Reference Digital Elevation Model Research Articles

A protocol for the ranking of interpolation algorithms based on confidence levels

ABSTRACTThe choice of the best interpolation algorithm of data gathered at a finite number of locations has been a persistently relevant topic. Typical papers take a single data set, a single set of data points, and a handful of algorithms. The process considers a subset I of the data points as known, builds the interpolant with each algorithm, applies it to the points of another subset C, and evaluates the MAE (mean absolute error), the RMSE (root mean square error), or any other metric over such points. The less these statistics are, the better the algorithm is, so a deterministic ranking between methods (without confidence level) can be derived based upon it. Ties between methods are usually not considered. In this article a complete protocol is proposed in order to build, with a modest additional effort, a ranking with a confidence level. To illustrate this point, the results of two tests are shown. In the first one, a simple Monte Carlo experiment was devised using irregularly distributed points taken from a reference DEM (digital elevation model) in raster format. Different metrics led to different rankings, suggesting that the choice of the metric to define the ‘best interpolation algorithm’ would need a trade-off. The second experiment used mean daily radiation data from an international interpolation comparison exercise and RMSE as the metric of success. Only five simple interpolation methods were employed. The ranking using this protocol anticipated correctly the first and second place, afterwards confirmed employing independent control data.

DEM Fusion using a modified k-means clustering algorithm

ABSTRACTDigital 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.

GLACIER VOLUME CHANGE ESTIMATION USING TIME SERIES OF IMPROVED ASTER DEMS

Abstract. Volume change data is critical to the understanding of glacier response to climate change. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) system embarked on the Terra (EOS AM-1) satellite has been a unique source of systematic stereoscopic images covering the whole globe at 15m resolution and at a consistent quality for over 15 years. While satellite stereo sensors with significantly improved radiometric and spatial resolution are available to date, the potential of ASTER data lies in its long consistent time series that is unrivaled, though not fully exploited for change analysis due to lack of data accuracy and precision. Here, we developed an improved method for ASTER DEM generation and implemented it in the open source photogrammetric library and software suite MicMac. The method relies on the computation of a rational polynomial coefficients (RPC) model and the detection and correction of cross-track sensor jitter in order to compute DEMs. ASTER data are strongly affected by attitude jitter, mainly of approximately 4 km and 30 km wavelength, and improving the generation of ASTER DEMs requires removal of this effect. Our sensor modeling does not require ground control points and allows thus potentially for the automatic processing of large data volumes. As a proof of concept, we chose a set of glaciers with reference DEMs available to assess the quality of our measurements. We use time series of ASTER scenes from which we extracted DEMs with a ground sampling distance of 15m. Our method directly measures and accounts for the cross-track component of jitter so that the resulting DEMs are not contaminated by this process. Since the along-track component of jitter has the same direction as the stereo parallaxes, the two cannot be separated and the elevations extracted are thus contaminated by along-track jitter. Initial tests reveal no clear relation between the cross-track and along-track components so that the latter seems not to be easily modeled analytically from the first one. We thus remove the remaining along-track jitter effects in the DEMs statistically through temporal DEM stacks to finally compute the glacier volume changes over time. Our method yields cleaner and spatially more complete elevation data, which also proved to be more in accordance to reference DEMs, compared to NASA’s AST14DMO DEM standard products. The quality of the demonstrated measurements promises to further unlock the underused potential of ASTER DEMs for glacier volume change time series on a global scale. The data produced by our method will help to better understand the response of glaciers to climate change and their influence on runoff and sea level.

