ENVISAT/ASAR多角度干涉雷达数据山区DEM生成及精度分析

在地形起伏较大的山区用干涉SAR生成DEM时,合适的入射角是获取高精度DEM的重要参数之一.本文基于ENVISAT/ASAR多角度干涉雷达数据,SRTM 90米分辨率的DEM以及1:5万的数字化DEM数据,从定性和定量的角度比较和分析了干涉SAR在获取山区DEM时,入射角对DEM精度的具体影响.结果表明:对于ASAR的多入射角干涉雷达数据,在不同入射角条件下由于雷达叠掩和透视收缩的影响,获取的DEM精度差别很大,入射角带来的影响相当显著,比如IS2和IS4角度得到的DEM的精度差超过了6米.因此,在山区干涉SAR地形成图时,必须对入射角的大小进行严格的选择.     

Qualitative and quantitative assessment of TanDEM-X DEM over western Himalayan glaciated terrain

Glaciers have a high impact in the socio-economic sectors including water supply, energy production, flood and avalanches. A high precision digital elevation model (DEM) is required to monitor glaciers and to study various glacier processes. The present study deals with the qualitative and quantitative evaluation of the DEM generated from the bistatic TanDEM-X data by comparing it with GPS, Ice, Cloud, and land Elevation Satellite (ICESat) data and standard global DEMs such as Shuttle Radar Topography Mission (SRTM) and Advanced Space-borne Thermal Emission and Reflection Radiometer Global DEM (ASTER GDEM). The study area consists of highly undulating glaciated terrain in western Himalaya, India. The results reveal that TanDEM-X is slightly better than SRTM both qualitatively and quantitatively, whereas ASTER GDEM showing maximum discrepancy among the three DEMs. The Root Mean Square Error (RMSE) of the TanDEM-X DEM with respect to GPS is 3.5 m at lower relief and 11.9 m at glaciated terrain, against 6.7 and 12.5 m for SRTM and 9.3 and 19.8 m for ASTER GDEM, respectively, for the same sites. On an average, for the whole study area, the RMSE of TanDEM-X is 7.9 m, SRTM is 9.3 m and ASTER GDM is 14.2 m. The RMSE of TanDEM-X, SRTM and ASTER GDEM with respect to ICESat are 16.3, 19.9 and 101.1 m, respectively. It is evident from the analysis that though SRTM is closer to TanDEM-X in terms of accuracy in the mountainous terrain, however, TanDEM-X will be more useful for studying glacier dynamics and topography.     

基于SRTM DEM的InSAR高分辨率山区地表高程重建算法

山体的叠掩和阴影现象造成的信号去相关,一直是InSAR重建山区地表高程的瓶颈之一.为此,提出了一种新的基于粗分辨率SRTM DEM(约90m分辨率)辅助InSAR数据重建山区地表高程的方法.利用SRTM DEM模拟的干涉相位,对ERS-1/2干涉相位做去地形相位处理,得到残余相位.通过对解缠后的残余相位计算方差提取叠掩和阴影区域的噪声,并用平均相位近似恢复噪声区域的相位,然后将其转换为高程,并用SRTM DEM作高程补偿处理,从而实现地表高程重建.最后,定量比较了该方法与传统InSAR技术生成的DEM精度.实验表明,这种方法能有效提高传统InSAR技术生成地表高程的精度,这对提高星载雷达数据的使用效率具有重要意义.     

露天矿区多源数字高程模型数据对比分析

针对数字高程模型数据源不同会带来一定的不确定性和差异性的问题,选取德国某露天矿为实验区,以高精度DEM数据TanDEM-X为参照,对比了SRTM、AW3D30、ASTER GDEM与TanDEM-X数据的高程精度,分析了DEM数据的差异.结果表明:(1)露天矿区的开采和复垦活动明显地体现在了不同时期获取的DEM高程变化...     

A case study of using external DEM in InSAR DEM generation

Synthetic aperture radar interferometry (InSAR) has been used as an innovative technique for digital elevation model (DEM) and topographic map generation. In this paper, external DEMs are used for InSAR DEM generation to reduce the errors in data processing. The DEMs generated from repeat-pass InSAR are compared. For steep slopes and severe changes in topography, phase unwrapping quality can be improved by subtracting the phase calculated from an external DEM. It is affirmative that the absolute height accuracy of the InSAR DEM is improved by using external DEM. The data processing was undertaken without the use of ground control points and other manual operation.     

