Vertical Accuracy Assessment Research Articles

VERTICAL ACCURACY ASSESSMENT FOR SRTM V.4 AND ASTER GLOBAL DIGITAL ELEVATION MODELS V.2: A CASE STUDY OF PADANG REGENCY, WEST SUMATERA

<p>Digital elevation model (DEM) is an important element used to represent surface of The Earth. Generally, DEM has been utilized in many geographic science, for instance cartography, hydrology, geology, and remote sensing. It has been widely used since the advanced of technology in remote sensing. This research concerned to assess the vertical accuracy of SRTM v.4 and ASTER GDEM v.2. Topographic or also known as RBI map of Padang City, West Sumatera which has scale 1:10.000 was used as a reference map. RBI has 2.5 m vertical accuracy and 0.5 mm horizontal accuracy. Moreover, to gain the bias value, root mean square errors (RMSE) assessment was used to calculate the different value between them. Point height would be obtained through sampling method based on the distribution of land-use, slope, and relief. Land-use was classified digitally using maximum likelihood method from SPOT 6 imagery, slope and relief that were derived based on the reference map. Vertical accuracy assessment for both DEM was necessary in order to know the bias elevation prior to using them in a research or project. Assessment of DEM vertical accuracy also could help to generate contour in global region which should be used after the bias vertical was applied.</p>Keywords: SRTM v.2, ASTER GDEM v.2, DEM Generation, Accuracy Assessment, RBI Map

ELEVATION-BASED SEA-LEVEL RISE VULNERABILITY ASSESSMENT OF MINDANAO, PHILIPPINES: ARE FREELY-AVAILABLE 30-M DEMS GOOD ENOUGH?

Abstract. We assessed the vertical accuracies and uncertainties of three freely-available global DEMs as inputs to elevation-based sea-level rise vulnerability assessment of Mindanao, Philippines – an area where above average SLR of 14.7 mm/year was recently found. These DEMs are the Shuttle Radar Topography Mission (SRTM) DEM, ASTER Global DEM (GDEM Version 2), and ALOS World 3D-30 (AW3D30). Using 2,076 ground control points, we computed each DEM’s vertical accuracies and uncertainties, and from these we determined the smallest increment of sea-level rise (SLRImin) that should be considered when using the DEMs for SLR impact assessment, as well as the Minimum Planning Timeline (TLmin) for an elevation-based SLR assessment. Results of vertical accuracy assessment revealed Root Mean Square Errors of 9.80 m for ASTER GDEM V2, 5.16 m for SRTM DEM, and 4.32 m for AW3D30. Vertical uncertainties in terms of the Linear Error at 95 % Confidence (LE95) were found to be as follows: 19.21 m for ASTER GDEM V2, 10.12 m for SRTM DEM, and 8.47 m for AW3D30. From these, we found that ASTER GDEM2 is suitable to model SLR increments of at least 38.41 m and it will take 2,613 years for the cumulative water level increase of 14.7 mm/year to reach the minimum SLR increment afforded by this DEM. For the SRTM DEM, SLRImin and TLmin were computed as 20.24 m and 1,377 years, respectively. For the AW3D30, SLRImin and TLmin were computed as 16.92 m and 1,151 years, respectively. These results suggest that the readily available global DEMs' suitability for mapping coastal inundations due to SLR in our study area is limited by their low vertical accuracies and high uncertainties. All the three DEMs do not have the necessary accuracy and minimum uncertainties that will make them suitable for mapping inundations of Mindanao at smaller increments of SLR (e.g., SLR ≤ 5 m). Hence, users who apply any of these DEMs for SLR impact assessment at SLRIs lower than the DEM’s SLRImin must be cautious in reporting the areas of SLR vulnerable zones. Reporting the inundated areas as a range instead of a singular value for a given SLR scenario can highlight the inherent accuracy and uncertainty of the DEM used in the assessment.