GLACIER VOLUME CHANGE ESTIMATION USING TIME SERIES OF IMPROVED ASTER DEMS

Volume change data is critical to the understanding of glacier response to climate change. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) system embarked on the Terra (EOS AM-1) satellite has been a unique source of systematic stereoscopic images covering the whole globe at 15m resolution and at a consistent quality for over 15 years. While satellite stereo sensors with significantly improved radiometric and spatial resolution are available to date, the potential of ASTER data lies in its long consistent time series that is unrivaled, though not fully exploited for change analysis due to lack of data accuracy and precision. Here, we developed an improved method for ASTER DEM generation and implemented it in the open source photogrammetric library and software suite MicMac. The method relies on the computation of a rational polynomial coefficients (RPC) model and the detection and correction of cross-track sensor jitter in order to compute DEMs. ASTER data are strongly affected by attitude jitter, mainly of approximately 4 km and 30 km wavelength, and improving the generation of ASTER DEMs requires removal of this effect. Our sensor modeling does not require ground control points and allows thus potentially for the automatic processing of large data volumes. <br><br> As a proof of concept, we chose a set of glaciers with reference DEMs available to assess the quality of our measurements. We use time series of ASTER scenes from which we extracted DEMs with a ground sampling distance of 15m. Our method directly measures and accounts for the cross-track component of jitter so that the resulting DEMs are not contaminated by this process. Since the along-track component of jitter has the same direction as the stereo parallaxes, the two cannot be separated and the elevations extracted are thus contaminated by along-track jitter. Initial tests reveal no clear relation between the cross-track and along-track components so that the latter seems not to be easily modeled analytically from the first one. We thus remove the remaining along-track jitter effects in the DEMs statistically through temporal DEM stacks to finally compute the glacier volume changes over time. Our method yields cleaner and spatially more complete elevation data, which also proved to be more in accordance to reference DEMs, compared to NASA’s AST14DMO DEM standard products. <br><br> The quality of the demonstrated measurements promises to further unlock the underused potential of ASTER DEMs for glacier volume change time series on a global scale. The data produced by our method will help to better understand the response of glaciers to climate change and their influence on runoff and sea level.

A robust interpolation method for constructing digital elevation models from remote sensing data

A digital elevation model (DEM) derived from remote sensing data often suffers from outliers due to various reasons such as the physical limitation of sensors and low contrast of terrain textures. In order to reduce the effect of outliers on DEM construction, a robust algorithm of multiquadric (MQ) methodology based on M-estimators (MQ-M) was proposed. MQ-M adopts an adaptive weight function with three-parts. The weight function is null for large errors, one for small errors and quadric for others. A mathematical surface was employed to comparatively analyze the robustness of MQ-M, and its performance was compared with those of the classical MQ and a recently developed robust MQ method based on least absolute deviation (MQ-L). Numerical tests show that MQ-M is comparative to the classical MQ and superior to MQ-L when sample points follow normal and Laplace distributions, and under the presence of outliers the former is more accurate than the latter. A real-world example of DEM construction using stereo images indicates that compared with the classical interpolation methods, such as natural neighbor (NN), ordinary kriging (OK), ANUDEM, MQ-L and MQ, MQ-M has a better ability of preserving subtle terrain features. MQ-M replaces thin plate spline for reference DEM construction to assess the contribution to our recently developed multiresolution hierarchical classification method (MHC). Classifying the 15 groups of benchmark datasets provided by the ISPRS Commission demonstrates that MQ-M-based MHC is more accurate than MQ-L-based and TPS-based MHCs. MQ-M has high potential for DEM construction.

VALIDATION OF "AW3D" GLOBAL DSM GENERATED FROM ALOS PRISM

Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM), one of onboard sensors carried by Advanced Land Observing Satellite (ALOS), was designed to generate worldwide topographic data with its optical stereoscopic observation. It has an exclusive ability to perform a triplet stereo observation which views forward, nadir, and backward along the satellite track in 2.5 m ground resolution, and collected its derived images all over the world during the mission life of the satellite from 2006 through 2011. A new project, which generates global elevation datasets with the image archives, was started in 2014. The data is processed in unprecedented 5 m grid spacing utilizing the original triplet stereo images in 2.5 m resolution. As the number of processed data is growing steadily so that the global land areas are almost covered, a trend of global data qualities became apparent. This paper reports on up-to-date results of the validations for the accuracy of data products as well as the status of data coverage in global areas. The accuracies and error characteristics of datasets are analyzed by the comparison with existing global datasets such as Ice, Cloud, and land Elevation Satellite (ICESat) data, as well as ground control points (GCPs) and the reference Digital Elevation Model (DEM) derived from the airborne Light Detection and Ranging (LiDAR).

VALIDATION OF "AW3D" GLOBAL DSM GENERATED FROM ALOS PRISM

Abstract. Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM), one of onboard sensors carried by Advanced Land Observing Satellite (ALOS), was designed to generate worldwide topographic data with its optical stereoscopic observation. It has an exclusive ability to perform a triplet stereo observation which views forward, nadir, and backward along the satellite track in 2.5 m ground resolution, and collected its derived images all over the world during the mission life of the satellite from 2006 through 2011. A new project, which generates global elevation datasets with the image archives, was started in 2014. The data is processed in unprecedented 5 m grid spacing utilizing the original triplet stereo images in 2.5 m resolution. As the number of processed data is growing steadily so that the global land areas are almost covered, a trend of global data qualities became apparent. This paper reports on up-to-date results of the validations for the accuracy of data products as well as the status of data coverage in global areas. The accuracies and error characteristics of datasets are analyzed by the comparison with existing global datasets such as Ice, Cloud, and land Elevation Satellite (ICESat) data, as well as ground control points (GCPs) and the reference Digital Elevation Model (DEM) derived from the airborne Light Detection and Ranging (LiDAR).

