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The primary goal of the German TanDEM-X mission is the generation of a highly accurate and global Digital Elevation Model (DEM) with global accuracies of at least 10 m absolute height ...error (linear 90% error). The global TanDEM-X DEM acquired with single-pass SAR interferometry was finished in September 2016. This paper provides a unique accuracy assessment of the final TanDEM-X global DEM using two different GPS point reference data sets, which are distributed across all continents, to fully characterize the absolute height error. Firstly, the absolute vertical accuracy is examined by about three million globally distributed kinematic GPS (KGPS) points derived from 19 KGPS tracks covering a total length of about 66,000 km. Secondly, a comparison is performed with more than 23,000 “GPS on Bench Marks” (GPS-on-BM) points provided by the US National Geodetic Survey (NGS) scattered across 14 different land cover types of the US National Land Cover Data base (NLCD). Both GPS comparisons prove an absolute vertical mean error of TanDEM-X DEM smaller than ±0.20 m, a Root Means Square Error (RMSE) smaller than 1.4 m and an excellent absolute 90% linear height error below 2 m. The RMSE values are sensitive to land cover types. For low vegetation the RMSE is ±1.1 m, whereas it is slightly higher for developed areas (±1.4 m) and for forests (±1.8 m). This validation confirms an outstanding absolute height error at 90% confidence level of the global TanDEM-X DEM outperforming the requirement by a factor of five. Due to its extensive and globally distributed reference data sets, this study is of considerable interests for scientific and commercial applications.
Geodetic observations for both vertical and horizontal control networks cannot be compromised for any reason in accuracy and precision in the field of geomatics. Due to the error-prone nature of ...survey measurements, standards are established to allow for comparing the obtained results with a set of guidelines, regulations, or pre-determined specifications. The University of Benin’s Ugbowo Campus in Nigeria does not have enough control points, which informs this study. The densification of more reliable control points using the most recent technology is necessary. Before the observations, control network design, excavation, casting, and monumentation of first-order compliance beacons had been completed. Eight GNSS receivers were connected to the CORS_Geosystems multi-link access point and simultaneously deployed for observations. The stages involve the adjustment of observed data, the presentation of adjusted results, and the determination of horizontal and vertical accuracies. The result of horizontal accuracy showed that the RAPH_GNSS_08 station had the highest horizontal accuracy standard ratio of 1:432,193, while the Raph_GNSS_04 station had the lowest, 1:133,271. The highest vertical accuracy standard was 4.0mm, achieved between Cors_Geo and RAPH_GNSS_09, while the lowest, which was 3.1mm, was observed between Cors_Geo and RAPH_GNSS_08. High-precision engineering projects in the research area will benefit from the established first-order controls in terms of execution, monitoring, and maintenance. The Surveyors Council of Nigeria (SURCON) has recommended GNSS as one of the methods for achieving geodetic control densification in Nigeria.
We present an analysis for Peru of the vertical accuracy and derived geomorphological parameters of three, freely available Digital Elevation Models (DEMs) with 30-m grid sizes and one commercially ...available 12-m DEM: ASTER GDEM2, SRTMv3.0 (hereafter called SRTM3), ALOS World 3D (AW3D30) and 12-m TanDEM-X. Their elevation values were compared against values measured with a dual-frequency Trimble 5800 Global Navigation Satellite Systems (GNSS) receiver with two antennas in static relative positioning. A total of 139 ground control points (GCPs) with elevations of up to 4334 m above sea level (asl). were obtained from four topographically contrasting regions along the flat, arid coast, the semi-dry Andes and the Amazon rainforest. The combined results of the four areas showed that the residuals of ASTER GDEM2 had a root mean square error (RMSE) of 6.907 m, SRTM3 5.113 m and AW3D30 6.246 m. For the two areas where TanDEM-X was investigated, a RMSE of 1.666 m was obtained. When considering each area individually, of the three 30-m DEMs, SRTM3 performed best in all areas, while ASTER GDEM2 was always performing worst. The standard deviation (SD) of the residuals of ASTER GDEM2 and AW3D30 varied much more between the four study areas than the SD of SRTM3 and TanDEM-X. It was possible to establish linear correlations with R2 > 0.95 between the GNSS-measured and DEM-derived elevation values for all areas and all DEMs, which can be used to correct ASTER GDEM2 and AW3D30 for Peru. No relationship was found between absolute elevation and residuals. Slope angle of >15°, however, correlated to much higher residuals for SRTM3 and AW3D30, whereas a constant increase in residual correlated to a constant increase in slope angle for TanDEM-X. In general, the highest residuals corresponded to the highest slope classes. A comparison of absolute elevation values and slope angles of selected areas between ASTER GDEM2 and SRTM3, as well as between AW3D30 and SRTM3, showed in all cases more deviation