A note on methods for vertical accuracy assessment of DEMs

This study investigates the vertical accuracy of a DEMs interpolated from 1:50,000 contours with universal kriging (UK) using DEMs interpolated from 1:10,000 contours as the independent source of higher accuracy following the geospatial accuracy standards proposed by the Federal Geographic Data Committee, FGDC, (1998). In accordance with the standards, the 1:10,000 contours do not qualify as well-defined points with known horizontal position and a high degree of accuracy that are easily visible and recoverable on the ground. Hence, DEMs are created from the 1:10,000 contours and used to check the vertical accuracy of the 1:50,000 DEMs with elevation errors, an RMSE and vertical accuracy measure calculated between the 1:10,000 and 1:50,000 DEMs. Other methods of vertical accuracy assessment for the 1:50,000 DEMs include a comparison of elevation ranges, visualization of error surfaces and latitudinal and longitudinal terrain profiles..

Vertical accuracy assessment for SRTM and ASTER Digital Elevation Models: A case study of Najran city, Saudi Arabia

Abstract Digital Elevation Model is imperative to many earth surface process analyses. In this study, the quality of DEMs acquired by SRTM ver.3 and ASTER ver.2 is evaluated. The reference levels produced from GPS elevations, and the topographic map is used to assess the vertical accuracy of SRTM and ASTAR DEMs in Najran city, Saudi Arabia. The GPS reference elevations gave us the values of ±5.94 m and ±5.07 m for used SRTM and ASTER DEMs. Also, by using elevation from the topographic map as a reference elevations the obtained accuracy was ±6.87 m and ±7.97 m for SRTM and ASTER DEMs. For our study area, the 30 m SRTM elevations data featured a much greater absolute vertical accuracy than the absolute vertical accuracy value of ±16 m, which published in the SRTM data specification.

Evaluation of Vertical Accuracy of the WorldDEM™ Using the Runway Method

Accuracy assessment of a global digital elevation model (DEM) is an important and challenging task primarily because of the difficulties and costs associated with securing a reliable and representative reference dataset. In this article, we report on the vertical accuracy assessment of the WorldDEM™, the latest global DEM using the synthetic aperture radar interferometry (InSAR) method, based on the German TanDEM-X mission data. For reference data we use vertical profiles along the centerline of 47 paved runways located in different areas around the world. Our accuracy statement is based on the analysis of discrepancies between the reference data and the corresponding vertical profiles extracted from the WorldDEM™ dataset. Since the runways are nearly flat and have homogenous surfaces, the observed discrepancies are mainly due to instrument-induced error. Therefore, the derived accuracy statement has a universal character, e.g., it is not biased by other error sources including target- or environment-induced errors. Our main conclusions are that the WorldDEM™ is the most accurate global DEM to date in terms of its vertical accuracy; it appears that the accuracy is spatially independent.

VERTICAL ACCURACY ASSESSMENT OF 30-M RESOLUTION ALOS, ASTER, AND SRTM GLOBAL DEMS OVER NORTHEASTERN MINDANAO, PHILIPPINES

Abstract. The ALOS World 3D – 30 m (AW3D30), ASTER Global DEM Version 2 (GDEM2), and SRTM-30 m are Digital Elevation Models (DEMs) that have been made available to the general public free of charge. An important feature of these DEMs is their unprecedented horizontal resolution of 30-m and almost global coverage. The very recent release of these DEMs, particularly AW3D30 and SRTM- 30 m, calls for opportunities for the conduct of localized assessment of the DEM’s quality and accuracy to verify their suitability for a wide range of applications in hydrology, geomorphology, archaelogy, and many others. In this study, we conducted a vertical accuracy assessment of these DEMs by comparing the elevation of 274 control points scattered over various sites in northeastern Mindanao, Philippines. The elevations of these control points (referred to the Mean Sea Level, MSL) were obtained through 3rd order differential levelling using a high precision digital level, and their horizontal positions measured using a global positioning system (GPS) receiver. These control points are representative of five (5) land-cover classes namely brushland (45 points), built-up (32), cultivated areas (97), dense vegetation (74), and grassland (26). Results showed that AW3D30 has the lowest Root Mean Square Error (RMSE) of 5.68 m, followed by SRTM-30 m (RMSE = 8.28 m), and ASTER GDEM2 (RMSE = 11.98 m). While all the three DEMs overestimated the true ground elevations, the mean and standard deviations of the differences in elevations were found to be lower in AW3D30 compared to SRTM-30 m and ASTER GDEM2. The superiority of AW3D30 over the other two DEMS was also found to be consistent even under different landcover types, with AW3D30's RMSEs ranging from 4.29 m (built-up) to 6.75 m (dense vegetation). For SRTM-30 m, the RMSE ranges from 5.91 m (built-up) to 10.42 m (brushland); for ASTER GDEM2, the RMSE ranges from 9.27 m (brushland) to 14.88 m (dense vegetation). The results of the vertical accuracy assessment suggest that the AW3D30 is more accurate than SRTM-30 m and ASTER GDEM2, at least for the areas considered in this study. On the other hand, the tendencies of the three DEMs to overestimate true ground elevation can be considered an important finding that users of the DEMs in the Philippines should be aware of, and must be considered into decisions regarding use of these data products in various applications.

