Evaluation of ASTER GDEM using GPS benchmarks and SRTM in China

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) has generated one of the most complete high-resolution digital topographic data sets of the world to date. The ASTER GDEM covers land surfaces between 83° N and 83° S at a spatial resolution of 1 arc-second (approximately 30 m at the equator). As an improvement over Shuttle Radar Topography Mission (SRTM) coverage, the ASTER GDEM will be a very useful product for many applications, such as relief analysis, hydrological studies, and radar interferometry. In this article, its absolute vertical accuracy in China was assessed at five study sites using ground control points (GCPs) from high-accuracy GPS benchmarks and also using a DEM-to-DEM comparison with the Consultative Group on International Agriculture Research Consortium for Spatial Information (CGIAR-CSI) SRTM DEM Version 4.1. It is demonstrated that the vertical accuracy of ASTER GDEM is 26 m (root mean square error (RMSE)) against GPS-GCPs, while for the SRTM DEM it is 23 m. Furthermore, height differences in the GDEM-SRTM comparison appear to be overestimated in the areas with a south or southwest aspect in the five study areas. To a certain extent, the error can be attributed to variations in heights due to land-cover effects and undefined inland waterbodies. But the ASTER GDEM needs further error-mitigating improvements to meet the expected accuracy specification. However, as for its unprecedented detail, it is believed that the ASTER GDEM offers a major alternative in accessibility to high-quality elevation data.     

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。     

多源外部DEM对两轨DINSAR测量结果影响分析

在总结两轨差分中参考DEM影响的最新研究成果基础上,以青藏高原上典型平地和山地作为研究区,利用理论上没有形变的ERS Tandem像对以及3种常用外部参考DEM（SRTM,ASTER GDEM,1∶5万DEM）,使用ROI_PAC软件进行两轨差分干涉试验。实例证明：SRTM更适合作为两轨差分中的外部参考DEM,并对此试验结果予以解释分析,即多源DEM数据质量的差异导致干涉图与DEM配准精度的不同,并最终反映在差分干涉相位误差中。本文研究结论对提高DInSAR处理精度有参考价值。     

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.     

基于无人机影像的山地人工林景观DEM构建

山地人工林景观的DEM构建是对景观地形信息进行描述的基础的研究内容,也是人工林景观面积、结构、蓄积量等信息提取的重要因子,具有重要的研究意义。通过无人机平台获取影像,采用立体像对拼接的方式生成正射影像并提取DEM信息,并与GPS测量数据、ASTER GDEM、SRTM数据进行比较分析。结果表明:在该区域无人机影像构建的DEM与实测高程差距最小(RMSE=8.96),具有比ASTER GDEM(RMSE=13.68)和SRTM(RMSE=11.81)更高的精度;在每个样方内的最大高程差值与最大树高最为接近(RMSE=1.813),说明无人机DEM能够反映出更多的冠层与地面分层信息,在山地人工林景观DEM构建中表现出较大潜力。     

A regional ASTER GDEM error model for the Chinese Loess Plateau

Accuracy of the global ASTER GDEM (Advanced Space-borne Thermal Emission and Reflection Radiometer Global Digital Elevation Model) version 2 (v2) elevation data product is highly variable regionally, as are its empirical correlations with landscape variables. This paper investigates GDEM error along a 49-site geomorphologic gradient within the core region of the Chinese Loess Plateau, notable for its heterogeneous terrain. The error is modelled using its associations with MODIS (Moderate Resolution Imaging Spectroradiometer) composite forest cover percentage, GlobeLand30 land cover, and key elevation derivatives, including two indices, terrain roughness index (TRI) and topographic position index (TPI), not previously evaluated in GDEM accuracy studies. Overall root mean squared error (RMSE) is 20.33 m, in excess of the GDEM v2 accuracy specifications, while RMSE at each site varies substantially, from 10.67 m for a low relief area to 21.84 m for the most rugged site. Strong associations between covariates, especially slope, aspect, TRI, and forest cover are identified. A regression model using these variables is developed to formally characterize and predict GDEM error. External validation with independent checkpoints across all sites demonstrates that this model can reduce mean error by about 4 m.     

