ASTER立体影像提取DEM的研究

介绍了具有同轨立体测图能力的ASTER传感器观测系统,及其立体影像生成DEM的算法和DEM的编辑方法,展示了ASTER立体影像生产DEM的实验结果,并以试验结果说明,其精度可以满足绘制1：100000～1：250000比例尺地形图要求。     

用地面立体摄影测量测绘1∶500比例尺地形图的精度检测

施测大比例尺地形图时，采用地面立体摄影方法，有很多优越性。为了更进一步了解各类地区地面立体摄影测量的成图精度情况，我队在施测某水库溢洪道1:500比例尺地形图过程中，在同一测区范围内，以同一比例尺，采用平板仪测图和地面立体摄影测量两种不同的成图方法分别成图，进行了精度测验。     

合成孔径雷达测图技术在西部测图中的应用

合成孔径雷达遥感作为一种新的对地观测技术手段,在西部测图中有效地解决了光学影像在困难地区因云雾、冰雪、阴影等遮蔽所产生的地形要素缺失问题。结合雷达影像立体测图的生产实践,介绍雷达影像在横断山脉区域地形测图的实际应用,重点阐述基于雷达影像的测图方法及工艺。     

使用SAR影像生成DEM的精度分析

雷达干涉测量(InSAR)和雷达立体测量(Radargrammetry)是使用SAR影像生成DEM的两种主动遥感新技术,前者利用反射雷达波的相位信息,而后者利用其灰度信息。本文利用ERS-1/2卫星对香港地区成像获取的SAR影像分别构成干涉像对和立体像对生成了DEM,并以外部DEM为参考,利用对比和统计方法分析了两种测量方法的精度情况和技术优势。     

一种利用影像模拟制作SAR立体模型的方法

针对SAR数字立体测图,提出了一种SAR理想立体模型的构建方法。利用西部横断山脉地区的机载SAR影像制作立体模型,进行数字测图试验。试验证明模型具有良好的立体视觉效果,同时能够用于高精度三维坐标的实时量测和地形图要素采集。     

基于多源数据的大比例尺地形图更新模式研究

为了克服传统地形图修测更新模式中存在的效率低下、数据获取困难等诸多现实问题,在地理信息产业数据高度融合的背景下,综合应用低空遥感、机载LiDAR以及移动车载激光测量等先进测绘技术进行大比例尺地形图修测更新。在数据获取、数据处理等方面较传统地形图修测更新模式的效率有较大提升,将测图工作从“外”搬到“内”,通过融合多种数据获取手段构建立体地形图绘制环境。将设计的多种数据融合的地形图更新模式应用于具体项目中,试验结果表明该作业模式绘制地形图精度满足规范要求。本文设计的大比例尺地形图修测更新作业模式可为测绘先进技术的推广与应用提供借鉴。     

基于粗DEM的立体SAR像对配准

影像配准是雷达立体摄影测量技术获取数字高程模型的一个关键步骤,也是一大难点。为了能够自动而又稳健地获取高精度的立体SAR像对配准结果,文中设计一种基于粗DEM、距离多普勒SAR构像模型和基于区域逐级窗口的立体SAR像对配准方法。该方法采用距离多普勒SAR成像模型和粗DEM获取像素级的粗略配准结果。在此基础上,采用基于区域的逐级窗口配准方法获取高精度的配准结果。文中最后利用立体SAR像对进行实验研究。实验结果表明,设计的立体像对配准方法可行,其配准精度可以达到子像素级,距离向为0.3像素左右,方位向为0.1像素左右,完全能够满足雷达立体测图的要求,而且该方法还具有很好的稳健性。     

基于WordView数据的西藏桑德地区快速制图方法

对WordView-2高分辨率卫星数据不同视角的立体像对运用不同方法进行点云和DEM制作,发现运用INPHO软件所生成的点云数据的高程误差最小,且符合测图精度。通过本次快速制图过程,形成了适用于卫片的快速制图流程。与传统的立体测图方法相比,不仅成本低,而且工期短,为以后的快速测图工作提供了依据,为测绘、国土、水利、环境等行业的快速地形图需求提供了可能。     

国产机载微型InSAR系统的DEM精度分析

针对我国一些多云、多雨地区光学影像获取困难,且国内机载InSAR系统获取DEM精度普遍较低的问题,该文以国产机载微型InSAR系统为依托,首先,对InSAR原理和DEM获取流程进行了分析,着重对运动补偿和基线估计方法进行了归纳分析;其次,使用实验数据对国产机载微型InSAR系统的高程精度进行了验证分析,检查点高程中误差为0.44m,结果表明使用国产机载微型InSAR系统可以获取高精度DEM数据,满足我国测量规范对于丘陵地区1∶5 000成图比例尺地形图的要求;最后,为了进一步提高国产微型InSAR系统的测量精度,对控制点位置、定标器、DEM局部编辑等方面提出了建议。     

地面控制困难地区IMU/DGPS辅助的航空摄影测量测图技术研究

针对自然条件恶劣、地面控制测量工作困难的情况,本文主要探讨利用IMU/DGPS辅助稀少控制区域网平差,以及全自动/半自动DEM/DOM生成、基于图幅的立体测图等试验,研究1∶50 000地形图生产的新工艺。     

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.     

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.     