from true values in areas with steeper slopes. This effect seems independent of vegetation. The presence of buildings however, severely affected performance of ASTER GDEM2. For some areas, AW3D30 suffered from mismatch between adjacent scenes and horizontal and oblique stripping. An analysis of drainage networks showed that all three 30-m DEMs were capable of producing a similar number of Strahler orders, total number of channels, minimum and maximum channel length and accumulative channel length. All DEMs produced accurate networks in the upper reaches of the catchments, but suffered in flat areas such as wide fluvial valleys and sink-filled areas. ASTER GDEM2 in particular produced parallel river channels and unnatural short cuts. Our results agreed well with those of other studies elsewhere around the world and showed that i) the vertical error is much less than those officially reported for all DEMs; ii) slope is the most determinant factor in DEM accuracy. We conclude that SRTM3 delivers the most stable performance in almost all tests and is therefore the DEM of choice for landscape analysis in Peru. TanDEM-X 12 m performed very well in our elevation accuracy test and could become a worthy successor to SRTM3.
•One of the few DEM comparison studies available for the South American continent.•Centimetre-precision ground control points of four contrasting areas in Peru.•DEM elevation errors are in the order of metres less than officially reported.•Correlations between DEM and GCP heights can be used to correct DEM values.•Geomorphological and hydrological metrics show strengths and weaknesses of each DEM.
In hydrogeological research, the systematic and periodic measurement of the piezometric level is fundamental to assess aquifer storage, identify recharge and discharge areas, define flow directions ...and to infer the balance between inputs and withdrawals. Furthermore, knowledge of this variable and its fluctuations is essential for the efficient management and protection of groundwater resources. In this work, a novel methodology is proposed for the remote acquisition of piezometric information from traditional large-diameter wells, using drone-borne LiDAR observations. The workflow developed consists of different stages, from flight planning and parameter setting, to point cloud generation, data processing and validation and its statistical treatment to extract piezometric information. This methodology has been applied in a small coastal aquifer with numerous wells that have served as monitoring points. The UAV-LiDAR has enabled the straightforward obtention of measurements of the piezometric level with very high vertical accuracies (RMSE of 5 cm) with minimum and maximum residuals of −8.7 and 7.9 cm respectively. Likewise, the method has shown vertical accuracies 3 times better than those inferred from the official DTM of best resolution available in Spain, which is usually used in hydrogeological works. Since the technique provides absolute values of the piezometric level, it eliminates the need for laborious levelling work prior to hydrogeological campaigns. This method has proved to be an effective alternative/complementary technique to traditional measurements of the piezometric level, allowing to monitor extensive or inaccessible areas over short periods of time and to potentially reduce gaps in hydrogeological databases.
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•A novel hydrogeological application of drone-borne LiDAR remote sensing is presented.•Method for measuring piezometric levels in shallow aquifers with large-diameter wells•UAV-LiDAR observations provide vertical accuracies in the order of 5 cm.•The method avoids the need for previous levelling of observation points.•This technique is a useful alternative to traditional groundwater monitoring works.
Peatlands are a major reservoir of global soil carbon, yet account for just 3% of global land cover. Human impacts like draining can hinder the ability of peatlands to sequester carbon and expose ...their soils to fire under dry conditions. Estimating soil carbon loss from peat fires can be challenging due to uncertainty about pre-fire surface elevations. This study uses multi-temporal LiDAR to obtain pre- and post-fire elevations and estimate soil carbon loss caused by the 2011 Lateral West fire in the Great Dismal Swamp National Wildlife Refuge, VA, USA. We also determine how LiDAR elevation error affects uncertainty in our carbon loss estimate by randomly perturbing the LiDAR point elevations and recalculating elevation change and carbon loss, iterating this process 1000 times. We calculated a total loss using LiDAR of 1.10TgC across the 25km2 burned area. The fire burned an average of 47cm deep, equivalent to 44kgC/m2, a value larger than the 1997 Indonesian peat fires (29kgC/m2). Carbon loss via the First-Order Fire Effects Model (FOFEM) was estimated to be 0.06TgC. Propagating the LiDAR elevation error to the carbon loss estimates, we calculated a standard deviation of 0.00009TgC, equivalent to 0.008% of total carbon loss. We conclude that LiDAR elevation error is not a significant contributor to uncertainty in soil carbon loss under severe fire conditions with substantial peat consumption. However, uncertainties may be more substantial when soil elevation loss is of a similar or smaller magnitude than the reported LiDAR error.