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。     

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.     

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.     

DEM generation using Ziyuan-3 mapping satellite imagery without ground control points

ABSTRACT

This article proposes a digital elevation model (DEM) generation approach using the Shuttle Radar Topography Mission (SRTM) DEM as the elevation constraint without ground control points. First, during the process of image block adjustment, we took advantage of the relatively high vertical accuracy of the SRTM-DEM in flat terrain regions and applied effective constraints on the object-space elevation-corrected value of tie points using the SRTM-DEM, achieving improved vertical accuracy for large-scale block adjustments. Subsequently, for the DEM matching process, multiple two-linear array stereo image pairs were obtained from along-track and across-track images with different look angles over the same region after the block adjustment. Then, the matching result of each stereo image pair underwent weighted fusion, before being used to generate the final DEM product. This approach can effectively enhance the matching quality and grid density of the final DEM product. The DEM generation experiment, using Ziyuan-3 images covering 186,000 km² of Hubei Province, China, showed that the matching quality of the 10 m grid DEM was excellent. The vertical root mean square errors were 1.5 m in the flat regions and 2.96 m in the mountainous regions, thus achieving China’s 1:25,000 scale specification requirement for DEM products.     

Effects of terrain-induced shade removal using global DEM data sets on land-cover classification

Free access to global data sets of satellite images and digital elevation models (DEMs) such as Aster Global DEM (GDEM) and Shuttle Radar Topography Mission (SRTM) digital topography are expected to contribute to various study areas that deal with land cover and land use. To assess the capabilities of these global DEM data sets and to provide guidelines for performing shade removal under various terrain and illumination conditions, we evaluated the results of shade removal using the Minnaert correction and C-correction. These corrections were applied, using the GDEM (versions 1 and 2), SRTM, and a DEM derived from a local map (local DEM), to 30 sample images from 20 scenes of 10 path-rows in global land survey (GLS) Landsat-TM/ETM+ images, in terms of statistical indices and the accuracy of land-cover discrimination. The analysis indicated that the results of shade removal depended mainly on the correlation between the cosine of the sunshine incidence angle (cos(i)) and the radiance before shade removal, except in some cases with inferior illumination conditions. Of the three global DEMs, GDEM version 2 had the highest performance in shade removal. However, this study also indicated that successful shade removal was only one of the several factors that increased the accuracy of land-cover classification. In practical applications, shade removal can be recommended only for images where the terrain shade obviously disturbs the original spectral reflection characteristics of each land-cover type and no significant dependence of the land-cover distribution on the slope aspect is assumed. In such cases, also global DEMs evaluated in this study can be used for shade removal.     

Combination of SRTM3 and repeat ASTER data for deriving alpine glacier flow velocities in the Bhutan Himalaya

The present study evaluates the fusion of DEMs from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument and the Shuttle Radar Topography Mission (SRTM). The study area consists of high elevation glaciers draining through the rough topography of the Bhutan Himalayas. It turns out that the ASTER-derived and SRTM3 DEMs have similar accuracy over the study area, but the SRTM3 DEM contains less gross errors. However, for rough topography large sections of the SRTM3 DEM contain no data. We therefore compile a combined SRTM3-ASTER DEM. From this final composite-master DEM, we produce repeat ASTER orthoimages from which we evaluate the DEM quality and derive glacier surface velocities through image matching. The glacier tongues north of the Himalayan main ridge, which enter the Tibet plateau, show maximum surface velocities in the order of 100-200 m year⁻¹. In contrast, the ice within the glacier tongues south of the main ridge flows with a few tens of meters per year. These findings have a number of implications, among others for glacier dynamics, glacier response to climate change, glacier lake development, or glacial erosion. The study indicates that space-based remote sensing can provide new insights into the magnitude of selected surface processes and feedback mechanisms that govern mountain geodynamics.     

