粗／精轨道数据对卫星InSAR DEM精度影响的对比分析

本文在介绍InSAR系统中卫星轨道状态矢量内插方法的基础上，从理论和实际两方面分析了轨道数据误差对参考椭球面相位、地形干涉相位和数字高程模型（DEM）精度的影响。以上海局部地区作为实验场，采用ERS-1／2卫星SAR影像数据，分别使用欧洲空间局粗略轨道数据和荷兰Delft大学空间研究中心精密轨道数据进行了干涉处理，生成了两种情况下的DEM，并对相关精度进行了对比与分析。研究结果表明，使用精轨数据建立的DEM的精度明显高于基于粗轨数据建立的DEM的精度。     

以Doris进行雷达干涉研究生成数字高程模型(DEM)

雷达干涉测量技术(InSAR)被认为是生成或更新DEM的有效方法,通过实地测量得到DEM精度虽高但成本高也费时,近年来,InSAR以其全天候、全天时、快速得到DEM而引起全世界地学人员的关注。但是由于处理过程复杂及条件要求严格,目前除购买高价的商业软件外,一般的研究人员很难投入到该项技术的研究与应用中去。本研究利用以荷兰Delft大学为主所研发的开源软件Doris来进行雷达影像生成DEM的研究。该软件是一套功能强大的干涉影像生成软件,作者详细介绍用Doris进行干涉处理过程并提取库赛湖区域DEM,最后对DEM精度做了对比分析。     

InSAR平地相位去除算法及其对DEM精度影响研究

准确有效去除干涉纹图中的平地相位是精确莺建DEM的关键.探讨了两类常见的去平地相位方法(基于地理定位和基于干涉频谱),分析了其所引起的误差影响.通过Envis砒和JERS-1两种数据的验证结果表明:在可获取精密轨道数据的情况下,基于地理定位的去平地方法能够有效去除干涉纹图中所包含的平地相位,并很好地控制最终所得的DEM误差,其效果优于基于干涉频谱的去平方法;基于干涉频谱的去平方法在干涉频谱平均空间频率为0时,所引起的DEM误差相对较小;在精密轨道数据缺乏的情况下,两种方法均不能满足重建DEM精度要求.     

卫星轨道和大气延迟误差联合校正的山地DEM提取

针对轨道误差和大气延迟误差是制约ALOS PALSAR数据快速获取大面积及高精度数字高程模型的主要因素这一问题,该文提出一种基于埃尔米特(Hermite)插值和高程大气模型对两种误差进行联合矫正的方法。首先,采用埃尔米特插值法对轨道矢量数据进行插值,以提高去除平地效应的效果;然后,建立高程与相位之间的线性模型,去除与高程相关的大气延迟误差;最后,进行相位高程转换得到数字高程模型。利用陕西省彬县地区的两景ALOS PALSAR数据进行实验分析。结果表明,该方法获取的数字高程模型以航天飞机雷达地形测绘使命为参考的均方根误差为14.48m,比常规干涉方法获取的结果有很大的提高,证明了该方法的有效性。     

InSAR提取DEM的原理与实践

介绍合成孔径雷达干涉测量的原理和DEM获取流程。基于Linux操作系统,利用Gamma软件处理平台,对上海某地区ERS-1／2卫星影像数据进行处理,成功提取高精度的数字高程模型。     

利用升降轨道SAR数据获取DEM的试验研究

首先介绍了利用InSAR技术提取DEM的原理及方法,其次对利用ENVISAT卫星的升轨SAR数据和降轨SAR数据获取DEM,然后对其融合,并将融合前后的DEM与SRTM3 DEM进行比较,分析其精度。结果表明,与单独利用升轨SAR数据或降轨SAR数据获取的DEM相比,融合后的DEM能更好地显示地形起伏特征,高程精度得到明显提升,且羽化融合后的DEM精度最高,其与参考DEM─SRTM3 DEM高程差异标准差为±7.25,高程差异绝对值小于15 m的地区占95.48%。     