•Multi-temporal LiDAR can provide estimates of soil carbon loss from fire.•1.1 Tg (44kg/m2) soil carbon were burned in a 2011 Virginia, USA peat fire.•Soil loss exceeded 1m in some parts of the drained peatland.•LiDAR elevation error was not a major contributor to uncertainty in carbon loss.
The past two decades have been prolific in production of global or near-global Digital Elevation Models (DEMs) derived from satellite data. The most recent addition to the family of global DEMs is ...the TanDEM-X DEM with resolution of 0.4 arc sec. DEMs are essential for a wide range of environmental applications, many of which are related to mountains including studies on natural hazards, forestry or glacier mass changes. However, synthetic aperture radar interferometry used for acquisition of TanDEM-X DEM is especially challenging over steep and irregular mountain surfaces due to shadowing and foreshortening effects. In this study, we assessed the absolute vertical accuracy of TanDEM-X DEM in European mountains. We compared it with both a Digital Terrain Model (DTM) and a Digital Surface Model (DSM) derived from airborne laser scanning data. Our results indicate that the height error of TanDEM-X DEM expressed as absolute deviation at the 90% quantile is consistent with the 10 m mission specification benchmark. We further concentrated on the absolute height error with respect to environmental characteristics (i.e. forested and non-forested areas, slope, and aspect). The comparison of TanDEM-X DEM with a reference DTM showed a positive vertical offset; however, the mean error differed greatly between forested and non-forested areas. When compared to reference DSM, our results showed a slight underestimation. We observed the highest underestimation in deciduous forests, followed by coniferous forests and non-forested areas. A significant decrease in accuracy was observed with increasing slope, especially for slopes above 10°. In mountains where the imagery was acquired only in one orbit direction (i.e. ascending for Northern hemisphere), the largest TanDEM-X DEM error when compared to DSM was recorded for the west-facing slopes (i.e. slopes facing the sensor); however, the association with terrain orientation diminished in mountains, the imagery of which was acquired from both the ascending and descending orbit. Finally, we evaluated the effect of data acquisition characteristics provided with TanDEM-X DEM as auxiliary data. Our results show that two coverages might not be sufficient in mountain environment. Additional acquisitions, especially those with different acquisition geometry, improved the absolute vertical accuracy of TanDEM-X DEM and eliminated areas of inconsistency. We discourage from using the Height Error Map (HEM) to estimate the error magnitude. On the other hand, auxiliary data (COM, COV) provide valuable information that should be always used in pre-analyses to identify possible problematic areas.
•Results indicate an outstanding absolute height error of TanDEM-X DEM in mountains.•Deciduous and coniferous forests have a profound effect on TANDEM-X DEM error.•Similarly, slope and aspect also affect TanDEM-X DEM accuracy.•Additional acquisitions improved the absolute vertical accuracy of TanDEM-X DEM.•Auxiliary files (COM, COV) provide valuable data that indicate problematic areas.
