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。     

低山丘陵区多源数字高程模型误差分析

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。     

利用ERS-1／2串接雷达干涉建立高山地区数字高程模型的实验研究

以昆仑山局部地区为例,利用ERS-1／2串接雷达干涉有效建立了高山地区数字高程模型,并以美国宇航局SRTM高程数据为标准,选取高相干系数点,采用多项式拟合法对实验生成的数字高程模型进行校正,得到实验区较高精度的数字高程模型。最后以SRTM高程数据和美国地质调查局GTOP030高程数据作为基准,对实验生成的数字高程模型的精度进行统计分析和评价,并分析了影响ERS-1／2干涉测量精度的主要因素。实验结果表明：采用ERS串接雷达干涉和基于多控制点的多项式拟合校正,可有效建立高山地区高精度的数字高程模型;在我国西部地区,建议采用ERS-1／2串接雷达干涉建立或更新数字高程模型。     

利用ERS-1/2串接雷达干涉建立高山地区数字高程模型的实验研究

以昆仑山局部地区为例,利用ERS-1/2串接雷达干涉有效建立了高山地区数字高程模型,并以美国宇航局SRTM高程数据为标准,选取高相干系数点,采用多项式拟合法对实验生成的数字高程模型进行校正,得到实验区较高精度的数字高程模型。最后以SRTM高程数据和美国地质调查局GTOPO30高程数据作为基准,对实验生成的数字高程模型的精度进行统计分析和评价,并分析了影响ERS-1/2干涉测量精度的主要因素。实验结果表明：采用ERS串接雷达干涉和基于多控制点的多项式拟合校正,可有效建立高山地区高精度的数字高程模型;在我国西部地区,建议采用ERS-1/2串接雷达干涉建立或更新数字高程模型。     

基于机载LiDAR的高寒山区遥感高程数据精度评估

遥感高程数据是获取缺资料地区DEM（Digital elevation models）数据的重要手段。然而,由于高寒山区实地高程测量稀少,难以对多源遥感DEM数据进行统一验证。ICESat-2等新的遥感高程数据在高寒山区也缺乏相应的精度评估。针对此问题,以青藏高原东北缘的冰沟流域作为研究区,采用机载航空遥感获取的大范围LiDAR（Light Detection And Ranging）DEM数据对新产品ICESat-2 ATL06（Ice, Cloud, and Land Elevation Satellite-2, Land Ice Height）、ALOS DEM（12.5 m分辨率）以及新版本SRTM V3（SRTM Arc-Second Global 1 V003）、ASTER GDEM V3（ASTER Global DEM）进行验证,并分析地形因子与均方根误差RMSE的关系。研究结果表明：ICESat-2 ATL06数据在高寒山区的RMSE为0.747 m。由于其较高的精度,可用于验证缺资料地区的其他遥感高程数据。其他遥感高程数据的精度都相对较低,ALOS 12.5 m数据的RMSE为5.284 m;ASTER GDEM V3版本的RMSE为9.903 m。实验所采用的4种遥感高程数据与机载LiDAR DEM均具有较高的相关性,相关系数在0.998与1.000之间。实验还揭示了坡度是影响遥感DEM精度的主要因素。除ICESat-2 ATL06外,其他高程数据的RMSE均随坡度的增大先减小再增大,且都存在一个最佳坡度值。鉴于地形复杂多样的冰沟流域具有青藏高原高寒山区的典型特征,多源遥感DEM数据在该区域的验证结论具有较好的代表性,可为相似地区DEM数据的使用和评估提供重要的知识补充。     

基于误差建模的SRTM高程精度提升方法研究

数字高程模型(DEM)是地理信息系统和遥感等领域所必需的核心数据,已经应用到很多方面。本文提出了一种利用ICESat GLA14数据优化SRTM1数据的方法。首先,根据SRTM误差分布去除GLA14数据中的粗差点,完成坐标基准和高程基准的统一。其次,分析了SRTM误差随坡度、坡向的变化规律,并建立了误差模型。最后,将GLA14数据随机划分为控制点和检查点,使用控制点采用最小二乘法拟合误差,使用检查点评价精度提升效果,并多次重复随机划分的过程,验证算法的有效性。实验结果表明:使用该算法针对不同地区不同地形的DEM进行了实验,均取得了很好的效果。     