VERTICAL ACCURACY ASSESSMENT OF 30-M RESOLUTION ALOS, ASTER, AND SRTM GLOBAL DEMS OVER NORTHEASTERN MINDANAO, PHILIPPINES

The ALOS World 3D – 30 m (AW3D30), ASTER Global DEM Version 2 (GDEM2), and SRTM-30 m are Digital Elevation Models (DEMs) that have been made available to the general public free of charge. An important feature of these DEMs is their unprecedented horizontal resolution of 30-m and almost global coverage. The very recent release of these DEMs, particularly AW3D30 and SRTM- 30 m, calls for opportunities for the conduct of localized assessment of the DEM’s quality and accuracy to verify their suitability for a wide range of applications in hydrology, geomorphology, archaelogy, and many others. In this study, we conducted a vertical accuracy assessment of these DEMs by comparing the elevation of 274 control points scattered over various sites in northeastern Mindanao, Philippines. The elevations of these control points (referred to the Mean Sea Level, MSL) were obtained through 3rd order differential levelling using a high precision digital level, and their horizontal positions measured using a global positioning system (GPS) receiver. These control points are representative of five (5) land-cover classes namely brushland (45 points), built-up (32), cultivated areas (97), dense vegetation (74), and grassland (26). Results showed that AW3D30 has the lowest Root Mean Square Error (RMSE) of 5.68 m, followed by SRTM-30 m (RMSE = 8.28 m), and ASTER GDEM2 (RMSE = 11.98 m). While all the three DEMs overestimated the true ground elevations, the mean and standard deviations of the differences in elevations were found to be lower in AW3D30 compared to SRTM-30 m and ASTER GDEM2. The superiority of AW3D30 over the other two DEMS was also found to be consistent even under different landcover types, with AW3D30's RMSEs ranging from 4.29 m (built-up) to 6.75 m (dense vegetation). For SRTM-30 m, the RMSE ranges from 5.91 m (built-up) to 10.42 m (brushland); for ASTER GDEM2, the RMSE ranges from 9.27 m (brushland) to 14.88 m (dense vegetation). The results of the vertical accuracy assessment suggest that the AW3D30 is more accurate than SRTM-30 m and ASTER GDEM2, at least for the areas considered in this study. On the other hand, the tendencies of the three DEMs to overestimate true ground elevation can be considered an important finding that users of the DEMs in the Philippines should be aware of, and must be considered into decisions regarding use of these data products in various applications.