Effect of Contour Intervals and Grid Cell Size on the Accuracy of DEMs and Slope Derivatives

Digital Elevation Models (DEMs) are indispensable tools in many environmental and natural resource applications. DEMs are frequently derived from contour lines. The accuracy of such DEMs depends on different factors. This research investigates the effect of sampling density used to derive contours, vertical interval between contours (spacing), grid cell size of the DEM (resolution), terrain complexity, and spatial filtering on the accuracy of the DEM and the slope derivative. The study indicated different alternatives to achieve an acceptable accuracy depending on the contour interval, the DEM resolution and the complexity of the terrain. The effect of these factors on the accuracy of the DEM and the slope derivative was quantified using models that determine the level of accuracy (RMSE). The implementation of the models will guide users to select the best combination to improve the results in areas with similar topography. For areas with variable terrain complexity, the suggestion is to generate DEMs and slope at a suitable resolution for each terrain separately and then to merge the results to produce one final layer for the whole area. This will provide accurate estimates of elevation and slope, and subsequently improve the analyses that rely on these digital derivatives.     

利用TanDEM-X生成DEM的精度评定

目前,许多学者对TanDEM-X生成DEM开展了一些研究,其研究成果也显示了TanDEM-X生成高精度DEM的可行性。为了验证TanDEM-X/TerraSAR-X干涉生成的DEM能否满足测图要求,需要对其进行精度评价和分析。相对于C波段的ERS、ASAR和L波段的ALOS,X波段的高分辨率TerraSAR影像干涉条纹更密集,解缠更加困难。针对这一问题,本文设计了一种低分辨率SRTM辅助高分辨率的X波段的TerraSAR干涉相位解缠方案,提高了解缠的效率和精度。同时,本文提出了一种基于协方差函数的方法对TDX/TSX DEM进行精度分析和评价。该方法通过对各个距离上的协方差值进行拟合,消除了高程误差异常对InSAR DEM精度评价的影响,可以更加客观真实地反映DEM的精度。实例分析结果表明：采用协方差函数方法来评价DEM的精度是可行的,对于试验研究区域,TDX/TSX干涉生成的DEM总体精度为1.42 m,能够满足1：10 000测图要求,为我国空白地区的测图提供了有利条件。     

Fusion of high-resolution DEMs derived from COSMO-SkyMed and TerraSAR-X InSAR datasets

Voids caused by shadow, layover, and decorrelation usually occur in digital elevation models (DEMs) of mountainous areas that are derived from interferometric synthetic aperture radar (InSAR) datasets. The presence of voids degrades the quality and usability of the DEMs. Thus, void removal is considered as an integral part of the DEM production using InSAR data. The fusion of multiple DEMs has been widely recognized as a promising way for the void removal. Because the vertical accuracy of multiple DEMs can be different, the selection of optimum weights becomes a key problem in the fusion and is studied in this article. As a showcase, two high-resolution InSAR DEMs near Mt. Qilian in northwest China are created and then merged. The two pairs of InSAR data were acquired by TerraSAR-X from an ascending orbit and COSMO-SkyMed from a descending orbit. A maximum likelihood fusion scheme with the weights optimally determined by the height of ambiguity and the variance of phase noise is adopted to syncretize the two DEMs in our study. The fused DEM has a fine spatial resolution of 10 m and depicts the landform of the study area well. The percentage of void cells in the fused DEM is only 0.13 %, while 6.9 and 5.7 % of the cells in the COSMO-SkyMed DEM and the TerraSAR-X DEM are originally voids. Using the ICESat/GLAS elevation data and the Chinese national DEM of scale 1:50,000 as references, we evaluate vertical accuracy levels of the fused DEM as well as the original InSAR DEMs. The results show that substantial improvements could be achieved by DEM fusion after atmospheric phase screen removal. The quality of fused DEM can even meet the high-resolution terrain information (HRTI) standard.     

Topographic correction of ALOS-PALSAR images using InSAR-derived DEM

Topographic corrections of synthetic aperture radar (SAR) images over hilly regions are vital for retrieval of correct backscatter values associated with natural targets. The coarse resolution external digital elevation models (DEM) available for topographic corrections of high resolution SAR images often result into degradation of spatial resolution or improper estimation of backscatter values in SAR images. Also, many a times the external DEMs do not spatially co-register well with the SAR data. The present study showcases the methodology and results of topographic correction of ALOS-PALSAR image using high resolution DEM generated from the same data. High resolution DEMs of Jaipur region, India were generated using multiple pair SAR images acquired from ALOS-PALSAR using interferometric (InSAR) techniques. The DEMs were validated using differential global positioning system measured elevation values as ground control points and were compared with photogrammetric DEM (advanced spaceborne thermal emission and reflection radiometer – ASTER) and SRTM (Shuttle Radar Topography Mission) DEM. It was observed that ALOS-PALSAR images with optimum baseline parameters produced high resolution DEM with better height accuracy. Finally, the validated DEM was used for topographic correction of ALOS-PALSAR images of the same region and were found to produce better result as compared with ASTER and SRTM-DEM.     

