Spot Revisited: Accuracy Assessment, Dem Generation and Validation from Stereo Spot 5 Hrg Images

SPOT 5 HRG Level 1A and 1B stereo scenes covering Zonguldak testfield in north-west Turkey have been analysed. They comprise the left and right image components with base to height ratio of 0·54. The pixel size on the ground is 5 m. The bundle orientation was executed by the PCI Geomatica V9.1.4 software package and resulted in 3D geopositioning to sub-pixel accuracies in each axis provided that at least six control points were used in the computation. Root mean square error (rmse) values and vectors of residual errors for Levels 1A and 1B are similar, even for different control and check point configurations. Based on the scene orientation, Level 1A and 1B digital elevation models (DEMs) of the testfield have been determined by automatic matching and validated by the reference DEM digitised from the 1:25 000 scale topographic maps, interferometric DEMs from Shuttle Radar Topography Mission (SRTM) X- and C-band SAR data and the GPS profiles measured along the main roads in the testfield. Although the accuracies of reference data-sets are too similar to the generated SPOT DEMs, these are the only high quality reference materials available in this area. Sub-pixel height accuracy was indicated by the comparison with profile points. However, they are in favourable locations where matching is always successful, so such a result may give a biased measure of the accuracy of the corresponding DEMs.     

Lidar Elevation Data for Surface Hydrologic Modeling: Resolution and Representation Issues

This paper is concerned with the application of high spatial resolution elevation data derived from light detection and ranging technologies (lidar) to surface hydrologic modeling. In recent years, airborne lidar technology has been employed to develop high accuracy digital elevation models (DEMs) with horizontal resolution on the order of a few meters. As with any spatial data product there are limits to the lidar's practical use that vary with the intended application. This paper considers potential issues and challenges for the use of lidar-derived DEMs in surface hydrologic modeling applications, such as characterizing flow direction and power, identifying sub-basins in a watershed, and calculating upstream contributing area and other variables. We compare results using conventional 30m DEMs and 6m lidar for a high relief study area and a low relief study area. Results are more comparable between these data sources, regardless of hydrologic operation, for the high relief area, while the similarity of results in the low relief area is dependent upon the particular operation. Post-processing on the lidar data successfully removed such flow obstacles as bridges that might have artificially impeded surface flow. An exploration of the effect of spatial resolution on results suggests that cell size is a more significant factor than production method.     

DEM精度检查中等高线回放的量化方法

目前数字高程模型(DEM)精度检查中广泛采用等高线回放方法,以目视检查方式进行,定性为主。基于集合论引进了一种量化方法,即层次等高线差异栅格分析法,用于描述等高线回放的平面位置变形量。实验证明此方法不仅可视化效果好,其量化指标有助于定位DEM误差,包括粗差;也适合对不同DEM内插方法精度评定的对比分析。     

Lidar-aided analysis of boreal forest backscatter at Ku band

This paper analyzes the backscatter of the microwave signal in a boreal forest environment based on a Ku -band airborne Frequency-Modulated Continuous Waveform (FMCW) profiling radar—Tomoradar. We selected a half-managed boreal forest in the southern part of Finland for a field test. By decomposing the waveform collected by the Tomoradar, the vertical canopy structure was achieved. Based on the amplitude of the waveform, the Backscattered Energy Ratio of Canopy-to-Total (BERCT) was calculated. Meanwhile, the canopy fraction was derived from the corresponding point cloud recorded by a Velodyne VLP-16 LiDAR mounted on the same platform. Lidar-derived canopy fraction was obtained by counting the number of the first/ the strongest returns versus the total amount of returns. Qualitative and quantitative analysis of radar-derived BERCT on lidar-derived canopy fraction and canopy height are investigated. A fitted model is derived to describe the Ku-band microwave backscatter in the boreal forest to numerically analyze the proportion contributed by four factors: lidar-derived canopy fraction, radar-derived canopy height, the radar-derived distance between trees and radar sensor and other factors, from co-polarization Tomoradar measurements. The Root Mean Squared Error (RMSE) of the proposed model was 0.0958, and the coefficient of determination R2 was 0.912. The fitted model reveals that the correlation coefficient between radar-derived BERCT and lidar-derived canopy fraction is 0.84, which illustrates that lidar surface reflection explains the majority of the profiling /waveform radar response. Thus, vertical canopy structure derived from lidar can be used for the benefit of radar analysis.     