VALIDATION OF THE ASTER GLOBAL DIGITAL ELEVATION MODEL VERSION 3 OVER THE CONTERMINOUS UNITED STATES

The ASTER Global Digital Elevation Model Version 3 (GDEM v3) was evaluated over the conterminous United States in a manner similar to the validation conducted for the original GDEM Version 1 (v1) in 2009 and GDEM Version 2 (v2) in 2011. The absolute vertical accuracy of GDEM v3 was calculated by comparison with more than 23,000 independent reference geodetic ground control points from the U.S. National Geodetic Survey. The root mean square error (RMSE) measured for GDEM v3 is 8.52 meters. This compares with the RMSE of 8.68 meters for GDEM v2. Another important descriptor of vertical accuracy is the mean error, or bias, which indicates if a DEM has an overall vertical offset from true ground level. The GDEM v3 mean error of −1.20 meters reflects an overall negative bias in GDEM v3. The absolute vertical accuracy assessment results, both mean error and RMSE, were segmented by land cover type to provide insight into how GDEM v3 performs in various land surface conditions. While the RMSE varies little across cover types (6.92 to 9.25 meters), the mean error (bias) does appear to be affected by land cover type, ranging from −2.99 to +4.16 meters across 14 land cover classes. These results indicate that in areas where built or natural aboveground features are present, GDEM v3 is measuring elevations above the ground level, a condition noted in assessments of previous GDEM versions (v1 and v2) and an expected condition given the type of stereo-optical image data collected by ASTER. GDEM v3 was also evaluated by differencing with the Shuttle Radar Topography Mission (SRTM) dataset. In many forested areas, GDEM v3 has elevations that are higher in the canopy than SRTM. The overall validation effort also included an evaluation of the GDEM v3 water mask. In general, the number of distinct water polygons in GDEM v3 is much lower than the number in a reference land cover dataset, but the total areas compare much more closely.

VALIDATION OF THE ASTER GLOBAL DIGITAL ELEVATION MODEL VERSION 3 OVER THE CONTERMINOUS UNITED STATES

Abstract. The ASTER Global Digital Elevation Model Version 3 (GDEM v3) was evaluated over the conterminous United States in a manner similar to the validation conducted for the original GDEM Version 1 (v1) in 2009 and GDEM Version 2 (v2) in 2011. The absolute vertical accuracy of GDEM v3 was calculated by comparison with more than 23,000 independent reference geodetic ground control points from the U.S. National Geodetic Survey. The root mean square error (RMSE) measured for GDEM v3 is 8.52 meters. This compares with the RMSE of 8.68 meters for GDEM v2. Another important descriptor of vertical accuracy is the mean error, or bias, which indicates if a DEM has an overall vertical offset from true ground level. The GDEM v3 mean error of −1.20 meters reflects an overall negative bias in GDEM v3. The absolute vertical accuracy assessment results, both mean error and RMSE, were segmented by land cover type to provide insight into how GDEM v3 performs in various land surface conditions. While the RMSE varies little across cover types (6.92 to 9.25 meters), the mean error (bias) does appear to be affected by land cover type, ranging from −2.99 to +4.16 meters across 14 land cover classes. These results indicate that in areas where built or natural aboveground features are present, GDEM v3 is measuring elevations above the ground level, a condition noted in assessments of previous GDEM versions (v1 and v2) and an expected condition given the type of stereo-optical image data collected by ASTER. GDEM v3 was also evaluated by differencing with the Shuttle Radar Topography Mission (SRTM) dataset. In many forested areas, GDEM v3 has elevations that are higher in the canopy than SRTM. The overall validation effort also included an evaluation of the GDEM v3 water mask. In general, the number of distinct water polygons in GDEM v3 is much lower than the number in a reference land cover dataset, but the total areas compare much more closely.

Vertical Accuracy Assessment of SRTM Ver 4.1 and ASTER GDEM Ver 2 Using GPS Measurements in Central West of Tunisia

This paper focuses on the quality of the vertical accuracy of two Digital Elevation Models, corresponding to Kasserine region, central west Tunisia. The vertical accuracy assessment is based on 23 GPS ground control points belonging to the study area. We applied a statistic analysis approach and established 3 elevation profiles corresponding to GPS, ASTER and SRTM. The erected statistical analysis reveals that the Root Mean Squared Error (RMSE) was 8.88 and 10.13 respectively for SRTM and ASTER DTMs. 2D elevation profiles constructed for GPS measurements, ASTER and SRTM, highlight that both DTMs underestimate the true elevation and that SRTM DTM is quite closer to the GPS elevation profile. Relying on this investigation, we think that both DTMs are significant for the vertical accuracy assessment and we urge that SRTM DTM might scheme the Kasserine area features better than ASTER DTM.