基于大比例尺地形图DEM快速建立方法的研究

利用现有大比例尺地形图快速生成DEM,通过对原数据格式的分析,利用程序采用基于高程点和等高线2种方式从dwg文件中批量提取出高程信息,高效、快速地获取大比例尺地形图中高精度的高程数据;使用VC^ 和ObjectARX编程技术进行DEM建模,在此过程中,通过采取优化数据结构等几种改进措施有效地减小了数据冗余并大大减少了程序运行的CPU时,快速制作出大区域高分辨率DEM。     

Mapping from ASTER stereo image data: DEM validation and accuracy assessment

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on-board the National Aeronautics and Space Administration's (NASA's) Terra spacecraft provides along-track digital stereo image data at 15-m resolution. As part of ASTER digital elevation model (DEM) accuracy evaluation efforts by the US/Japan ASTER Science Team, stereo image data for four study sites around the world have been employed to validate prelaunch estimates of heighting accuracy. Automated stereocorrelation procedures were implemented using the Desktop Mapping System (DMS) software on a personal computer to derive DEMs with 30- to 150-m postings. Results indicate that a root-mean-square error (RMSE) in elevation between ±7 and ±15 m can be achieved with ASTER stereo image data of good quality. An evaluation of an ASTER DEM data product produced at the US Geological Survey (USGS) EROS Data Center (EDC) yielded an RMSE of ±8.6 m. Overall, the ability to extract elevations from ASTER stereopairs using stereocorrelation techniques meets expectations.     

一种基于高分辨率雷达影像以及外部DEM辅助的复杂地形制图方法

为满足在坡度陡、高差大的复杂地形地区高精度DEM制图的需要,在传统的雷达干涉测量技术的基础上,通过引入外部DEM,建立外部DEM模拟相位和干涉解缠相位的对应关系,构建多维线性模型,进行线性回归分析,去除误差相位趋势;同时根据引入的外部DEM估计高程的误差范围,进行高程点的滤波,达到精化DEM的目的,形成最终的DEM产品。该方法已经应用于高分辨雷达影像（COSMO数据）在云南德钦地区DEM地形图的制作,通过GPS数据的验证,其精度达到了国家1∶50 000 DEM制图要求。     

基于栅格DEM的地形特征提取与分析

以陕北延安地区燕儿沟流域为实验样区,运用比较分析法和数理统计法进行基于栅格DEM的地形特征提取和分析,以及DEM分辨率对地形特征的影响,并计算和比较了地形特征的空间统计分布。研究表明:一个相对真实的DEM能够通过修改生成DEM的基本材料,以及对DEM进行再加工而获得。由于DEM分辨率的不同,由此得到的地形特征值(如坡度、地形指数、河网密度等)在统计特性上也会随之变化。随着DEM分辨率的降低,坡度减小,地形坦化,地形指数均值变大,流域总面积变大,子流域数量减少,河流总长度减小,河网密度降低。     

DEM Extraction in Urban Areas Using High-Resolution TerraSAR-X Imagery

Three-dimensional (3D) spatial information is crucial for improving the quality of human life through urban planning and management, and it is widely utilized due to its rapid, periodic and inexpensive acquisition. In this context, extraction of digital surface and elevation models (DSM and DEM) is a significant research topic for space-borne optical and synthetic aperture radar (SAR) remote sensing. The DSMs include visible features on the earth’s surface such as vegetation, forest and elevated man-made objects, while DEMs contain only the bare ground. In this paper, using TerraSAR-X (TSX) high resolution Spotlight (HS) images, high-resolution interferometric DEM generation in a part of Istanbul urban area is aimed. This is not an easy task because of SAR imaging problems in complex geometry of urban settlements. The interferometric processing steps for DSM generation were discussed including critical parameters and thresholds to improve the quality of the final product and a 3 m gridded DSM was generated. The DSM-DEM conversion was performed by filtering and the quality of generated DEM was verified against a reference DEM from stereo photogrammetry with 3 m original grid spacing. The achieved root mean square error of height differences (RMSZ) varies from 7.09 to 8.11 m, depending on the terrain slope. The differential DEM, illustrates the height differences between generated DEM and the reference DEM, was generated to show the correlation between height differences and the coherence map. Finally, a perspective view of test area was created draping extracted DEM and a high-resolution IKONOS panchromatic image.     

