityanglecandorientationangley.Recently,twoflightsofpo-larimetricSARimagedatahavebeenutilizedtogene…     

Map of deep seated gravitational slope deformations susceptibility in central Italy derived from SRTM DEM and spectral mixing analysis of the Landsat ETM+ data

Considerable enhancement for morphometric interpretation can be obtained by means of the integration of spectral data with Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM). The effectiveness of topography classification with SRTM DEM is enhanced by the use of optical remote sensing data such as Landsat ETM+ that has undergone Spectral Mixing Analysis (SMA). The SMA uses a linear mixture model to provide a physical basis for a more detailed representation of land surface reflectance as mixture of endmembers. In this work we use these data for deep seated gravitational slope deformation (DSGSD) topography characterization to identify slopes whose morphology is indicative of deep seated phenomena. The final results indicate that when incorporated with optical SMA of the Landsat ETM+, the SRTM analysis should improve our capacity for mapping and identifying DSGSD in specific landscapes.     

Evaluating Shuttle radar and interpolated DEMs for slope gradient and soil erosion estimation in low relief terrain

The error in slope gradient estimates provided by digital elevation models propagates to spatial modelling of erosion and other environmental attributes, potentially impacting land management priorities. This study compared the slope estimates of Shuttle Radar Topographic Mission (SRTM) DEMs with those generated by interpolation of topographic contours, at two grid cell resolutions. The magnitude and spatial patterns of error in DEM slope, and derived erosion estimates using the Revised Universal Soil Loss Equation (RUSLE), were evaluated at three sites in eastern Australia. The sites have low-relief terrain and slope gradients less than 15%, characteristics which dominate the global land surface by area and are often highly utilised. Relative to a reference DEM resampled to the same resolution (a measure of DEM ‘quality’), the 90 m (3-s) SRTM DEM provided the best estimates of slopes, being within 20% for each 5% slope class outside alluvial floodplains where it over-predicted by up to 220%. Relative to a hillslope scale 10 m reference DEM, the 30 m (1-s) SRTM-derived DEM-S, provided slope gradient estimates slightly less biased towards under-prediction than the 90 m SRTM and significantly less biased on alluvial floodplains. In contrast, the 20 m vertical contour intervals underpinning the interpolated DEMs resulted in under-prediction of slope gradient by more than a factor of 5 over large contiguous areas (>1 km²). The 30 m DEM-S product provided the best estimate of hillslope erosion, being 3–4% better than the 90 m SRTM. The slope errors in the interpolated DEMs translated into generally poorer and less consistent erosion estimates than SRTM. From this study it is concluded that the SRTM DEM products, in particular the 30 m SRTM-derived DEM-S, provide estimates of slope gradient and erosion which are more accurate, and more consistent within and between low relief study sites, than interpolated DEMs.     

Construction of a high-resolution DEM of an Arctic ice cap using shape-from-shading

Digital elevation models (DEMs) of ice sheets and ice caps are usually constructed from elevation data acquired from airborne or satellite-borne altimetric systems. Consequently, the DEMs have a spatial resolution of about 1km which limits their use for most glaciological and remote sensing studies. In this paper we investigated the possibility of using a shape-from-shading technique, applied to a Landsat MSS image, to create a high spatial resolution DEM of Austfonna, an ice cap in Svalbard. A high correlation (coefficient of determination = 0.85) was observed between Landsat pixel brightness values, acquired during winter, and the surface slope component parallel to the solar azimuth. This relationship was used to create a DEM by calculating surface elevation profiles across the ice cap, using low spatial resolution radio echo sounding data as tie points. The resulting DEM had an estimated rms error of about 14m, with the error occurring mostly at low spatial frequencies. Shape-from-shading produces less accurate DEMs than interferometric SAR (InSAR) techniques. Nevertheless, in scenarios for which InSAR cannot be used to construct a DEM, shape-from-shading provides an acceptable alternative.     

Estimating vertical error of SRTM and map-based DEMs using ICESat altimetry data in the eastern Tibetan Plateau