ZY-3卫星异轨立体影像DSM提取精度分析

为充分发掘以ZY-3为代表的国产测绘卫星的效能,本文提出了由不同轨道的前视、后视相机影像构建异轨立体的测绘模式,选取该卫星在不同轨道分别侧摆3.9°和0°成像获取的河南嵩山同一地区三线阵影像,比较了常规同轨立体和本文异轨立体构建方式下的传感器校正级(SC)影像几何定位精度及数字表面模型(DSM)提取精度。试验结果显示,由于基高比条件良好,异轨立体构建方式能够达到与同轨立体相似的几何定位精度,自动提取的异轨DSM与同轨DSM高程精度基本一致。     

地面三维激光扫描数据的DEM重建精度分析

提出将地面三维激光扫描技术获取的地表点云数据,实现数字高程模型(DEM)表面的重建,并从数据误差和建模误差两个方面对DEM重建的精度进行分析,提出了改进精度的方法。     

干涉雷达在DEM测量中的精度影响及处理方法

干涉合成孔径雷达 (INSAR)为数字高程模型 (DEM)测量提供了一种新的手段。它具有同时获取三维信息、测量范围广、空间和高程分辨率高等优点。文中首先扼要介绍了干涉雷达的原理 ,然后重点讨论几个影响测量精度的因素及其处理方法 ,如相关、运动补偿、配准、相位展开等。     

InSAR技术高植被覆盖区DEM重建及精度分析

合成孔径雷达干涉测量(InSAR)技术是大区域数字高程模型数据获取的重要手段之一,本文介绍了In-SAR技术在高植被覆盖区DEM重建的技术原理及流程,阐述了干涉相位点与实测目标点映射关系,通过实验获取柬埔寨某公路项目全程的DEM,辅助融合GLAS星载激光测高数据与实测GNSS数据进行比较、分析,验证了方法的高效性与正确性。     

Evaluation of digital elevation models for delineation of hydrological response units in a Himalayan watershed

This study reports results from evaluation of the quality of digital elevation model (DEM) from four sources viz. topographic map (1:50,000), Shuttle Radar Topographic Mission (SRTM) (90 m), optical stereo pair from ASTER (15 m) and CARTOSAT (2.5 m) and their use in derivation of hydrological response units (HRUs) in Sitla Rao watershed (North India). The HRUs were derived using water storage capacity and slope to produce surface runoff zones. The DEMs were evaluated on elevation accuracy and representation of morphometric features. The DEM derived from optical stereo pairs (ASTER and CARTOSAT) provided higher vertical accuracies than the SRTM and topographic map-based DEM. The SRTM with a coarse resolution of 90 m provided vertical accuracy but better morphometry compared to topographic map. The HRU maps derived from the fine resolution DEM (ASTER and CARTOSAT) were more detailed but did not provide much advantage for hydrological studies at the scale of Sitla Rao watershed (5800 ha).     

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.     

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.     

Evaluation of vertical accuracy of open source Digital Elevation Model (DEM)

Digital Elevation Model (DEM) is a quantitative representation of terrain and is important for Earth science and hydrological applications. DEM can be generated using photogrammetry, interferometry, ground and laser surveying and other techniques. Some of the DEMs such as ASTER, SRTM, and GTOPO 30 are freely available open source products. Each DEM contains intrinsic errors due to primary data acquisition technology and processing methodology in relation with a particular terrain and land cover type. The accuracy of these datasets is often unknown and is non-uniform within each dataset. In this study we evaluate open source DEMs (ASTER and SRTM) and their derived attributes using high postings Cartosat DEM and Survey of India (SOI) height information. It was found that representation of terrain characteristics is affected in the coarse postings DEM. The overall vertical accuracy shows RMS error of 12.62 m and 17.76 m for ASTER and SRTM DEM respectively, when compared with Cartosat DEM. The slope and drainage network delineation are also violated. The terrain morphology strongly influences the DEM accuracy. These results can be highly useful for researchers using such products in various modeling exercises.     