基于地形图构建DEM模型的方法研究

在地质调查工作中,地质工作人员常利用掌握的地形图作为参考数据,结合地质调查项目需求,将地形图中的等高线数据进行提取,并通过研究区的数据验证了逐点插入算法构建数字高程模型的效率和精度,选择合适的精度建立了研究区的数字高程模型,实现在三维空间模拟真实地形地貌特征,使地质工作者可以更直观地认识分析区域的地形特征。     

基于SRTM的飞行模拟器三维地形生成技术

针对波音737-300全任务飞行模拟器中的地形无法满足国内拥有复杂地形特点机场的训练需求,提出了应用SRTM数字高程数据构建真实地形的方法,并针对sRTM数字高程数据中存在的数据空洞及大数据量的特点,分别提出了基于数据融合的克里金插值算法和基于改进四叉树的1OD地形简化方法,从而在提高原始SRTM数字高程数据精度的同时,也保证以此数据所构建出的地形能够满足飞行模拟器视景系统对实时性的要求。实验结果表明,利用该方法所构建出的地形能够真实地展现机场周边的复杂地形特征,同时,其渲染帧速率也证明了该地形能够满足系统对实时性的要求。     

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。     

建立数字地形模型的扫描方法

建立数字地形模型有两种方式:一种是将现有地形图数字化,使其成为以a×a平方米为基本单元的地面网格数字模型(数字高程模型、数字坡度模型等);另一种是从地面影像(如航空像片,SPOT卫星像片)直接获得数字地形模型。本文仅讨论第一种方式,即地形图数字化建立数字地形模型的方法。     

Vertical accuracy assessment of global digital elevation models and validation of gravity database heights in Niger

In this study, we assessed the vertical accuracy of ASTER GDEM (Advanced Space-borne Thermal Emission and Reflection Radiometer – Global Digital Elevation Model) version 2, AW3D30 (ALOS World 3D – 30m) and the 1 and 3 arc-seconds versions of SRTM (Shuttle Radar Topography Mission) in Niger Republic. We explored the GDEMs to evaluate large void and erroneous pixel areas. GDEMs were then compared to three kinds of ground control data located on several sites and all merged data after vertical datum matching. We also analysed the vertical accuracy by land cover and compared GDEMs to each other. We finally validated the gravity database heights by using the relatively most accurate GDEM. All GDEMs still contain void pixels except for SRTM3 CGIAR, it was then retained for the assessment with 1 arc-second GDEMs. The vertical accuracies in terms of RMS (Root Mean Square) and in m are: ASTER (6.2, 8.0, 9.8 and 9.2), AW3D30 (2.2, 2.1, 1.8 and 1.6), SRTM1 (3.8, 4.3, 2.5 and 2.9) and SRTM3 (3.7, 4.1, 2.4 and 2.7) compared to levelling data, local DEM of Imouraren, GPS (Global Positioning System) data and all merged data. Absolute height differences are less than 10 m at 74.00%, 99.99%, 99.91% and 99.98% for ASTER, AW3D30, SRTM1 and SRTM3, respectively. AW3D30 is the most accurate and ASTER is the least accurate. For all GDEMs, different accuracies were found depending on land cover classes that could be caused by the random spatial distribution of validation data. Small differences were observed between SRTM and AW3D30 and large values between the two models and ASTER similarly. The gravity database was validated using AW3D30, large values of height differences were found in the northern part in agreement with the database specifications and in the southern part indicating erroneous elevations.     