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.

Quality assessment from a hydrological perspective of a digital elevation model derived from WorldView-2 remote sensing data

A digital elevation model (DEM) derived from a stereo pair of WorldView-2 (WV-2) images was assessed against ground-truth GPS point datasets. Two assessment methods were used: (a) vertical accuracy assessment and (b) hydrological assessment of surface runoff variables. Three agricultural plots with different topographic slopes were selected to perform a vertical accuracy assessment, followed by a comparative assessment of a set of hydrological variables. The results show an overall vertical accuracy of 0.45 m, confirming the potential of WV-2 stereo images to extract elevation information at high spatial resolution. Concerning plot-scale micro-topographic features, the WV-2 DEM performed better on the plot with rolling slopes (5–10%), extracting variables such as the total length and drainage area of flow paths with relative errors lower than 20%. However, some limitations were detected in the extraction of variables such as terrain slope, drainage points of flow paths and terrain depressions in areas of flatter slopes (<5%).Editor Z.W. Kundzewicz; Associate editor D. Gerten

A comparative appraisal of hydrological behavior of SRTM DEM at catchment level

• SRTM DEM has vertically accuracy (±27.58 m) less than specified standard (±16 m). • Terrain analysis indicates that SRTM DEM and TOPO DEM are hydrological different. • SRTM DEM shows a significantly higher sediment yield with lower prediction accuracy. • SRTM and TOPO DEMs have moderate variation for predicted runoff values. • Sediment yield is more sensitive to choice of DEM in comparison to runoff estimation. The Shuttle Radar Topography Mission (SRTM) data has emerged as a global elevation data in the past one decade because of its free availability, homogeneity and consistent accuracy compared to other global elevation dataset. The present study explores the consistency in hydrological behavior of the SRTM digital elevation model (DEM) with reference to easily available regional 20 m contour interpolated DEM (TOPO DEM). Analysis ranging from simple vertical accuracy assessment to hydrological simulation of the studied Maithon catchment, using empirical USLE model and semidistributed, physical SWAT model, were carried out. Moreover, terrain analysis involving hydrological indices was performed for comparative assessment of the SRTM DEM with respect to TOPO DEM. Results reveal that the vertical accuracy of SRTM DEM (±27.58 m) in the region is less than the specified standard (±16 m). Statistical analysis of hydrological indices such as topographic wetness index (TWI), stream power index (SPI), slope length factor (SLF) and geometry number (GN) shows a significant differences in hydrological properties of the two studied DEMs. Estimation of soil erosion potentials of the catchment and conservation priorities of microwatersheds of the catchment using SRTM DEM and TOPO DEM produce considerably different results. Prediction of soil erosion potential using SRTM DEM is far higher than that obtained using TOPO DEM. Similarly, conservation priorities determined using the two DEMs are found to be agreed for only 34% of microwatersheds of the catchment. ArcSWAT simulation reveals that runoff predictions are less sensitive to selection of the two DEMs as compared to sediment yield prediction. The results obtained in the present study are vital to hydrological analysis as it helps understanding the hydrological behavior of the DEM without being influenced by the model structural as well as parameter uncertainty. It also reemphasized that SRTM DEM can be a valuable dataset for hydrological analysis provided any error/uncertainty therein is being properly evaluated and characterized.