海岛礁卫星影像无地面控制点定位方法

针对海岛礁卫星影像的定位问题，提出一种利用航天飞机雷达地形测绘任务（shuttle radar topography mission，SRTM）DEM辅助的无地面控制点定位方法。该方法分为概略定位和精定位两个阶段，各阶段均包括DEM提取和DEM匹配等主要步骤，可分别对影像中的相对误差和绝对误差进行补偿。SRTM DEM被充分应用到方法各环节中，以发挥其高精度的特性:提取DEM时既用于剔除海域点，也用于确定求解陆域点高程时的高程搜索范围，从而避免海域影像的不利影响，同时保证计算效率；DEM匹配时其作为基准数据。利用多景天绘一号卫星海岛礁地区的立体影像进行验证。实验结果表明，所提出的方法对具有不同陆域比例、不同生产方式的天绘一号海岛礁影像均能得到较稳定且较高的定位精度，平面和高程精度分别优于6.2 m、5.2 m，能较好地满足1:50 000比例尺地形图的精度要求。定位精度基本不受待匹配DEM分辨率的影响，计算效率取决于陆域比例和待匹配DEM的分辨率。     

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.     

基于ICESat-2 ATLAS数据的DEM高程精度评价

为探究ASTER GDEMV3、SRTM1 DEM和AW3D30 DEM 3种开源DEM数据的高程精度,本文以高精度ICESat-2 ATLAS测高数据为参考数据,利用GIS统计分析、误差相关分析及数理统计对DEM的高程精度进行对比评价。结果表明：①AW3D30的质量最稳定;SRTM1 DEM在平原精度最高;在高原山地精度由高到低依次为AW3D30 DEM、ASTER GDEMV3、SRTM1 DEM。②DEM数据高程精度受地表覆盖影响较大,且与地形因素密切相关,在相同地表覆盖的两个研究区中DEM数据高程精度表现情况不一致,SRTM在平原地表覆盖下精度表现最好,平均误差为3.15 m,AW3D30 DEM在山地地表覆盖下精度表现最好,平均误差为7.61 m。③坡度对DEM数据的高程精度影响较大,在两个研究区3种DEM数据的高程误差均随坡度的增加而增加;坡向对DEM数据的高程精度影响较小,未发现明显的规律。     

国产资源三号测绘卫星DSM数据质量评价--以高海拔山区为例

为了评价国产资源三号测绘卫星DSM数据精度,在顾及地貌类型的情况下,以涵盖平原、台地、丘陵等地貌的高海拔山区为研究案例,并以1∶1万实测地形图DEM为假定真值,以90m分辨率SRTM DEM为评价参照,从高程精度和地形描述精度两个方面,对15m分辨率ZY-3DSM进行精度评价分析。研究结果表明:ZY-3DSM高程精度优于SRTM DEM,前者高程中误差仅为后者的1/6;就地形描述精度来讲,ZY-3DSM与SRTM DEM相比,其地形描述精度更接近理论值,前者RMS Et实际值仅为理论值0.99倍,而后者的实际值却是理论值5.13倍。由此看来,ZY-3DSM数据精度整体上高于SRTM DEM。     

基于SWBD修复的SRTM DEM的1∶250000水系自动更新——以浙江省瓯江流域为例

以浙江省瓯江流域为例,基于SWBD修复的SRTM DEM数据,采用Arc Hydro Tools水文分析工具自动提取瓯江水系,并分地貌、分河流等级地定量评价水系数据精度,开展1∶250 000水系自动更新的可行性研究。结果表明：①SWBD修复的SRTM DEM的空白区域面积为54.78 km2,有效地弥补了SRTM DEM的数据缺失,进而提高了水系提取的准确度和精度;②与1∶250 000水系数据相比,基于SWBD修复后的SRTM DEM,在小起伏山、中起伏低山、低海拔丘陵上提取的水系数据精度高于其他地貌,而干流、一级支流、二级支流的精度又高于三级支流;③以资源三号卫星ZY-3遥感影像为参照,从水系上采集同名点反复比较点位精度后发现,利用SRTM DEM提取的水系符合制图规范和测绘内业规范（限差1 mm）,可以满足1∶250 000水系自动更新的要求。