Vertical Accuracy of Google Earth Data Khalid L. A. El-Ashmawy
Engineering, technology & applied science research,
06/2024, Letnik:
14, Številka:
3
Journal Article
Recenzirano
Odprti dostop
Digital Elevation Models (DEMs) are an important data source used in many engineering and Geographic Information System (GIS) applications. This paper illustrates a strategy for creating a DEM by ...utilizing elevation data from Google Earth and evaluating the vertical positional accuracy of the generated DEM adopting a well-defined methodology. To ensure the accuracy of the elevation data obtained from Google Earth, a thorough evaluation was done in three diverse small districts of the northern shoreline in Egypt. The evaluation process involved determining the ground coordinates of reference points utilizing two surveying techniques: total station and Real-Time Kinematic (RTK) Global Positioning System (GPS) surveys. These coordinates were compared with the ones predicated by the DEM generated by putting into service Google Earth's elevation data. Furthermore, the vertical accuracy was assessed using Shuttle Radar Topographic Mission (SRTM) data of Google Earth collected at two different periods in 2015 and 2023. The vertical accuracy of the Google Earth data is detailed utilizing Mean Error (ME), Maximum Absolute Error (MAE), and Root Mean Square Error (RMSE). According to the results, Google Earth's elevation data accuracy remains consistent from 2015 to 2023, and refining SRTM data does not improve the vertical accuracy. The vertical accuracy of the total station survey surpasses the one of the RTK GPS survey, and the elevation accuracy of the RTK GPS survey decreases with increasing height difference. In addition, the vertical accuracy of DEMs was found to be sufficient for some engineering applications but not accurate enough for precise engineering studies. The accuracy achieved in small height difference terrain can be utilized to produce large-scale cadastral maps, city plans, or land use maps. Finally, the elevation data offered by Google Earth can be utilized for preliminary studies at a low cost. However, to ensure the accuracy of these data, it is recommended that users compare them with reference data before implementation.
ABSTRACTDigital Elevation Models (DEMs) are critical datasets in the field of Earth sciences, essential for accurate measurement and analysis of the Earth's surface. We used ICESat-2 to ...quantitatively evaluate 5 DEMs (ALOS PALSAR, ASTER GDEM V3, COPERNICUS, NASADEM and TanDEM-X) on the Tibetan Plateau. The research findings indicate that the ALOS exhibits the highest level of accuracy, as evidenced by its root mean square error (RMSE) value of 5.05m. It is closely followed by NASA and COP, which have RMSE values of 6.23m and 8.10m, respectively. In contrast, the ASTER and TDX90 demonstrate comparatively lower levels of accuracy, as indicated by their respective RMSE values of 11.47m and 12.32m. It is worth mentioning that the accuracy of DEMs is significantly influenced by land cover, especially during the transition from areas with low vegetation to those with high vegetation. This transition often results in a decrease in accuracy. Furthermore, the accuracy of DEMs tends to decrease with increasing slope values. Aspect exhibits a notable spatial distribution pattern characterized by a "low in the Southwest direction, high in all other directions" phenomenon. This study offers significant contributions to the evaluation of DEMs accuracy and its suitability in the Qinghai-Tibet Plateau.
Digital elevation models (DEMs) are crucial for numerous assessments of the Earth's surface, so this research aim to evaluate the quality of several open source DEMs like advanced spaceborne thermal ...emission and reflection radiometer global DEM (ASTER GDEM), shuttle radar topography mission DEM (SRTM DEM), SENTINEL-1, and TerraSAR-X for digital elevation measurement (TanDEM-X). TanDEM-X is one of the newest DEM models; however, ASTER and SRTM are still the most used. To evaluate the qualities of these DEMs, the vertical accuracies of ASTER, STRM (all 30 m), SRTM, TanDEM-X (90 m), and SENTINEL 1 (range from 5 to 12.5 m) were tested using GPS reference points and The RMSE gave the values of ± 3.56 m ± 57.68 m, ±5.89 m, ±10.21 m and ± 20.25 m for used SRTM1, SENTINEL-1, SRTM3, TanDEM-X, and ASTER DEMs respectively. As is well known, obtaining a high-quality DEM is exceedingly challenging since it is time-consuming, expensive, and often constrained, therefore this study examined how to enhance SRTM1 as it gave the best result and assessed the effects of increasing the number of points on digital elevation model accuracy by using raster calculator and merge model in ArcGIS. The results showed that the merge model method gave the best result and, by increasing the number of reference points, the accuracy increased. The DEM produced by the enhanced SRTM (iSRTM) demonstrated noticeably better outcomes than the baseline SRTM DEM, with around 3.56 m RMSE.In this research, STRM-1 DEM is used to determine watershed basin delineation. The topographic map showed significant variations in the level of the Earth's surface, as the heights of the area ranged between 20 m and 120 m. The number of watersheds extracted in the Benban is 132 with different areas, the large area is about 72.14 km2, while the small area is about 1.13 km2, and between those areas, there are various areas. The largest recorded watershed circumference reached 48.94 km in area (72.14 km2), while the lowest recorded perimeter is 5.40 km for the area (1.13 km2).
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