Uncertainty analysis of soil erosion modelling using different resolution of open-source DEMs

The Digital Elevation Model (DEM) is one of the important parameters of soil erosion assessment and notable uncertainties are found in using different resolutions of the DEM. Revised Universal Soil Loss Equation model has been applied to analyze the effect of open-source DEMs with different resolution and accuracy on the uncertainties of soil erosion modelling in a part of the Narmada river basin in Madhya Pradesh in central India. Selected open-source DEMs are GTOPO30 (1 km), SRTM (30 and 90 m), CARTOSAT (30 m) and ASTER (30 m), used for estimating erosion rate. Results with better accuracy are achieved with the high-resolution DEMs (30 m) with higher vertical accuracy than the coarse resolution DEMs with lower accuracy. This study has presented potential uncertainties introduced by the open-source DEMs in soil erosion modelling for better understanding of appropriate selection and acceptable errors for researchers.     

Comparative evaluation of horizontal accuracy of elevations of selected ground control points from ASTER and SRTM DEM with respect to CARTOSAT-1 DEM: a case study of Shahjahanpur district,Uttar Pradesh,India

Digital elevation model (DEM) data of Shuttle Radar Topography Mission (SRTM) are distributed at a horizontal resolution of 90 m (30 m only for US) for the world, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) DEM data provide 30 m horizontal resolution, while CARTOSAT-1 (IRS-P5) gives 2.6 m horizontal resolution for global coverage. SRTM and ASTER data are available freely but 2.6 m CARTOSAT-1 data are costly. Hence, through this study, we found out a horizontal accuracy for selected ground control points (GCPs) from SRTM and ASTER with respect to CARTOSAT-1 DEM to implement this result (observed from horizontal accuracy) for those areas where the 2.6-m horizontal resolution data are not available. In addition to this, the present study helps in providing a benchmark against which the future DEM products (with horizontal resolution less than CARTOSAT-1) with respect to CARTOSAT-1 DEM can be evaluated. The original SRTM image contained voids that were represented digitally as ?140; such voids were initially filled using the measured values of elevation for obtaining accurate DEM. Horizontal accuracy analysis between SRTM- and ASTER-derived DEMs with respect to CARTOSAT-1 (IRS-P5) DEM allowed a qualitative assessment of the horizontal component of the error, and the appropriable statistical measures were used to estimate their horizontal accuracies. The horizontal accuracy for ASTER and SRTM DEM with respect to CARTOSAT-1 were evaluated using the root mean square error (RMSE) and relative root mean square error (R-RMSE). The results from this study revealed that the average RMSE of 20 selected GCPs was 2.17 for SRTM and 2.817 for ASTER, which are also validated using R-RMSE test which proves that SRTM data have good horizontal accuracy than ASTER with respect to CARTOSAT-1 because the average R-RMSE of 20 GCPs was 3.7 × 10^?4 and 5.3 × 10^?4 for SRTM and ASTER, respectively.     

Assessment of Dem Quality for Characterizing Surface Roughness Using Close Range Digital Photogrammetry

This paper presents a procedure for assessing the quality of a digital elevation model (DEM) which has been applied to the output of a normalized cross correlation based stereomatching algorithm. Using semimetric photography of natural gravel river bed surfaces acquired in the field, digital photogrammetry was used to extract DEMs automatically for use in characterizing surface roughness properties. The procedure for assessing DEM quality involves examination of (i) ortho-images, to provide a qualitative check on stereomatching performance; (ii) DEM collection statistics which quantify the percentage of correctly matched pixels as a function of those interpolated; and (iii) height differences between check points, measured using independent field survey, and corresponding DEM points. The concepts of precision, accuracy and reliability are defined in the context of DEM quality assessment and methods are outlined which can be used to assess these variables. The assessment is conducted for two adjacent stereopairs with similar characteristics, considering the effects of both DEM collection parameters and different lens models upon DEM quality. Results show that digital photogrammetry, in conjunction with independent field survey, can be used successfully for extracting high resolution, small scale DEMs from natural gravel surfaces. Components (i) and (ii) of the quality assessment suggest the need to optimize DEM collection parameters, although the effects of not using a properly specified lens model were minimal at this scale. Method (iii) showed that increasing stereomatching success does not necessarily lead to more accurately estimated DEM points. However, the use of method (iii) remained difficult because of the scale of the photogrammetric application being used; check point positioning within the photogrammetric co-ordinate system was only possible to ±10 mm which, for a gravel bed surface, was associated with elevation variance of a similar, sometimes greater, magnitude. The next stage of this research will require the use of higher quality check data, possibly from laser profiling.     