DEM-Aided Bundle Adjustment With Multisource Satellite Imagery: ZY-3 and GF-1 in Large Areas

In this letter, a new digital elevation model (DEM)-aided bundle block adjustment (BBA) method is proposed which utilizes a rational-polynomial-coefficient affine transformation model and a preconditioned conjugate gradient (PCG) algorithm with multisource satellite imagery (ZY-3 and GF-1) for producing and updating ortho maps of large areas. To deal with the weak geometry of the large blocks, a reference DEM is used in this method as an additional constraint in the BBA. The PCG algorithm is applied to solve the large normal matrix produced by the massive data of the large areas. Our proposed method was tested on three blocks of real data collected by GF-1 panchromatic and multispectral sensors and ZY-3 three-line-camera sensors. The preliminary results show that the proposed method can achieve an accuracy of better than 0.5 pixels in planimetry and is suitable for wide application in ortho-map production. It also has great potential for the ortho-map production of superlarge areas such as the country of China as one block.

An innovative approach to improve SRTM DEM using multispectral imagery and artificial neural network

AbstractAlthough the Shuttle Radar Topography Mission [SRTM) data are a publicly accessible Digital Elevation Model [DEM) provided at no cost, its accuracy especially at forested area is known to be limited with root mean square error (RMSE) of approx. 14 m in Singapore's forested area. Such inaccuracy is attributed to the 5.6 cm wavelength used by SRTM that does not penetrate vegetation well. This paper considers forested areas of central catchment of Singapore as a proof of concept of an approach to improve the SRTM data set. The approach makes full use of (1) the introduction of multispectral imagery (Landsat 8), of 30 m resolution, into SRTM data; (2) the Artificial Neural Network (ANN) to flex its known strengths in pattern recognition and; (3) a reference DEM of high accuracy (1 m) derived through the integration of stereo imaging of worldview‐1 and extensive ground survey points. The study shows a series of significant improvements of the SRTM when assessed with the reference DEM of 2 different areas, with RMSE reduction of ∼68% (from 13.9 m to 4.4 m) and ∼52% (from 14.2 m to 6.7 m). In addition, the assessment of the resulting DEM also includes comparisons with simple denoising methodology (Low Pass Filter) and commercially available product called NEXTMap® World 30™.

Assessment of orthoimage and DEM derived from ZY-3 stereo image in Northeastern China

ZiYuan-3 (ZY-3, meaning Resource-3) is China's first civilian multispectral satellite with high-resolution stereo mapping capability. The along-track stereo images of ZY-3 allow the generation of digital elevation models (DEMs) for various mapping applications. This article evaluated the precision of the derived stereo DEM and orthoimages of ZY-3 data for a test site in Northeastern China. Pixel offset and GPS survey data were used to evaluate the image products. Orthoimages were derived by incorporating rational polynomial coefficients (RPCs) of the satellite orbits and the reference DEMs, including the Advanced Spaceborne Thermal Emission and Reflection Radiomete (ASTER) global digital elevation model (GDEM) and ZY-3 stereo elevation model. The generations of orthoimages were categorised into four approaches depending on the RPCs, control points and/or reference DEMs used. When only the ASTER GDEM was used, the derived orthoimages of the forward and backward viewing sensors showed clear pixel offsets against the GPS check points (CKPs). For example, the offsets of the orthoimage derived using forward-looking image were 13·58 and 26·50 m, in x (easting) and y (northing) directions, respectively. These results also indicated that the pixel offset vectors between the forward and backward orthoimages was systematic which was caused by the error in the RPCs. The second and third approaches were to generate the ZY-3 stereo DEMs first, with and without the use of ground control points (GCPs), and then used the stereo DEMs to generate the orthoimages of the forward and backward looking images. The forth approach used both GCPs and ASTER GDEM to generate the orthoimages. The results showed the use of four GCPs in the process improved the accuracy of the orthoimages. Therefore, ZY-3 can deliver the DEM and orthoimage products to meet the accuracy requirement of the national 1 : 50 000 mapping with four well distributed GCPs.

