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.     

Vertical accuracy evaluation of freely available latest high-resolution (30 m) global digital elevation models over Cameroon (Central Africa) with GPS/leveling ground control points.

Digital Elevation Models (DEMs) contain topographic relief data that are vital for many geoscience applications. This study relies on the vertical accuracy of publicly available latest high-resolution (30?m) global DEMs over Cameroon. These models are (1) the ALOS World 3D-30?m (AW3D30), (2) the Shuttle Radar Topography Mission 1 Arc-Second C-Band Global DEM (SRTM 1) and (3) the Advanced Spaceborne Thermal Emission and Reflection Global DEM Version 2 (ASTER GDEM 2). After matching their coordinate systems and datums, the horizontal positional accuracy evaluation was carried out and it shows that geolocation errors significantly influence the vertical accuracy of global DEMs. After this, the three models are compared among them, in order to access random and systematic effects in the elevation data each of them contains. Further, heights from 555 GPS/leveling points distributed all over Cameroon are compared to each DEM, for their vertical accuracy determination. Traditional and robust statistical measures, normality test, outlier detection and removal were used to describe the vertical quality of the DEMs. The test of the normality rejected the hypothesis of normal distribution for all tested global DEMs. Overall vertical accuracies obtained for the three models after georeferencing and gross error removal in terms of Root Mean Square (RMS) and Normalized Median Absolute Deviation (NMAD) are: AW3D30 (13.06?m and 7.75?m), SRTM 1 (13.25?m and 7.41?m) and ASTER GDEM 2 (18.87?m and 13.30?m). Other accuracy measures (MED, 68.3% quantile, 95% quantile) supply some evidence of the good quality of AW3D30 over Cameroon. Further, the effect of land cover and slope on DEM vertical accuracy was also analyzed. All models have proved to be worse in the areas dominated by forests and shrubs areas. SRTM 1 and AW3D30 are more resilient to the effects of the scattering objects respectively in forests and cultivated areas. The dependency of DEMs accuracy on the terrain roughness is evident. In all slope intervals, AW3D30 is performing better than SRTM 1 and ASTER GDEM 2 over Cameroon. AW3D30 is more representative of the external topography over Cameroon in comparison with two others datasets and SRTM 1 can be a serious alternative to AW3D30 for a range of DEM applications in Cameroon.     

ASTER GDEM与SRTM3高程差异影响因素分析

作为最新发布的全球地形数据,ASTER GDEM比目前常用的SRTM3数据有着更高的分辨率和更广的覆盖范围,对于相关地学分析具有重要意义。本文以华中地区为研究区域,对ASTER GDEM与SRTM3数据进行了比较,重点分析了坡度、坡向、地形起伏度、土地利用类型、植被覆盖度、生成ASTER GDEM栅格点高程数据所用的ASTER DEM影像数等因素对2种DEM数据高程差异的影响。结果表明,在研究区域内,ASTER GDEM高程比SRTM3高程平均低5.42 m,两种DEM数据高程差异的RMS值为16.90 m;ASTER GDEM与SRTM3之间的高程差异随着坡度、地形起伏度、植被覆盖度的增大而增大,而ASTER DEM影像数越大,高程差异越小;坡向、土地利用类型对高程差异也有影响。     

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。     

Creating high-resolution bare-earth digital elevation models (DEMs) from stereo imagery in an area of densely vegetated deciduous forest using combinations of procedures designed for lidar point cloud filtering

For areas of the world that do not have access to lidar, fine-scale digital elevation models (DEMs) can be photogrammetrically created using globally available high-spatial resolution stereo satellite imagery. The resultant DEM is best termed a digital surface model (DSM) because it includes heights of surface features. In densely vegetated conditions, this inclusion can limit its usefulness in applications requiring a bare-earth DEM. This study explores the use of techniques designed for filtering lidar point clouds to mitigate the elevation artifacts caused by above ground features, within the context of a case study of Prince William Forest Park, Virginia, USA. The influences of land cover and leaf-on vs. leaf-off conditions are investigated, and the accuracy of the raw photogrammetric DSM extracted from leaf-on imagery was between that of a lidar bare-earth DEM and the Shuttle Radar Topography Mission DEM. Although the filtered leaf-on photogrammetric DEM retains some artifacts of the vegetation canopy and may not be useful for some applications, filtering procedures significantly improved the accuracy of the modeled terrain. The accuracy of the DSM extracted in leaf-off conditions was comparable in most areas to the lidar bare-earth DEM and filtering procedures resulted in accuracy comparable of that to the lidar DEM.     