The Geoscience Laser Altimeter System (GLAS) instrument onboard the Ice, Cloud and land Elevation Satellite (ICESat) provides elevation data with very high accuracy which can be used as ground data to evaluate the vertical accuracy of an existing Digital Elevation Model (DEM). In this article, we examine the differences between ICESat elevation data (from the 1064 nm channel) and Shuttle Radar Topography Mission (SRTM) DEM of 3 arcsec resolution (90 m) and map-based DEMs in the Qinghai-Tibet (or Tibetan) Plateau, China. Both DEMs are linearly correlated with ICESat elevation for different land covers and the SRTM DEM shows a stronger correlation with ICESat elevations than the map-based DEM on all land-cover types. The statistics indicate that land cover, surface slope and roughness influence the vertical accuracy of the two DEMs. The standard deviation of the elevation differences between the two DEMs and the ICESat elevation gradually increases as the vegetation stands, terrain slope or surface roughness increase. The SRTM DEM consistently shows a smaller vertical error than the map-based DEM. The overall means and standard deviations of the elevation differences between ICESat and SRTM DEM and between ICESat and the map-based DEM over the study area are 1.03 ± 15.20 and 4.58 ± 26.01 m, respectively. Our results suggest that the SRTM DEM has a higher accuracy than the map-based DEM of the region. It is found that ICESat elevation increases when snow is falling and decreases during snow or glacier melting, while the SRTM DEM gives a relative stable elevation of the snow/land interface or a glacier elevation where the C-band can penetrate through or reach it. Therefore, this makes the SRTM DEM a promising dataset (baseline) for monitoring glacier volume change since 2000.     

Measurement of ocean surface slopes and wave spectra using polarimetric SAR image data

Methods have been investigated which use fully polarimetric synthetic aperture radar (SAR) image data to measure ocean slopes and wave spectra. Independent techniques have been developed to measure wave slopes in the SAR azimuth and range directions. The azimuth slope technique, in particular, is a more direct measurement than conventional, intensity based, backscatter cross-section measurements.In the azimuth direction, wave-induced perturbations of the polarimetric orientation angle are used to sense the wave slopes. In the range direction, a new technique involving the alpha parameter from the Cloude-Pottier H-A-? (Entropy, Anisotropy, and (averaged) Alpha) polarimetric scattering decomposition theorem is used to measure slopes. Both measurement types are sensitive to ocean wave slopes and are directional. Taken together, they form a means of using polarimetric SAR (POLSAR) image data to make complete measurements of either ocean wave slopes, or directional wave spectra.These measurements must still contend with fundamental nonlinearities in the SAR image processing (i.e., azimuth direction “velocity bunching”) that are due to wave velocity and acceleration effects.NASA/JPL/AIRSAR L-, and P-band data from California coastal waters were used in the studies. Wave parameters measured using the new methods are compared with those developed using both conventional SAR intensity based methods, and with in situ NOAA National Data Center buoy measurement products.     

低山丘陵区多源数字高程模型误差分析北大核心CSCD

作为多学科交叉与渗透产物的数字高程模型(DEM)已在诸多学科和领域及实际应用中发挥了重要作用,但目前能够免费获取的高分辨全球DEM在不同区域仍存在很大的不确定性,应用之前进行质量评估至关重要。以烟台市为实验区,以大比例尺地形图(1∶10 000)生成的DEM为参照,结合坡度、坡向和土地覆被类型等地学因子,定量分析了目前广泛应用的两个版本ASTER GDEM(先进星载热辐射和反射辐射计全球数字高程模型)ASTETR 1和ASTER 2及不同空间分辨率SRTM DEM(航天飞机雷达地形测绘任务)(SRTM 1:～30m和SRTM 3:～90m)在低山丘陵区高程、坡度及坡向误差。结果表明:在研究区域内,ASTER 1、ASTER 2、SRTM 3、SRTM 1总体高程均方根误差分别为8.7m、6.3m、3.7m和2.9m。ASTER与SRTM的高程精度不同程度地受坡度、坡向以及土地覆被类型等地学因子的影响,DEM误差随坡度增加而增大,其中SRTM 3精度对该因子最敏感。尽管坡向对DEM精度影响不明显(4种DEM在不同坡向上的均方根误差波动范围均不超过2m),但是不同土地覆被类型下这4种DEM精度差异显著。此外,分析4种DEM提取的坡度可知,SRTM 1的均方根坡度误差最低(2.5°)、ASTER 1与ASTER 2的坡度的均方根误差大致相同(3.6°、3.9°)、SRTM 3的坡度均方根误差最高(4.3°)。坡向的精度SRTM 1最高,ASTER 1与ASTER 2次之,SRTM 3最低。研究结果对我国低山丘陵区ASTER GDEM与SRTM DEM的应用与精度评估具有一定的借鉴作用。     

InSAR技术获取高山峡谷区DEM精度研究

通过对金沙江河段高山峡谷区L波段的Alos-Palasar和C波段的Radarsat-2雷达单视复数数据的干涉处理,获取此区域的数字高程模型(DEM)。利用SRTM 90m分辨率的DEM为参考数据,通过对比分析发现InSAR技术生成的DEM精度与相干系数、地形和波长有密切的关系。同时也验证了在相干性好,地形起伏不太剧烈的地区,用InSAR技术生成DEM是可行的。     