Analysis of the water volume,length, total area and inundated area of the Three Gorges Reservoir,China using the SRTM DEM data

Using the Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) data covering the region of the Three Gorges Reservoir, Changjiang, China, we have computed the water volume, length, and total and inundated areas of the reservoir, with the assumption that the water surface within the reservoir is flat. When the reservoir's surface water level is 175 m above the mean sea level, the computed values may be comparable to the official data published by the Chinese government.     

Evaluating and comparing performances of topographic correction methods based on multi-source DEMs and Landsat-8 OLI data

Topographic correction is a crucial and challenging step in interpreting optical remote-sensing images of extremely complex terrain environments due to the lack of universally suitable correction algorithms and digital elevation models (DEMs) of adequate resolution and quality. The free availability of open source global DEMs provides an unprecedented opportunity to remove topographic effects associated with remote-sensing data in remote and rugged mountain terrains. This study evaluated the performances of seven topographic correction methods including C-correction (C), Cosine C-correction (CC), Minnaert correction (M), Sun–canopy–sensor (SCS) correction (S), SCS+C-correction (SC), Teillet regression correction (TR), and the Terrain illumination correction model (TI) based on multi-source DEMs (local topographic map, Shuttle Radar Topography Mission (SRTM) DEM filled-finished A/B and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) global digital elevation model (GDEM) data sets) and Landsat-8 Operational Land Imager (OLI) data using visual and statistical evaluation strategies. Overall, these investigated topographic correction methods removed topographic effects associated with Landsat-8 OLI data to varying degrees. However, the performances of these methods generally depend on the use of different DEMs and evaluation strategies. Among these correction methods, the SCS+C-correction performed best and was less sensitive to the use of different DEMs. The performances of topographic corrections based on free and open-access DEMs were generally better than or comparable to those based on local topographic maps. In particular, the topographic correction performance was greatly improved using the SRTM filled-finished B (FFB) data set with a resampling scheme based on the average value within a 3 × 3 pixel window. Nevertheless, further quantitative investigation is needed to determine the relative importance of DEMs and evaluation strategies used to select topographic correction methods.     

A mutual assessment of the uncertainties of digital elevation models using the triple collocation technique

This study investigates the uncertainties of digital elevation models (DEMs) using the triple collocation (TC) method. DEMs from satellite missions are important for many geoscience disciplines and for economic benefits and are freely available. Validating DEMs is necessary to select an appropriate model for a given region and application. Provided certain assumptions about the error structure of any three data sets – measuring the same phenomenon – can be made, the TC approach can be used to provide an unbiased and scaled estimate of the error variances of the data sets, without requiring a reference data. We compared the TC approach to the traditional approach of using a reference data set using the Shuttle Radar Topography Mission version 4.1 (SRTM v4.1) DEM, ASTER (the Advanced Spaceborne Thermal Emission and Reflection Radiometer) GDEM (Global DEM) version 2, the 1 arc-minute global relief model (ETOPO1), a DEM compiled by the Survey and Mapping Division of Ghana (SMD DEM), and 545 ground control stations (GCSs). The error estimates for the DEMs via TC were considerably smaller than those obtained from the reference-based approach. As an example, the best performing DEM (SRTM v4.1) recorded a root-mean-square error (RMSE) of 15.601 m using the GCSs as reference, while its TC-derived accuracy was 6.517 m. We note that based on the results of the TC, the estimated error of the GCSs is approximately 14 m. Using a data set with an error of 14 m to validate other data sets is certainly bound to result in unfavorable results. Thus, we have demonstrated in this work that the TC approach is able to provide an unbiased error of DEMs. The approach is important even for regions where GCSs are highly accurate, but more so for regions with low-quality GCSs.     