利用弹性反馈神经网络融合ASTER GDEM和SRTM1高程数据

由于数据获取与后期处理方式不同,先进星载热发射和反射辐射仪全球数字高程模型(advanced spaceborne thermalemissionandreflectionradiometerglobaldigitalelevationmodel,ASTERGDEM)和航天飞机雷达地形测绘任务(shuttle radar topography mission,SRTM)数据在高程精度上存在差异,采用弹性反馈（resilient backpropagation,RProp）神经网络算法对二者进行融合处理,实现优势互补以提升高程精度。选取两个黄土丘陵沟壑地貌样区分别用于模型建立与效果验证,1∶10 000高程精度为参考数据,在建模样区应用RProp神经网络算法构建ASTER GDEM高程校正模型、SRTM1高程校正模型、ASTER GDEM与SRTM1高程融合模型,同时应用误差反向传播(back propagation,BP)神经网络建立ASTER GDEM与SRTM1高程融合模型,将这些模型的高程精度优化效果进行对比,并在验证样区检验RProp融合模型的可行性。结果表明,RProp融合模...     

多源DEM融合的高差拟合神经网络方法

本文侧重于介绍智能化摄影测量机器学习的高差拟合神经网络方法。观测手段和处理方式等限制导致全球高质量无缝DEM数据的缺乏,进而制约了它在水文、地质、气象及军事等领域的应用。本文提出了一种基于高差拟合神经网络的多源DEM融合方法,尝试融合全球DEM产品SRTM1、ASTER GDEM v2和激光雷达测高数据ICESat GLAS。首先,根据ICESat GLAS的相关参数及与DEM数据的高程差值,结合坡度自适应的思想设置高差阈值对ICESat GLAS进行滤波,剔除异常数据点。然后,以ICESat GLAS数据为控制点,利用神经网络模型拟合ASTER GDEM v2的误差分布。以地形坡度信息和经纬度坐标作为网络输入,ICESat GLAS和ASTER GDEM v2的高程差值作为目标输出,训练得到预测高差,将其与ASTER GDEM v2高程值相加即可获得校正结果。最后,引入TIN差分曲面的方法,利用校正后的ASTER GDEM v2高程值对SRTM1的数据空洞进行填充,融合生成空间无缝DEM。本文通过随机选取数据进行真实试验,对模型进行了精度验证,并给出了处理结果的定量评价和目视效果。结果表明,不论是空洞还是整体区域,本文方法相比其他DEM数据集和其他方法的处理结果都能够在RMSE上表现出优势,同时,本文提出的方法能够有效克服ASTER GDEM中异常值的影响,得到空间无缝DEM。     

中国地区SRTM3 DEM高程精度质量评价

为揭示我国SRTM3DEM数据高程精度质量,结合已开展过SRTM3DEM高程精度质量评价工作的局部地区的研究,考虑空间分布情况,选取新疆、辽宁、山东、浙江、海南5个地区的平原、丘陵、盆地、山地等地形区域作为典型研究区,并以1∶5万DEM为假定真值、以1∶25万DEM为参照,通过DEM面误差可视化分析、DEM面误差信息熵模型、中误差模型等方法对SRTM3DEM数据高程精度质量做了分析。计算结果表明我国SRTM3DEM数据高程精度质量受地形影响并存在一定的空间差异性,同时我国范围内SRTM3DEM数据高程精度质量整体上要高于1∶25万DEM。     

Accuracy assessment of GDEM,SRTM, and DLR-SRTM in Northeastern China

This paper compares the accuracy of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM), Shuttle Radar Topography Mission (SRTM) C-band and German Aerospace Centre (DLR)-SRTM X-band digital elevation models (DEMs) with the Ziyuan 3 (ZY-3) stereoscopic DEM and ground control points (GCPs). To date, the horizontal error of these DEMs has received little attention in accuracy assessments. Using the ZY-3 DEM as reference, this study examines (1) the horizontal offset between the three DEMs and the reference DEM using the normalised cross-correlation method, (2) the vertical accuracy of those DEMs using kinematic GPS data and (3) the relationship between the three DEMs and the reference ZY-3 DEM. The results show that the SRTM and DLR-SRTM have greater vertical accuracy after applying horizontal offset correction, whereas the vertical accuracy of the ASTER GDEM is less than the other two DEMs. These methods and results can be useful for researchers who use DEMs for various applications.     

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。     

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).     