Combination of SRTM3 and repeat ASTER data for deriving alpine glacier flow velocities in the Bhutan Himalaya

The present study evaluates the fusion of DEMs from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument and the Shuttle Radar Topography Mission (SRTM). The study area consists of high elevation glaciers draining through the rough topography of the Bhutan Himalayas. It turns out that the ASTER-derived and SRTM3 DEMs have similar accuracy over the study area, but the SRTM3 DEM contains less gross errors. However, for rough topography large sections of the SRTM3 DEM contain no data. We therefore compile a combined SRTM3-ASTER DEM. From this final composite-master DEM, we produce repeat ASTER orthoimages from which we evaluate the DEM quality and derive glacier surface velocities through image matching. The glacier tongues north of the Himalayan main ridge, which enter the Tibet plateau, show maximum surface velocities in the order of 100-200 m year⁻¹. In contrast, the ice within the glacier tongues south of the main ridge flows with a few tens of meters per year. These findings have a number of implications, among others for glacier dynamics, glacier response to climate change, glacier lake development, or glacial erosion. The study indicates that space-based remote sensing can provide new insights into the magnitude of selected surface processes and feedback mechanisms that govern mountain geodynamics.     

利用星载InSAR技术提取镇江地区DEM及其精度分析

InSAR技术是目前获取高精度数字高程模型（DEM）的一种新方法。为了分析InSAR技术提取DEM的精度,首先介绍了美国航天飞机雷达SRTM DEM的精度和数据结构,然后以江苏镇江地区作为试验区,采用ERS1/2卫星影像来提取DEM,并对星载SAR提取的DEM与SRTM 3弧秒分辨率DEM的精度作了比较。 结果表明,利用星载SAR提取的DEM分辨率与SRTM 3弧秒分辨率的DEM相当,能很好地显示出地形起伏（如山脉、沟谷）的纹理特征。进一步的研究还表明,利用InSAR技术提取DEM的精度与SRTM 3 DEM之间存在5米左右的系统误差,并对产生这一系统误差的原因作了详细分析。     

基于区域网平差的干涉合成孔径雷达数字高程模型校正

合成孔径雷达干涉测量（InSAR）是获取数字高程模型（DEM）的常规手段,而通过干涉技术获得DEM后,其精度会受到轨道定位、影像的配准、干涉图获取、相位解缠等精度的影响。已有的利用区域网平差提升DEM精度的研究忽略了DEM的初始平面定位误差的影响。引入DEM的平面高程一体化区域网平差,将区域网平差分解为平面定位六参数的优化和高程误差模型的平差求解两个独立的平差过程,同时利用激光测高数据作为高程控制。从哨兵干涉生成的20 m分辨率DEM实验结果看,平差后DEM的高程均方根误差（RMSE）从平差前的19.372 m提升到了3.459 m。DEM对应连接点的平面内符合精度RMSE从初始182.462 m提升至14.887 m。而传统的不考虑平面误差的DEM优化方法在平差后高程精度提升至7.865 m,远低于所提出的方法,验证了提出的考虑平面误差的区域网平差方法的有效性。     

Effects of terrain-induced shade removal using global DEM data sets on land-cover classification

Free access to global data sets of satellite images and digital elevation models (DEMs) such as Aster Global DEM (GDEM) and Shuttle Radar Topography Mission (SRTM) digital topography are expected to contribute to various study areas that deal with land cover and land use. To assess the capabilities of these global DEM data sets and to provide guidelines for performing shade removal under various terrain and illumination conditions, we evaluated the results of shade removal using the Minnaert correction and C-correction. These corrections were applied, using the GDEM (versions 1 and 2), SRTM, and a DEM derived from a local map (local DEM), to 30 sample images from 20 scenes of 10 path-rows in global land survey (GLS) Landsat-TM/ETM+ images, in terms of statistical indices and the accuracy of land-cover discrimination. The analysis indicated that the results of shade removal depended mainly on the correlation between the cosine of the sunshine incidence angle (cos(i)) and the radiance before shade removal, except in some cases with inferior illumination conditions. Of the three global DEMs, GDEM version 2 had the highest performance in shade removal. However, this study also indicated that successful shade removal was only one of the several factors that increased the accuracy of land-cover classification. In practical applications, shade removal can be recommended only for images where the terrain shade obviously disturbs the original spectral reflection characteristics of each land-cover type and no significant dependence of the land-cover distribution on the slope aspect is assumed. In such cases, also global DEMs evaluated in this study can be used for shade removal.     