Geomorphological changes associated with underground coal mining in the Fushun area,northeast China revealed by multitemporal satellite remote sensing data

Fushun is a famous coal-mining city in northeastern China with more than 100 years of history. Long-term underground coal mining has caused serious surface subsidence in the eastern part of the city. In this study, multitemporal and multisource satellite remote sensing data were used to detect subsidence and geomorphological changes associated with underground coal mining over a 10-year period (1996–2006). A digital elevation model (DEM) was generated through Synthetic Aperture Radar (SAR) interferometry processing using data from a pair of European Remote Sensing Satellite (ERS) SAR images acquired in 1996. In addition, a Shuttle Radar Topography Mission (SRTM) DEM obtained from data in 2000 and an Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) DEM from 2006 were used for this study. The multitemporal DEMs indicated that the maximum vertical displacement due to subsidence was around 13 m from 1996 to 2006. Multitemporal ASTER images showed that the flooded water area associated with subsidence had increased by 1.73 km² over the same time period. Field investigations and ground level measurements confirmed that the results obtained from the multitemporal remote sensing data agreed well with ground truth data. This study demonstrates that DEMs derived from multisource satellite remote sensing data can provide a powerful tool to map geomorphological changes associated with underground mining activities.     

SRTM 3″ DEM (versions 1, 2, 3, 4) validation by means of extensive kinematic GPS measurements: a case study from North Greece

In 2000, the Shuttle Radar Topography Mission (SRTM) provided for the first time a global high-quality digital elevation model (DEM) at resolution levels of one and three arcseconds, using single-pass synthetic aperture radar (SAR) interferometry. In January and February 2008, an extensive four-day kinematic global positioning system (GPS) (KGPS) campaign was carried out in the vicinity of the city of Thessaloniki (North Greece), during which more than 60 000 points were collected, providing an unprecedented density of measurements in the order of 20 points km^?2. The purpose of the present study was to assess the vertical accuracy of the four versions of SRTM 3″ DEMs that are currently available over the Internet for public use, on the basis of the KGPS data collected.     

SRTM DEM accuracy assessment over vegetated areas in Norway

Results from the Shuttle Radar Topography Mission (SRTM) are presented. The SRTM C‐band and X‐band digital elevation models (DEMs) are evaluated with regard to elevation accuracies over agricultural fields, forest areas and man‐made features in Norway. High‐resolution digital maps and satellite images are used as background data. In general, many terrain details can be observed in the SRTM elevation datasets. The elevation accuracy (90% confidence level) of the two SRTM systems is estimated to less than 6.5 m for open agricultural fields and less than 11 m considering all land surface covers. This is better than specifications. Analysis of dense Norwegian forest stands shows that the SRTM system will produce elevation data that are as much as 15 m higher than the ground surface. The SRTM DEM products will therefore partly indicate canopy elevations in forested areas. We also show that SRTM data can be used to update older DEMs obtained from other sources, as well as estimating the volume of rock removed from large man‐made gravel pits.     

ASTER GDEM数据介绍与程序读取

2009年6月30日,期待已久的ASTER GDEM数据由日本经济产业省(METI)和美国航天局(NASA)共同发布,其空间分辨率达到了1弧秒×1弧秒(约30m×30m),相比2003年NASA发布的SRTM数据有了很大的提高,并且其陆地表面覆盖率也大幅提高,达到了陆地面积的99%。本文介绍了ASTER GDEM的相关特性以及使用程序读取该数据的方法。     

Digital elevation model (DEM) generation and accuracy assessment from ASTER stereo data

Digital elevation models (DEM) are the indispensable quantitative environmental variable in most of the research studies in remote sensing. The improvement of sensor and satellite imaging technologies enabled the researchers to generate DEM using remotely sensed data. These data can be started to use as not only the two-dimensional (2-D) but also three-dimensional (3-D) information sources with usage of the DEM. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is one of the sensor systems capable of DEM generation and during the study, ASTER level 1A (L1A) data were used. Due to presence of many geological features and different landcover types, the test site is selected as the watershed of Asarsuyu River, located in north-western Anatolia in between Duzce and Bolu plains. The aim of this study is to check the best effort of 15 m spatial resolution DEM generation from ASTER L1A data by collecting different numbers of ground control points (GCP) (30, 45, and 60) and tie points (TP). During the study, three different techniques—spatial correlation, image differencing and profiling—were used for both planimetric and vertical accuracy assessment. The obtained results from both of the techniques show that the accuracy of the DEM increases by increasing the number of GCP. However, there is an only slight difference between the result of 45 GCPs and 60 GCPs.