Standardization of figures and assessment procedures for DTM verticalaccuracy

Digital Terrain Models (DTMs) are widely used in many sectors. They play a key role in hydrological risk prevention, risk mitigation and numeric simulations. This paper deals with two questions: (i) when it is stated that a DTM has a given vertical accuracy, is this assertion univocal? (ii) when DTM vertical accuracy is assessed by means of checkpoints, does their location influence results? First, the paper illustrates that two vertical accuracy definitions are conceivable: Vertical Accuracy at the Nodes (VAN, the average vertical distance between the model and the terrain, evaluated at the DTM's nodes) and Vertical Accuracy at the interpolated Points (VAP, in which the vertical distance is evaluated at the generic points). These two quantities are not coincident and, when they are calculated for the same DTM, different numeric values are reached. Unfortunately, the two quantities are often interchanged, but this is misleading. Second, the paper shows a simulated example of a DTM vertical accuracy assessment, highlighting that the checkpoints’ location plays a key role: when checkpoints coincide with the DTM nodes, VAN is estimated; when checkpoints are randomly located, VAP is estimated, instead. Third, an in-depth, theoretical characterization of the two considered quantities is performed, based on symbolic computation, and suitable standardization coefficients are proposed. Finally, our discussion has a well-defined frame: it doesn't deal with all the items of the DTM vertical accuracy budget, which would require a much longer essay, but only with one, usually called fundamental vertical accuracy.

Extraction of High Resolution DEM from Cartosat-1 Stereo Imagery using Rational Math Model and Its Accuracy Assessment for a Part of Snow Covered NW-Himalaya

This paper reports the experiments carried out for extraction of DEMs from Cartosat-1 stereo imagery using stereo correlation technique for Manali region. The focus of this paper was to assess the accuracy of extracted DEM with respect to DGPS observations, DEM generated from digitized contours of Survey of India (SoI), 1:50,000 scale topographic map(converted to ellipsoidal height using egm2008 geoid model) as well as well-known freely available DEMs ASTER GDEM and SRTM. The vertical accuracy of Cartosat-1 DEMs was analysed with DGPS derived ground control points. The relative vertical accuracy (root mean square error; RMSE) of Cartosat-1 DEM with DGPS control points was ±9.6 m. The RMSE with the topographic DEM was found to be ±10.6 for 22 spot heights and ±10.8 m for 6,458,800 checkpoints. The relative vertical accuracy assessment is more important than the absolute vertical accuracy assessment. The result of relative accuracy assessment of DEMs with respect to field measurement of DGPS points and reference DEMs shows Cartosat-1 DEM is more accurate when compared to ASTER DEM, SoI Topographic DEM, and SRTM DEM for Manali region.

Toward a Method of Constructing Tidal Flat Digital Elevation Models with MODIS and Medium-Resolution Satellite Images

ABSTRACT Liu, Y.; Li, M.; Mao, L.; Cheng, L., and Li, F., 2013. Toward a method of constructing tidal flat digital elevation models with MODIS and medium-resolution satellite images. The terrain of tidal flats often varies remarkably over space and time, but few existing methods are capable of producing fine–spatiotemporal resolution digital elevation models (DEMs) for tidal flats. This research aims to fill the knowledge gap and propose a 6-step method to construct tidal flat DEMs by incorporating both moderate-resolution imaging spectroradiometer and medium-resolution satellite images. The six steps include: waterline extraction, water level simulation, height assignment, median filtering, waterline point fusion, and interpolation to DEMs. A case study was conducted at the Dongsha sandbank—one of the largest sandbanks among the radial tidal sand ridges of Jiangsu Province, China. The resultant DEMs were compared with the light detection and ranging–based DEMs for vertical accuracy assessment. The result...

VALIDATION OF THE ASTER GLOBAL DIGITAL ELEVATION MODEL VERSION 2 OVER THE CONTERMINOUS UNITED STATES

Abstract. The ASTER Global Digital Elevation Model Version 2 (GDEM v2) was evaluated over the conterminous United States in a manner similar to the validation conducted for the original GDEM Version 1 (v1) in 2009. The absolute vertical accuracy of GDEM v2 was calculated by comparison with more than 18,000 independent reference geodetic ground control points from the National Geodetic Survey. The root mean square error (RMSE) measured for GDEM v2 is 8.68 meters. This compares with the RMSE of 9.34 meters for GDEM v1. Another important descriptor of vertical accuracy is the mean error, or bias, which indicates if a DEM has an overall vertical offset from true ground level. The GDEM v2 mean error of –0.20 meters is a significant improvement over the GDEM v1 mean error of –3.69 meters. The absolute vertical accuracy assessment results, both mean error and RMSE, were segmented by land cover to examine the effects of cover types on measured errors. The GDEM v2 mean errors by land cover class verify that the presence of aboveground features (tree canopies and built structures) cause a positive elevation bias, as would be expected for an imaging system like ASTER. In open ground classes (little or no vegetation with significant aboveground height), GDEM v2 exhibits a negative bias on the order of 1 meter. GDEM v2 was also evaluated by differencing with the Shuttle Radar Topography Mission (SRTM) dataset. In many forested areas, GDEM v2 has elevations that are higher in the canopy than SRTM.