Method of creating digital terrain models and its practical application as exemplified by Samara region

The article shows that high accuracy is one of the most important elements in the technology of creating such information products as a digital elevation model (DEM) of the terrain, so a reference is to be provided to confirm the accuracy. Unlike the methodological approach based on collecting data on the terrain relief using digitized topographic maps, a procedure is proposed to generate a reference DEM. The procedure provides high accuracy in solving the problem of coordinate referencing of control points due to differential processing of the navigation information obtained with the help of dual-frequency receivers of the geodetic class. In the course of work a technique for obtaining precise contour intervals of the terrain based on a rigidly bound algorithm for combining inertial and satellite measurements providing high-precision solutions even in the temporary absence of satellite signals was developed and experimentally validated. As a result of field and office works conducted in 2013-2015, a reference DEM with a size of about 50 50 km2 was established that made it possible to evaluate the results obtained by DEM space stereo photography and make appropriate corrections in the program and methodical apparatus of Earth remote sensing data processing.

Relative Height Accuracy Estimation Method for InSAR-Based DEMs

Digital elevation models (DEMs) are of fundamental importance for a broad range of commercial and scientific applications. The relative height accuracy of the DEM is one of the most important quality parameters as it refers to the local differences among adjacent elevation values. A direct comparison against a reliable reference DEM is only possible for some single regions where an accurate model similar in resolution is already available. DEMs generated from interferometric synthetic aperture radar (InSAR) can be analyzed with respect to the relative height accuracy based on the data itself. This paper introduces a novel approach to estimate the relative height accuracy. The analysis is based on the well-known statistical characteristics of SAR interferograms and is designed as a specification check for global DEM generation. First results of evaluation of the relative height accuracy are presented for TanDEM-X data.

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.

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.

Evaluation and Validation of Recent Freely-Available ASTER-GDEM V.2, SRTM V.4.1 and the DEM Derived from Topographical Map over SW Grombalia (Test Area) in North East of Tunisia

Digital Elevation Models (DEMs) provide one of the most useful digital datasets for a wide range of users. Both the Shuttle Radar Topographic Mission (STRM V.4.1) topography and the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER-GDEM V.2) have been widely used in geomorphology, hydrology, tectonic, and others since they were made access to the public. The magnitude of vertical errors of two near-global DEMs—SRTM and ASTER-GDEM is compared and validated against a reference DEM which has a relatively high precision of 1:25,000 scale constructed from topographical map. Moreover, the reference DEM, ASTER-GDEM and SRTM were used as basic topographic data to extract some Morphometric index. The parameters like slope and shaded reflectance maps, were derived from the elevation distribution to provide a more sensitive indication of DEM quality. A square area in the North East of Tunisia was selected as a case study to test and evaluate the elevation accuracy of ASTER-GDEM and SRTM. The relative accuracy approach and absolute accuracy were adopted to evaluate global DEMs. The comparisons show that SRTM overestimates and ASTER-GDEM underestimates elevations, both DEMs can be used to extract the elevations of required geometric data, i.e. sub watershed boundaries, drainage information and cross sections. However, small errors still exist in. The lower root mean square errors values indicate that SRTM is comparatively more accurate than ASTER-GDEM.

Investigating Performance Of Airborne Lidar Data Filtering With Triangular Irregular Network (TIN) Algorithm

Abstract. Digital Elevation Model (DEM) is an important topographic product and essential demand for many applications. Traditional methods for creating DEM are very costly and time consuming because of land surveying. In time, Photogrammetry has become one of the major methods to generate DEM. Recently, airborne Light Detection and Ranging (LIDAR) system has become a powerful way to produce a DEM due to advantage of collecting three-dimensional information very effectively over a large area by means of precision and time. Airborne LIDAR system collects information not only from land surface but also from every object between plane and terrain that can reflect the laser beam. So filtering out nonground points from raw point clouds is the major step of DEM generation. There are many filtering algorithm due to several factors that affect the filtering prosedures. The performanses of these filters change based on the topographic features of area.One of these algorithm is called Triangular Irregular Network (TIN). In this study the TIN algorithm is used to filter Lidar point cloud that are collected from two different sites. While one of these sites is a rural area, the other site is an urban area; therefore these sites have different topographic features. In addition, the reference DEMs are available for these sites. In order to test the performance of TIN algorithm, the Lidar point clouds are filtered and used to generate DEM for the sites. Finally, the generated DEM are compared with the reference DEM for each site. The comparison results show that the TIN filtering algorithm perform more effectively in urban area than rural area in terms of correlations with reference DEMs.