Enhanced edge detection for polarimetric SAR images using a directional span-driven adaptive window

ABSTRACT

Automatic edge detection for polarimetric synthetic aperture radar (PolSAR) images plays a fundamental role in various PolSAR applications. The classic methods apply the fixed-shape windows to detect the edges, whereas their performance is limited in heterogeneous areas. This article presents an enhanced edge detection method for PolSAR data based on the directional span-driven adaptive (DSDA) window. The DSDA window has variable sizes and flexible shapes, and is constructed by adaptively selecting samples that follow the same statistical distribution. Therefore, it can overcome the limitation of classic fixed-shape windows. To obtain refined and reliable edge detection results in heterogeneous urban areas, we adopt the spherically invariant random vector (SIRV) product model since the complex Wishart distribution is often not met. In addition, a span ratio is combined with the SIRV distance to highlight the dissimilarity measure and to improve the robustness of the proposed method. The simulated PolSAR data and three real data sets from experimental synthetic aperture radar, electromagnetics institute synthetic aperture radar, and Radarsat-2 systems are used to validate the performance of the enhanced edge detector. Both quantitative evaluation and visual presentation of the results demonstrate the effectiveness of the proposed method and its superiority over the classic edge detectors.     

SPOT5-HRS digital elevation models and the monitoring of glacier elevation changes in North-West Canada and South-East Alaska

Monitoring the response of land ice to climate change requires accurate and repeatable topographic surveys. The SPOT5-HRS (High Resolution Stereoscopic) instrument covers up to 120 km by 600 km in a single pass and has the potential to accurately map the poorly known topography of most glaciers and ice caps. The acquisition of a large HRS archive over ice-covered regions is planned by the French Space Agency (CNES) and Spotimage, France during the 2007–2008 International Polar Year (IPY). Here, we report on the accuracy and value of HRS digital elevation model (DEM) over ice and snow surfaces.

A DEM is generated by combining tools available from CNES with the PCI Orthoengine^SE software, using HRS images acquired in May 2004 over South-East Alaska (USA) and northern British Columbia (Canada). The DEM is evaluated through comparison with shuttle radar topographic mission (SRTM) DEM and ICESAT data, on and around the glaciers. A horizontal shift of 50 m is found between the HRS and SRTM DEMs and is attributed to errors in the SRTM DEM. Over ice-free areas, HRS elevations are 7 m higher than those of SRTM, with a standard deviation of ± 25 m for the difference between the two DEMs. The 7-m difference is partly attributed to the differential penetration of the electromagnetic waves (visible for HRS; microwave for SRTM) in snow and vegetation.

We also report on the application of sequential DEMs (SRTM DEM in February 2000 and HRS DEM in May 2004) for the monitoring of glacier elevation changes. We map the topographic changes induced by a surge of one tributary of Ferris Glacier. Maximum surface lowering of 42 (± 10) m and rising of 77 (± 10) m are observed in the 4 years time interval. Thinning rates up to 10 (± 2.5) m/yr are observed at low altitudes and confirm the ongoing wastage of glaciers in South-East Alaska.     

A novel super-resolution method of PolSAR images based on target decomposition and polarimetric spatial correlation

The polarimetric synthetic aperture radar (PolSAR) is becoming more and more popular in remote-sensing research areas. However, due to system limitations, such as bandwidth of the signal and the physical dimension of antennas, the resolution of PolSAR images cannot be compared with those of optical remote-sensing images. Super-resolution processing of PolSAR images is usually desired for PolSAR image applications, such as image interpretation and target detection. Usually, in a PolSAR image, each resolution contains several different scattering mechanisms. If these mechanisms can be allocated to different parts within one resolution cell, details of the images can be enhanced, which that means the resolution of the images is improved. In this article, a novel super-resolution algorithm for PolSAR images is proposed, in which polarimetric target decomposition and polarimetric spatial correlation are both taken into consideration. The super-resolution method, based on polarimetric spatial correlation (SRPSC), can make full use of the polarimetric spatial correlation to allocate different scattering mechanisms of PolSAR images. The advantage of SRPSC is that the phase information can be preserved in the processed PolSAR images. The proposed methods are demonstrated with the German Aerospace Center (DLR) Experimental SAR (E-SAR) L-band full polarized images of the Oberpfaffenhofen Test Site Area in Germany, obtained on 30 September 2000. The experimental results of the SRPSC confirms the effectiveness of the proposed methods.¹     

SRTM DEM and its application advances

The Shuttle Radar Topography Mission (SRTM) provides for the first time a near-global high-resolution digital elevation model (DEM) with great advantages of homogeneous quality and free availability. The last 10 years or so have seen rapid advances in the data processing and applications of SRTM DEM. From the perspective of SRTM, we present in this article a brief overview of the principles, datasets, void filling and accuracy of SRTM DEM first. Special emphasis is on its application advances in various research fields including, but not limited to, geology, geomorphology, water resources and hydrology, glaciology, evaluation of natural hazards and vegetation surveys. Problems that arose from the applications and the future research interests are also addressed. We hope this study will greatly facilitate the ease of use of SRTM DEM in extensive fields.     