A total error-based multiquadric method for surface modeling of digital elevation models

Digital elevation model (DEM) source data are subject to both horizontal and vertical errors owing to improper instrument operation, physical limitations of sensors, and bad weather conditions. These factors may bring a negative effect on some DEM-based applications requiring low levels of positional errors. Although classical smoothing interpolation methods have the ability to handle vertical errors, they are prone to omit horizontal errors. Based on the statistical concept of the total least squares method, a total error-based multiquadric (MQ-T) method is proposed in this paper to reduce the effects of both horizontal and vertical errors in the context of DEM construction. In nature, the classical multiquadric (MQ) method is a vertical error regression procedure, whereas MQ-T is an orthogonal error regression model. Two examples, including a numerical test and a real-world example, are employed in a comparative performance analysis of MQ-T for surface modeling of DEMs. The numerical test indicates that MQ-T performs better than the classical MQ in terms of root mean square error. The real-world example of DEM construction with sample points derived from a total station instrument demonstrates that regardless of the sample interval and DEM resolution, MQ-T is more accurate than classical interpolation methods including inverse distance weighting, ordinary kriging, and Australian National University DEM. Therefore, MQ-T can be considered as an alternative interpolator for surface modeling with sample points subject to both horizontal and vertical errors.     

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.     

Effect of sensor modelling methods on computation of 3-D coordinates from Cartosat-1 stereo data

The orbital and the rational polynomial coefficients (RPC) models are the two most commonly used models to compute a three-dimensional coordinates from an image stereo-pair. But it is still confusing that with the identical user provided inputs, which one of these two models provides more accurate digital elevation model (DEM), especially for mountainous terrain. This study aimed to find out the answer by evaluating the impact of used models on the vertical accuracy of DEM extracted from Cartosat-1 stereo data. We used high-accuracy photogrammetric DEM as the reference DEM. Apart from general variations in statistics, surprisingly in a few instances, both the DEMs provided contrasting results, thus proving the significance of this study. The computed root mean square errors and linear error at 90% (LE90) were lower in case of RPC DEM for various classes of slope, aspect and land cover, thus suggesting its better relative accuracy.     

Orthorectification of IKONOS and impact of different resolution DEM

IKONOS image has been wildly used in city planning, precision agriculture and emergence response. However, the accuracy of IKONOS Geo product is limited due to distortion caused by terrain relief. Orthorectification was performed to remove the distortion and the impact of different DEM on orthorectification were evaluated. 38 ground control points （GCPs） and 25 independent check points （ICPs） were collected. DEMs were generated from 1 ： 10 000 and 1 ： 50 000 topographic maps. Results show that RMS error at the check points is 1. 554 0 m using DEM generated from 1 ： 10 000 topographic map, which can meet the accuracy requirement of IKONOS Precision product （1.9 m RMSE）. While RMS error is 2. 572 4 m using DEM generated from 1 ： 50 000 topographic map.     

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.     

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.     