A geomorphology-based approach for digital elevation model fusion – case study in Danang city, Vietnam

Abstract. Global digital elevation models (DEM) are considered a source of vital spatial information and find wide use in several applications. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global DEM (GDEM) and Shuttle Radar Topographic Mission (SRTM) DEM offer almost global coverage and provide elevation data for geospatial analysis. However, GDEM and SRTM still contain some height errors that affect the quality of elevation data significantly. This study aims to examine methods to improve the resolution as well as accuracy of available free DEMs by data fusion techniques and evaluating the results with a high-quality reference DEM. The DEM fusion method is based on the accuracy assessment of each global DEM and geomorphological characteristics of the study area. Land cover units were also considered to correct the elevation of GDEM and SRTM with respect to the bare-earth surface. The weighted averaging method was used to fuse the input DEMs based on a landform classification map. According to the landform types, the different weights were used for GDEM and SRTM. Finally, a denoising algorithm (Sun et al., 2007) was applied to filter the output-fused DEM. This fused DEM shows excellent correlation to the reference DEM, having a correlation coefficient R2 = 0.9986, and the accuracy was also improved from a root mean square error (RMSE) of 14.9 m in GDEM and 14.8 m in SRTM to 11.6 m in the fused DEM. The results of terrain-related parameters extracted from this fused DEM such as slope, curvature, terrain roughness index and normal vector of topographic surface are also very comparable to reference data.

Estimation of Mass Balance of the Grosser Aletschgletscher, Swiss Alps, from ICESat Laser Altimetry Data and Digital Elevation Models

Traditional glaciological mass balance measurements of mountain glaciers are a demanding and cost intensive task. In this study, we combine data from the Ice Cloud and Elevation Satellite (ICESat) acquired between 2003 and 2009 with air and space borne Digital Elevation Models (DEMs) in order to derive surface elevation changes of the Grosser Aletschgletscher in the Swiss Alps. Three different areas of the glacier are covered by one nominal ICESat track, allowing us to investigate the performance of the approach under different conditions in terms of ICESat data coverage, and surface characteristics. In order to test the sensitivity of the derived trend in surface lowering, several variables were tested. Employing correction for perennial snow accumulation, footprint selection and adequate reference DEM, we estimated a mean mass balance of −0.92 ± 0.18 m w.e. a−1. for the whole glacier in the studied time period. The resulting mass balance was validated by a comparison with another geodetic approach based on the subtraction of two DEMs for the years 1999 and 2009. It appears that the processing parameters need to be selected depending on the amount of available ICESat measurements, quality of the elevation reference and character of the glacier surface.

Assessment of interferometric dems from terrasar‐x stripmap and spotlight stereopairs: case study in istanbul

AbstractTerraSAR‐X (TSX) has led to a new era for synthetic aperture radar (SAR) imaging, offering high‐resolution (1 m) data that was not previously available from space. The TSX X‐band sensor can be operated in three interferometrically compatible imaging modes: Stripmap (SM), high‐resolution Spotlight (HS) and ScanSAR. Due to the low resolution of ScanSAR (16 to 30 m), SM and HS images are preferred for resolution‐based applications. This paper attempts to validate and compare the digital elevation models (DEMs) derived from TSX SM and HS image pairs. Digital surface models (DSMs) were generated by interferometry in a part of Istanbul with a variety of ground types. These DSMs were converted to DEMs by filtering and then compared with a reference DEM produced from aerial photographs. The quality assessment was performed using advanced analyses concerned with accuracy and morphologic detail. The results of both absolute and relative accuracy analyses clearly reveal that the quality of the TSX HS DEM is better than SM and very consistent with the reference model.

Quantitative assessment of remotely sensed global surface models using various land classes produced from Landsat data in Istanbul

Digital elevation model (DEM) is the most popular product for three-dimensional (3D) digital representation of bare Earth surface and can be produced by many techniques with different characteristics and ground sampling distances (GSD). Space-borne optical and synthetic aperture radar (SAR) imaging are two of the most preferred and modern techniques for DEM generation. Using them, global DEMs that cover almost entire Earth are produced with low cost and time saving processing. In this study, we aimed to assess the Satellite pour l’observation de la Terre-5 (SPOT-5), High Resolution Stereoscopic (HRS), the Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER), and the Shuttle Radar Topography Mission (SRTM) C-band global DEMs, produced with space-borne optical and SAR imaging. For the assessment, a reference DEM derived from 1:1000 scaled digital photogrammetric maps was used. The study is performed in 100 km2 study area in Istanbul including various land classes such as open land, forest, built-up land, scrub and rough terrain obtained from Landsat data. The analyses were realized considering three vertical accuracy types as fundamental, supplemental, and consolidated, defined by national digital elevation program (NDEP) of USA. The results showed that, vertical accuracy of SRTM C-band DEM is better than optical models in all three accuracy types despite having the largest grid spacing. The result of SPOT-5 HRS DEM is very close by SRTM and superior in comparison with ASTER models.