Crop discrimination based on polarimetric correlation coefficients optimization for PolSAR data

Crop discrimination is a necessary step for most agricultural monitoring systems. Radar polarimetric responses from various crops strongly relate to the types and orientations of the local scatterers, which makes the discrimination still difficult using the polarimetric synthetic aperture radar (PolSAR) technique. This work provides a new approach by investigating and utilizing the characteristics of polarimetric correlation coefficients in the rotation domain along the radar line of sight. The theoretical basis lies in that polarimetric correlation coefficients can reflect the different responses and can be enhanced at different levels for various land-cover types with suitable rotation angles in the rotation domain. In this vein, a polarimetric correlation coefficient optimization framework is established and new polarimetric features are extracted therein. Demonstration with multi-frequency (P-, L-, and C-bands) airborne synthetic aperture radar (AIRSAR) PolSAR data over crop areas validates that polarimetric correlation coefficients are crop dependent and the optimized polarimetric correlation coefficient parameters can better discriminate them. Then, a crop discrimination scheme is proposed using the derived polarimetric features. A flow chart for the optimal discrimination feature set selection and determination is provided and is validated by the real data with seven typical crop types. All these crop types are successfully discriminated for the P- and L-band data, whereas only two types of crops are slightly overlapped in the feature space for the C-band data. Experimental studies demonstrate the efficiency and potential of the established methodology.     

Validation of surface height from shuttle radar topography mission using shuttle laser altimeter

Spaceborne Interferometric SAR (InSAR) technology used in the Shuttle Radar Topography Mission (SRTM) and spaceborne lidar such as Shuttle Laser Altimeter-02 (SLA-02) are two promising technologies for providing global scale digital elevation models (DEMs). Each type of these systems has limitations that affect the accuracy or extent of coverage. These systems are complementary in developing DEM data. In this study, surface height measured independently by SRTM and SLA-02 was cross-validated. SLA data was first verified by field observations, and examinations of individual lidar waveforms. The geolocation accuracy of the SLA height data sets was examined by checking the correlation between the SLA surface height with SRTM height at 90 m resolution, while shifting the SLA ground track within its specified horizontal errors. It was found that the heights from the two instruments were highly correlated along the SLA ground track, and shifting the positions did not improve the correlation significantly. Absolute surface heights from SRTM and SLA referenced to the same horizontal and vertical datum (World Geodetic System (WGS) 84 Ellipsoid) were compared. The effects of forest cover and surface slope on the height difference were also examined. After removing the forest effect on SRTM height, the mean height difference with SLA-02 was near zero. It can be further inferred from the standard deviation of the height differences that the absolute accuracy of SRTM height at low vegetation area is better than the SRTM mission specifications (16 m). The SRTM height bias caused by forest cover needs to be further examined using future spaceborne lidar (e.g. GLAS) data.     

基于张量空间中的均值漂移聚类的极化SAR图像分割

提出了一种基于均值漂移(Mean Shift, MS)聚类的全极化合成孔径雷达(Polarimetric Synthetic Aperture Radar, PolSAR)图像无监督分割算法. 已有的工作在将MS算法应用于全PolSAR图像分割时, 仅使用每个像素点的极化总功率值作为该像素点的特征值, 没有充分利用极化协方差矩阵或者相干矩阵所包含的完整的极化散射信息. 但是如果直接利用每个像素点的极化协方差矩阵作为特征向量, 则这些特征向量构成的空间不再是一个欧氏空间, 而原始的MS算法是定义在欧氏空间中的. 因此, 本文首先将每一个像素点的厄尔米特正定极化协方差矩阵也称为一个张量, 而且使用黎曼流形来描述该张量空间. 然后, 原始的MS算法被扩展到该张量空间中. 直接扩展得到的算法每一步具有明确的含义, 但是运算复杂度较高. 所以本文又进一步对该算法进行了简化, 从而得到了一个实用的分割算法. 通过使用真实的全PolSAR数据以及仿真数据进行实验, 结果验证了新方法的有效性.