3-D Radargrammetric Modeling of RADARSAT-2 Ultrafine Mode: Preliminary Results of the Geometric Calibration

The geometry and the accuracy of the 3-D cartographic localization of RADARSAT-2 images are being evaluated as part of the Canadian Space Agency's Science and Operational Applications Research program. In a first step, the Toutin's 3-D physical model, previously developed for RADARSAT-1, was adapted to RADARSAT-2 sensor and applied to two ultrafine mode images (U2 and U25) acquired over an area in Beauport, Quebec. Both the 3-D modeling computed with only 12 ground control points and its geometric localization were evaluated with different check data: 1) independent check points; 2) the two quasi-epipolar images; 3) the two orthoimages; and 4) 1-m accurate orthophotos. All four results and validations are in agreement and confirm that the 3-D geometric localization and restitution accuracy are 1 m in planimetry and 2 m in elevation. The checked data error being included in these evaluations and the relative error computed from the quasi-epipolar comparison provided a high level of confidence that the precision of Toutin's 3-D radargrammetric model is better than 0.25 m.     

Effects of laser beam alignment tolerance on lidar accuracy

One of the major lidar error sources not yet analyzed in the literature is the tolerance of the laser beam alignment with respect to the scanning mirror. In this paper, the problem of quantifying these errors is solved for rotating polygon mirror type lidar systems. An arbitrary deviation of the beam from its design direction–the vector of beam misalignment–can be described by two independent parameters. We choose these as horizontal and vertical components of the misalignment vector in the body frame. Either component affects both, horizontal and vertical lidar accuracy. Horizontal lidar errors appear as scan line distortions—along and across track shifts, rotations and scaling. It is shown that the horizontal component of misalignment results in a scan line first being shifted across the track and then rotated around the vertical at the new center of the scan line. Resulting vertical lidar error, being a linear function of the scan angle, is similar to that produced by a roll bias. The vertical component of the beam misalignment causes scan line scaling and an along track shift. The corresponding vertical error is quadratic with respect to the scan angle. The magnitude of these effects is significant even at tight alignment tolerances and cannot be realistically accounted for in the conventional calibration model, which includes only range, attitude and GPS biases. Therefore, in order to attain better accuracy, this model must be expanded to include the beam misalignment parameters as well. Addition of new parameters into the model raises a question of whether they can be reliably solved for. To give a positive answer to this question, a calibration method must utilize not only ground control information, which is typically very limited, but also the relative accuracy information from the overlapping flight lines.     

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.     

Accuracy assessment of airborne photogrammetrically derived high-resolution digital elevation models in a high mountain environment

High-resolution digital elevation models (DEMs) generated by airborne remote sensing are frequently used to analyze landform structures (monotemporal) and geomorphological processes (multitemporal) in remote areas or areas of extreme terrain. In order to assess and quantify such structures and processes it is necessary to know the absolute accuracy of the available DEMs. This study assesses the absolute vertical accuracy of DEMs generated by the High Resolution Stereo Camera-Airborne (HRSC-A), the Leica Airborne Digital Sensors 40/80 (ADS40 and ADS80) and the analogue camera system RC30. The study area is located in the Turtmann valley, Valais, Switzerland, a glacially and periglacially formed hanging valley stretching from 2400 m to 3300 m a.s.l. The photogrammetrically derived DEMs are evaluated against geodetic field measurements and an airborne laser scan (ALS). Traditional and robust global and local accuracy measurements are used to describe the vertical quality of the DEMs, which show a non Gaussian distribution of errors. The results show that all four sensor systems produce DEMs with similar accuracy despite their different setups and generations. The ADS40 and ADS80 (both with a ground sampling distance of 0.50 m) generate the most accurate DEMs in complex high mountain areas with a RMSE of 0.8 m and NMAD of 0.6 m They also show the highest accuracy relating to flying height (0.14‰). The pushbroom scanning system HRSC-A produces a RMSE of 1.03 m and a NMAD of 0.83 m (0.21‰ accuracy of the flying height and 10 times the ground sampling distance). The analogue camera system RC30 produces DEMs with a vertical accuracy of 1.30 m RMSE and 0.83 m NMAD (0.17‰ accuracy of the flying height and two times the ground sampling distance). It is also shown that the performance of the DEMs strongly depends on the inclination of the terrain. The RMSE of areas up to an inclination <40° is better than 1 m. In more inclined areas the error and outlier occurrence increase for all DEMs. This study shows the level of detail to which airborne stereoscopically derived DEMs can reliably be used in high mountain environments. All four sensor systems perform similarly in flat terrain.     