中国地区3"SRTM高程误差特征

系统评估了中国地区航天飞机雷达地形测绘任务（Shuttle Radar Topography Mision,SRTM）3″高程误差的分布及其与地形和地表覆盖因素的关系。通过单因子分析法,使用从50多万个样本点中提取的地表特征属性确定误差的变化规律。结果显示:SRTM高程误差与不同地形和地表覆盖类型关系密切;坡度增大误差由正变负,误差绝对值增大;正误差集中在偏北坡向,负误差集中在西南坡向;误差随植被覆盖增加而增大;冰川、沙漠、湿地区域误差整体为负,城镇建筑区的误差整体为正;坡度作为主导因素,同时影响其他因素对高程误差的作用。数据在某些区域存在明显高程异常,在平坦地区存在条带现象。整体上SRTM高程误差在中国地区呈现复杂的变化规律。     

基于资源三号测绘卫星DSM的精度评估研究

作为我国首颗民用立体测绘卫星数据产品,ZY-3 DSM对于我国地学分析具有极其重要的作用。本文在顾及地貌情况前提下,选取云南省高海拔山区为试验区,辅以1∶10 000野外实测地形图DEM为参考值,将分辨率为15 m的ZY-3 DSM与90 m的SRTM DEM从高程精度和地形精度进行较为全面的数据质量比较。结果表明:ZY-3 DSM在高程精度和地形精度均有更好的表现。总体看来,ZY-3 DSM数据质量更高,具有更广泛的利用价值。     

Assessment of Shuttle Radar Topography Mission Elevation Data Based on Topographic Maps in Turkey

Depending on scale, topographic maps depicting the shape of the land surfaces of the Earth are produced from different data sources. National topographic maps at a scale of 1:25 000 (25K maps) produced by General Command of Mapping are used as the base map set in Turkey. This map set, which consists of approximately 5500 sheets, covers the whole country and is produced using photogrammetric methods. Digital Elevation Models (DEMs) created from these maps are also available. Recently, another data source, Synthetic Aperture Radar (SAR) interferometric data, has become more important than those produced by conventional methods. The Shuttle Radar Topography Mission (SRTM) contains elevation data with 3 arc-second resolution and 16 m absolute height error (90 percent confidence level). These data are freely available via the Internet for approximately 80 percent of the Earth's land mass. In this study, SRTM DEM was compared with DEM derived from 25K topographic maps for different parts of Turkey. The study areas, each covering four neighboring 25K maps, and having an area of approximately 600 km², were chosen to represent various terrain characteristics. For the comparison, DEMs created from the 25K maps were obtained and organized as files for each map sheet in vector format, containing the digitized contour lines. From these data, DEMs in the resolution of 3 arc-second were created (25K-DEM), in the same structure as the SRTM DEM, allowing the 25K-DEMs and the SRTM DEM to be compared directly. The results show that the agreement of SRTM DEM to the 25K-DEM is within about 13 m, which is less than the SRTM's targeted error of 16 m. The spatial distribution of the height differences between SRTM-DEM and the 25K-DEM and correlation analysis show that the differences were mainly related to the topography of the test areas. In some areas, local height shifts were determined.     

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。     

SAR卫星轨道数据精度对Doris获取DEM精度的影响研究

本文介绍了InSAR卫星轨道状态矢量内插方法,基于荷兰Delft大学开发的Doris雷达干涉软件分析了SAR卫星轨道数据误差对基线参数、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。以西藏玛尼地区为例,采用ERS1/2卫星数据,利用Doris软件,分别生成了基于欧空局(ESA)粗略轨道数据和荷兰Delft大学精密轨道数据的数字高程模型(DEM),并以SRTMDEM为基准对其精度进行了对比分析。结果表明,基于粗轨数据获取的DEM明显存在系统偏差,而基于精轨数据获取的DEM与SRTM DEM吻合的很好,相对于前者,精度提高5倍。     

Effect of the SRTM global DEM on the determination of a high-resolution geoid model: a case study in Iran

Any errors in digital elevation models (DEMs) will introduce errors directly in gravity anomalies and geoid models when used in interpolating Bouguer gravity anomalies. Errors are also propagated into the geoid model by the topographic and downward continuation (DWC) corrections in the application of Stokes’s formula. The effects of these errors are assessed by the evaluation of the absolute accuracy of nine independent DEMs for the Iran region. It is shown that the improvement in using the high-resolution Shuttle Radar Topography Mission (SRTM) data versus previously available DEMs in gridding of gravity anomalies, terrain corrections and DWC effects for the geoid model are significant. Based on the Iranian GPS/levelling network data, we estimate the absolute vertical accuracy of the SRTM in Iran to be 6.5 m, which is much better than the estimated global accuracy of the SRTM (say 16 m). Hence, this DEM has a comparable accuracy to a current photogrammetric high-resolution DEM of Iran under development. We also found very large differences between the GLOBE and SRTM models on the range of −750 to 550 m. This difference causes an error in the range of −160 to 140 mGal in interpolating surface gravity anomalies and −60 to 60 mGal in simple Bouguer anomaly correction terms. In the view of geoid heights, we found large differences between the use of GLOBE and SRTM DEMs, in the range of −1.1 to 1 m for the study area. The terrain correction of the geoid model at selected GPS/levelling points only differs by 3 cm for these two DEMs.     

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.     

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.     

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.