DEM Fusion using a modified k-means clustering algorithm

Digital elevation models (DEMs) are a necessary dataset for modelling the Earth’s surface; however, all DEMs contain error. Researchers can reduce this error using DEM fusion techniques since numerous DEMs can be available for a region. However, the use of a clustering algorithm in DEM fusion has not been previously reported. In this study a new DEM fusion algorithm based on a clustering approach that works on multiple DEMs to exploit consistency in the estimates as indicators of accuracy and precision is presented. The fusion approach includes slope and elevation thresholding, k-means clustering of the elevation estimates at each cell location, as well as filtering and smoothing of the fusion product. Corroboration of the input DEMs, and the products of each step of the fusion algorithm, with a higher accuracy reference DEM enabled a detailed analysis of the effectiveness of the DEM fusion algorithm. The main findings of the research were: the k-means clustering of the elevations reduced the precision which also impacted the overall accuracy of the estimates; the number of final cluster members and the standard deviation of elevations before clustering both had a strong relationship to the error in the k-means estimates.     

Accuracy assessment of airborne photogrammetrically derived high-resolution digital elevation models in a high mountain environment

High-resolution digital elevation models (DEMs) generated by airborne remote sensing are frequently used to analyze landform structures (monotemporal) and geomorphological processes (multitemporal) in remote areas or areas of extreme terrain. In order to assess and quantify such structures and processes it is necessary to know the absolute accuracy of the available DEMs. This study assesses the absolute vertical accuracy of DEMs generated by the High Resolution Stereo Camera-Airborne (HRSC-A), the Leica Airborne Digital Sensors 40/80 (ADS40 and ADS80) and the analogue camera system RC30. The study area is located in the Turtmann valley, Valais, Switzerland, a glacially and periglacially formed hanging valley stretching from 2400 m to 3300 m a.s.l. The photogrammetrically derived DEMs are evaluated against geodetic field measurements and an airborne laser scan (ALS). Traditional and robust global and local accuracy measurements are used to describe the vertical quality of the DEMs, which show a non Gaussian distribution of errors. The results show that all four sensor systems produce DEMs with similar accuracy despite their different setups and generations. The ADS40 and ADS80 (both with a ground sampling distance of 0.50 m) generate the most accurate DEMs in complex high mountain areas with a RMSE of 0.8 m and NMAD of 0.6 m They also show the highest accuracy relating to flying height (0.14‰). The pushbroom scanning system HRSC-A produces a RMSE of 1.03 m and a NMAD of 0.83 m (0.21‰ accuracy of the flying height and 10 times the ground sampling distance). The analogue camera system RC30 produces DEMs with a vertical accuracy of 1.30 m RMSE and 0.83 m NMAD (0.17‰ accuracy of the flying height and two times the ground sampling distance). It is also shown that the performance of the DEMs strongly depends on the inclination of the terrain. The RMSE of areas up to an inclination <40° is better than 1 m. In more inclined areas the error and outlier occurrence increase for all DEMs. This study shows the level of detail to which airborne stereoscopically derived DEMs can reliably be used in high mountain environments. All four sensor systems perform similarly in flat terrain.     

Improving Cartosat-1 DEM accuracy using synthetic stereo pair and triplet

Cartosat–1 is the first Indian Remote Sensing Satellite capable of providing along-track stereo images. Cartosat–1 provides forward stereo images with look angles +26° and −5° with respect to nadir for generating Digital Elevation Models (DEMs), Orthoimages and value added products for various applications. A pitch bias of −21° to the satellite resulted in giving reverse tilt mode stereo pair with look angles of +5° and −26° with respect to nadir. This paper compares DEMs generated using forward, reverse and other possible synthetic stereo pairs for two different types of topographies. Stereo triplet was used to generate DEM for Himalayan mountain topography to overcome the problem of occlusions.For flat to undulating topography it was shown that using Cartosat-1 synthetic stereo pair with look angles of −26° and +26° will produce improved version of DEM. Planimetric and height accuracy (Root Mean Square Error (RMSE)) of less than 2.5 m and 2.95 m respectively were obtained and qualitative analysis shows finer details in comparison with other DEMs. For rugged terrain and steep slopes of Himalayan mountain topography simple stereo pairs may not provide reliable accuracies in DEMs due to occlusions and shadows. Stereo triplet from Cartosat-1 was used to generate DEM for mountainous topography. This DEM shows better reconstruction of elevation model even at occluded region when compared with simple stereo pair based DEM. Planimetric and height accuracy (RMSE) of nearly 3 m were obtained and qualitative analysis shows reduction of outliers at occluded region.