Approximation Theory Applied to DEM Vertical Accuracy Assessment

AbstractExisting research on DEM vertical accuracy assessment uses mainly statistical methods, in particular variance and RMSE which are both based on the error propagation theory in statistics. This article demonstrates that error propagation theory is not applicable because the critical assumption behind it cannot be satisfied. In fact, the non‐random, non‐normal, and non‐stationary nature of DEM error makes it very challenging to apply statistical methods. This article presents approximation theory as a new methodology and illustrates its application to DEMs created by linear interpolation using contour lines as the source data. Applying approximation theory, a DEM's accuracy is determined by the largest error of any point (not samples) in the entire study area. The error at a point is bounded by max(|δnode|+M2h2/8) where |δnode| is the error in the source data used to interpolate the point, M2 is the maximum norm of the second‐order derivative which can be interpreted as curvature, and h is the length of the line on which linear interpolation is conducted. The article explains how to compute each term and illustrates how this new methodology based on approximation theory effectively facilitates DEM accuracy assessment and quality control.

Thematic information content assessment of the ASTER GDEM: a case study of watershed delineation in West Java, Indonesia

This study assesses the thematic information content using subwatershed boundaries mapped using advanced spaceborne thermal emission and reflection (ASTER) global digital elevation model (GDEM), shuttle radar topography mission (SRTM) DEM and a topographic map (Topo-DEM), and verifies the absolute elevation accuracy by the use of a real-time kinematic differential global positioning system (RTK-DGPS) survey. Subwatershed boundaries extracted from the three different DEMs exhibit a high degree of congruency especially in upstream areas. In these areas, SRTM exhibits lower root mean square errors (RMSEs) than the ASTER GDEM. The discrepancies were larger at lower altitudes. The vertical accuracy assessment using the RTK-DGPS data showed strong correlation with the three DEMs at some stations but the accuracy varied from one area to another. The ASTER GDEM and SRTM had lower accuracy than the Topo-DEM due to the influence of artefacts as shown by their total average RMSE (4.42, 3.30 and 3.13 m, respectively). The average RMSE values also indicate that SRTM is comparatively more accurate than ASTER GDEM.

Generation and evaluation of multitemporal digital terrain models of the Mt. Everest area from different optical sensors

Multitemporal digital terrain models (DTM) are an important source for many purposes such as the detection of areas, which are susceptible to natural hazards such as landslides and glacial lake outburst floods, or for the examination of changes in glacier thickness. To exploit the potential of stereo satellite and aerial imagery for time series analysis, the employed methodology and software can be critical. A statistical analysis based on quartiles is presented to eliminate the influence of registration and elevation errors in DTMs. For our analysis, we used multi-temporal airborne and spaceborne stereoscopic images. The oldest images were recorded in the 1960s by the US American reconnaissance satellite Corona, while the most recent imagery are 2007 Cartosat-1 stereo scenes, along with one ASTER stereo pair. Complex panoramic distortion and limited spatial resolution resulted in the Corona and ASTER DTMs having the highest RMSEz. Due to differing acquisition techniques, applied software packages and temporal differences DTMs will never be identical. Therefore, we propose a relative vertical accuracy assessment with a master DTM. We chose the Cartosat-1 DTM as it showed the highest absolute accuracy. Inaccuracies between the master and the slave DTMs were adjusted by means of trend surfaces and outliers were successfully eliminated applying the interquartile range.