Spatial structure and landscape associations of SRTM error

This paper evaluates the spatial structure of Shuttle Radar Topography Mission (SRTM) error and its associations with globally available topographic and land cover variables across a wide range of landscapes. Two continental-scale SRTM elevation data samples were extracted, along with collocated National Elevation Dataset (NED) elevations, MODIS composite forest cover percentage, and global ecoregion major habitat type codes. The larger punctual sample contained nearly 247,000 sites on a regular grid across the conterminous United States, while the smaller areal sample consisted of 37,500 45″ × 45″ rectangular regions on a regular grid. Sub-pixel positional mismatch was accounted for by finding and using the best local fit between the 1 arc sec horizontal resolution NED product and the 3 arc sec (3″) horizontal resolution SRTM product. Slope and aspect were calculated for all samples. Using the larger point sample, we identified associations between SRTM error, defined as NED-SRTM 3″ differences, with these land cover and terrain derivative variables. Using the areal sample, we developed semivariograms of elevation error for tens of thousands of small regions across the United States, as well as for sets of these regions with common slope and landcover properties. This facilitated a more comprehensive evaluation of the spatial structure of SRTM error than has previously been done. The punctual sample RMSE was 8.6 m, conforming to previous estimates of SRTM error, but many errors in excess of 50 m were identified. Nearly 90% of these large errors were positive and correlated with high forest cover percentage. Overall, SRTM elevations consistently overestimated the surface. Forest cover and slope were positively correlated with positive bias. A strong association of aspect with SRTM error was noted, with positive error magnitudes peaking for aspects oriented to the northwest and negative error magnitudes peaking for slopes facing southeast. Error bias, standard deviation, and semivariograms differed substantially across ecoregion types. These variables were incorporated in a regression model to predict SRTM error: this model explained nearly 60% of the total error variation and has the potential to substantially improve the SRTM data product worldwide using globally available datasets.     

Accuracy assessment of the ASTER GDEM and SRTM3 DEM: an example in the Loess Plateau and North China Plain of China

The digital elevation model (DEM) produced by the Shuttle Radar Topographic Mission (SRTM) has provided important fundamental data for topographic analysis in many fields. The recently released global digital elevation model (GDEM) produced by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) has higher spatial resolution and wider coverage than the SRTM3 DEM, and thus may be of more value to researchers. Taking two typical study areas—the Loess Plateau and the North China Plain of China—as an example, this article assesses the accuracy of the SRTM3 DEM and ASTER GDEM by collecting ground control points from topographical maps. It is found that both the SRTM3 DEM and the ASTER GDEM are far more accurate for the North China Plain than for the Loess Plateau. For the Loess Plateau, the accuracy of the ASTER GDEM is similar to that of the SRTM3 DEM; whereas for the North China Plain, it is much worse than that of the SRTM3 DEM. Considering the negative bias of the ASTER GDEM for flat or gentle regions, we improve its accuracy by adding the difference of the mean value between the SRTM3 DEM and ASTER GDEM for the North China Plain; then, the root mean square error (RMSE) of ±7.95 m from the original ASTER GDEM is improved to ±5.26 m, which demonstrates that it is a simple but useful way to improve the accuracy of the ASTER GDEM in flat or gentle regions.     

SRTM vs ASTER elevation products. Comparison for two regions in Crete,Greece

The Shuttle Radar Topography Mission (SRTM) collected elevation data over 80% of earth's land area during an 11‐day Space Shuttle mission. With a horizontal resolution of 3 arc sec, SRTM represents the best quality, freely available digital elevation models (DEMs) worldwide. Since the SRTM elevation data are unedited, they contain occasional voids, or gaps, where the terrain lay in the radar beam's shadow or in areas of extremely low radar backscatter, such as sea, dams, lakes and virtually any water‐covered surface. In contrast to the short duration of the SRTM mission, the ongoing Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is continuously collecting elevation information with a horizontal resolution of 15 m. In this paper we compared DEM products created from SRTM data with respective products created from ASTER stereo‐pairs. The study areas were located in Crete, Greece. Absolute DEMs produced photogrammetricaly from ASTER using differentially corrected GPS measurements provided the benchmark to infer vertical and planimetric accuracy of the 3 arc sec finished SRTM product. Spatial filters were used to detect and remove the voids, as well as to interpolate the missing values in DEMs. Comparison between SRTM‐ and ASTER‐derived DEMs allowed a qualitative assessment of the horizontal and vertical component of the error, while statistical measures were used to estimate their vertical accuracy. Elevation difference between SRTM and ASTER products was evaluated using the root mean square error (RMSE), which was found to be less than 50 m.     