Improving the Elevation Accuracy of Digital Elevation Models: A Comparison of Some Error Detection Procedures

The widespread availability of powerful desktop computers, easy‐to‐use software tools and geographic datasets have raised the quality problem of input data to be a crucial one. Even though accuracy has been a concern in every serious application, there are no general tools for its improvement. Some particular ones exist, however, and some results are presented here for a particular case of quantitative raster data: Digital Elevation Models (DEM). Two procedures designed to detect anomalous values (also named gross errors, outliers or blunders) in DEMs, but valid also for other quantitative raster datasets, were tested. A DEM with elevations varying from 181 to 1044 m derived from SPOT data has been used as a contaminated sample, while a manually derived DEM obtained from aerial photogrammetry was regarded as the ground truth to allow a direct performance comparison for the methods with real errors. It is assumed that a “better” value can be measured or obtained through some methodology once an outlier location is suggested. The options are different depending upon the user (DEM producers might go to the original data and make another reading, while end users might use interpolation). Both choices were considered in this experiment. Preliminary results show that for the available dataset, the accuracy might be improved to some extent with very little effort. Effort is defined here as the percentage of points suggested by the methodology in relation with its total number: thus 100 per cent effort implies that all points have been checked. The method proposed by López (1997) gave poor results, because it has been designed for errors with low spatial autocorrelation (which is not the case here). A modified version was then designed and compared with the method proposed by Felicísimo (1994). The three procedures can be applied both for error detection during DEM generation and by end users, and they might be of use for other quantitative raster data. The choice of the best methodology is different depending on the effort involved. The conclusions have been derived for a photogrammetrically obtained DEM; other production procedures might lead to different results.     

QUALITY CONTROL OF PHOTOGRAMMETRICALLY SAMPLED DIGITAL ELEVATION MODELS

The object of this paper is to study the geometric accuracy of photogrammetrically sampled digital elevation models (DEMs)obtained by using an on line graphical DEM editor. As a reference, DEMs obtained by regular grid measurements have been used. Three different test areas are used in the study, each representing different ground types and degrees of homogeneity. The DEMs have been evaluated with respect to their standard errors in elevation, slope and curvature. The results show that the standard errors are not improved by using the on line DEM editor. It is also demonstrated that an increased point density decreases the standard error in elevation while its effect on the standard error in slope is limited. The standard error in curvature is almost independent of the point density.     

DEM约束的卫星影像定位法

作为"云控制"摄影测量理论和方法的发展,研究了DEM约束的立体卫星影像区域网平差方法。与DEM仅作为高程控制信息使用,或者是通过DEM表面匹配实现绝对定向的间接定位方法不同,DEM作为平高控制信息被直接引入至基于RFM模型的卫星影像区域网平差之中。本文方法将连接点地面高程与DEM格网内插高程之差作为虚拟观测值构建约束方程,不仅利用了DEM高程信息,并且利用了其地形曲面包含的平面信息,以"云控制"方式在区域网平差过程中有效消除卫星影像RPC参数中包含的整体偏移及区域网内部的扭曲变形,实现了无地面控制点条件下卫星影像平面及高程绝对定位精度的大幅提升。使用覆盖山东全境的330景天绘一号立体卫星影像进行试验,分别以AW3D30、ASTER GDEM和SRTM GL3共3种开源DEM作为控制信息,并使用100个外业实测控制点进行精度评测。试验表明,以DEM作为控制可显著提高区域网平差的平面与高程精度,卫星影像绝对定位精度与DEM自身精度有关。当使用AW3D30作为控制时,可以取得与使用100个外业控制点平差同等精度,平面中误差为5.0 m(约1像素),高程中误差为2.9 m。试验结果证明了DEM替代外业控制点作为平差控制信息的有效性与可行性。     

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.