顾及地形坡度的SRTM和ASTER加权融合

为了克服现有SRTM和ASTER各自缺陷，提升公共DEM精度，本文提出了一种顾及地形坡度的SRTM和ASTER加权融合方法。首先对两种DEM进行地理配准；然后计算不同坡度等级下SRTM和ASTER的高程误差，并得到DEM融合权重；最后采用加权平均法对SRTM和ASTER进行融合。高精度控制点的检验表明：融合后DEM精度有明显提高，相比于原始SRTM和ASTER高程误差，标准差分别降低了5.65 m和1.20 m。     

基于CryoSat-2测高数据的南极局部地区DEM的建立与精度评定

南极数字高程模型(DEM)是南极冰盖变化研究的基础数据,在我国南极重点考察地区Dome A及中山站至Dome A考察断面,利用新一代测高卫星CryoSat-2,对常用的几种插值方法如反距离加权、克里金、径向基函数、局部多项式和最近邻点插值方法的插值精度进行交叉比较,结果显示克里金插值方法的精度最高。利用中国第21次南极科学考察队采集的GPS数据,对克里金插值方法生成的两个区域的DEM精度进行验证。结果表明,坡度较小的Dome A区域DEM精度较高,平均高差为1.248 m,标准差为0.51 m;坡度较大的中山站至Dome A断面区域DEM精度较低,平均高程差达到3.87 m,标准差为9.358 m。     

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.     

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.     

A practical method for SRTM DEM correction over vegetated mountain areas

Digital elevation models (DEMs) are essential to various applications in topography, geomorphology, hydrology, and ecology. The Shuttle Radar Topographic Mission (SRTM) DEM data set is one of the most complete and most widely used DEM data sets; it provides accurate information on elevations over bare land areas. However, the accuracy of SRTM data over vegetated mountain areas is relatively low as a result of the high relief and the penetration limitation of the C-band used for obtaining global DEM products. The objective of this study is to assess the performance of SRTM DEMs and correct them over vegetated mountain areas with small-footprint airborne Light Detection and Ranging (Lidar) data, which can develop elevation products and vegetation products [e.g., vegetation height, Leaf Area Index (LAI)] of high accuracy. The assessing results show that SRTM elevations are systematically higher than those of the actual land surfaces over vegetated mountain areas. The mean difference between SRTM DEM and Lidar DEM increases with vegetation height, whereas the standard deviation of the difference increases with slope. To improve the accuracy of SRTM DEM over vegetated mountain areas, a regression model between the SRTM elevation bias and vegetation height, LAI, and slope was developed based on one control site. Without changing any coefficients, this model was proved to be applicable in all the nine study sites, which have various topography and vegetation conditions. The mean bias of the corrected SRTM DEM at the nine study sites using this model (absolute value) is 89% smaller than that of the original SRTM DEM, and the standard deviation of the corrected SRTM elevation bias is 11% smaller.     

Vertical accuracy assessment of freely available digital elevation models over low-lying coastal plains

The frequency of coastal flood damages is expected to increase significantly during the twenty-first century as sea level rises in the coastal floodplain. Coastal digital elevation model (DEM) data describing coastal topography are essential for assessing future flood-related damages and understanding the impacts of sea-level rise. The Shuttle Radar Topography Mission (SRTM) and Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) are currently the most accurate and freely available DEM data. However, an accuracy assessment specifically targeted at DEMs over low elevation coastal plains is lacking. The present study focuses on these areas to assess the vertical accuracy of SRTM and ASTER GDEM using Ice, Cloud, and land Elevation Satellite, Geoscience Laser Altimeter System (ICESat/GLAS) and Real Time Kinematic (RTK) Global Positioning System (GPS) field survey data. The findings show that DEM accuracy is much better than the mission specifications over coastal plains. In addition, optical remote sensing image analysis further reveals the relationship between DEM vertical accuracy and land cover in these areas. This study provides a systematic approach to assess the accuracy of DEMs in coastal zones, and the results highlight the limitations and potential of these DEMs in coastal applications.     

Spheroidal equal angular DEMs: The specificity of morphometric treatment

Digital elevation models (DEMs) are commonly constructed using two main types of regular grids: plane square grids and spheroidal equal angular grids. Methods and algorithms intended for plane square‐gridded DEMs should not be directly applied to spheroidal equal angular DEMs. This is because these grids have fundamentally different geometry. However, some researchers continue to apply square‐grid algorithms to spheroidal equal angular DEMs. It seems appropriate to consider once again the specifity of morphometric treatment of spheroidal equal angular DEMs. This article, first, demonstrates possibilities of direct calculation of local, nonlocal, and combined morphometric variables from spheroidal equal angular DEMs exemplified by slope gradient, catchment area, and topographic index. Second, the article shows computational errors when algorithms for plane square‐gridded DEMs are unreasonably applied to spheroidal equal angular DEMs. The study is exemplified by two DEMs. A medium‐resolution DEM of a relatively small, high‐mountainous area (Mount Elbrus) was extracted from the SRTM1 DEM. A low‐resolution DEM of a vast region with the diverse topography (the central and western regions of Kenya) was extracted from the SRTM30_PLUS DEM. The results show that application of square‐grid methods to spheroidal equal angular DEMs leads to substantial computational errors in models of morphometric variables.