The impact of misregistration on SRTM and DEM image differences

Image differences between Shuttle Radar Topography Mission (SRTM) data and other Digital Elevation Models (DEMs) are often performed for either accuracy assessment or for estimating vegetation height across the landscape. It has been widely assumed that the effect of sub-pixel misregistration between the two models on resultant image differences is negligible, yet this has not previously been tested in detail. The aim of this study was to determine the impact that various levels of misregistration have on image differences between SRTM and DEMs. First, very accurate image co-registration was performed at two study sites between higher resolution DEMs and SRTM data, and then image differences (SRTM–DEM) were performed after various levels of misregistration were systematically introduced into the SRTM data. It was found that: (1) misregistration caused an erroneous and dominant correlation between elevation difference and aspect across the landscape; (2) the direction of the misregistration defined the direction of this erroneous and systematic elevation difference; (3) for sub-pixel misregistration the error due solely to misregistration was greater than, or equal to the true difference between the two models for substantial proportions of the landscape (e.g., greater than 33% of the area for a half-pixel misregistration); and (4) the strength of the erroneous relationship with aspect was enhanced by steeper terrain. Spatial comparisons of DEMs were found to be sensitive to even sub-pixel misregistration between the two models, which resulted in a strong erroneous correlation with aspect. This misregistration induced correlation with aspect is not likely specific to SRTM data only; we expect it to be a generic relationship present in any DEM image difference analysis.     

Evaluation of TanDEM-X 90 m Digital Elevation Model

German Aerospace Center (DLR), EADS Astrium GmbH and Infoterra GmbH alliance came up with the idea of taking DTED-2 (Digital terrain elevation data, level-2) specifications to even higher standard of HRTE-3 (High resolution terrain elevation, level-3) in 2006, as a result TDX (TerraSAR-X, TanDEM-X) constellation was born. The mission was geared to create a rather sensitive, high precision 3 dimensional map of the entire Earth in seamless and very high quality. After Shuttle Radar Topography Mission (SRTM) in 2000 and its derivatives, along with numerous prior and subsequent other similar data, have practically set the standard for defining the topographical surfaces in global scale, the twin satellites acquired all of Earth’s land surfaces numerous times to produce varying resolution digital elevation models (DEM) between 2011 and late 2015. DEMs are widely used in many planning, decision making and engineering related projects. They provide sound backing for mankind’s endeavors. Ground resolution is the most sought after feature of any DEM. Finer resolution is usually associated with a better surface definition. Recently, an entirely new global DEM has been released DLR. The 90 m DEM is the latest variant derived from such an undertaking. This study aimed to examine the overall effectiveness of this alleged new data in four previously surveyed locations and against the performances of finer SRTM 1- and comparable SRTM 3 arc second data. The results showed that TanDEM-X 90 m data overestimated. They seemed to be rather accurate in flat to slightly undulating terrain, but overestimated in broken to treacherous terrain than both SRTMs. Root Mean Square Error was greater in site one and site four, and lower in site two and site three compared to both SRTM 1 and SRTM 3 arc second data.     

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.     

航天飞机雷达测图计划大块区域无效数据填补方法

在总结国内外对SRTM无效数据填补方法的基础上,针对直接用低精度的GTOPO30数据进行镶嵌填充SRTM无效数据会产生边界不光滑,细节表现不好的问题,采用Laplacian迭代修复算法。该算法是经典的基于偏微分方程(PDE)的图像修复算法。实例对比验证表明,该方法在对SRTM大块无效数据填补效果上明显好于用GTOPO30数据直接填补的效果,是获取完整SRTM数据的有效方法之一。     

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.