scholarly journals Assessing the influence of DEM source on derived streamline and catchment boundary accuracy

Water SA ◽  
2019 ◽  
Vol 45 (4 October) ◽  
Author(s):  
Zama Eric Mashimbye ◽  
Willem Petrus De Clercq ◽  
Adriaan Van Niekerk

Accurate DEM-derived streamlines and catchment boundaries are essential for hydrological modelling. Due to the popularity of hydrological parameters derived mainly from free DEMs, it is essential to investigate the accuracy of these parameters. This study compared the spatial accuracy of streamlines and catchment boundaries derived from available digital elevation models in South Africa. Two versions of Stellenbosch University DEMs (SUDEM5 and DEMSA2), the second version of the 30 m advanced spaceborne thermal emission and reflection radiometer global digital elevation model (ASTER GDEM2), the 30 and 90 m shuttle radar topography mission (SRTM30 and SRTM90 DEM), and the 90 m Water Research Commission DEM (WRC DEM) were considered. As a reference, a 1 m GEOEYE DEM was generated from GeoEye stereo images. Catchment boundaries and streamlines were extracted from the DEMs using the Arc Hydro module. A reference catchment boundary was generated from the GEOEYE DEM and verified during field visits. Reference streamlines were digitised at a scale of 1:10 000 from the 1 m orthorectified GeoEye images. Visual inspection, as well as quantitative measures such as correctness index, mean absolute error, root mean squares error and figure of merit index were used to validate the results. The study affirmed that high resolution (<30 m) DEMs produce more accurate parameters and that DEM source and resampling techniques also play a role. However, if high resolution DEMs are not available, the 30 m SRTM DEM is recommended as its vertical accuracy was relatively high and the quality of the streamlines and catchment boundary was good. In addition, it was found that the novel Euclidean distance-based MAE and RMSE proposed in this study to compare reference and DEM-extracted raster datasets of different resolutions is a more reliable indicator of geometrical accuracy than the correctness and figure of merit indices.

2019 ◽  
Author(s):  
Giuseppe Amatulli ◽  
Daniel McInerney ◽  
Tushar Sethi ◽  
Peter Strobl ◽  
Sami Domisch

Topographical relief is composed of the vertical and horizontal variations of the Earth's terrain and drives processes in geography, climatology, hydrology, and ecology. Its assessment and characterisation is fundamental for various types of modelling and simulation analyses. In this regard, the Multi-Error-Removed Improved Terrain (MERIT) Digital Elevation Model (DEM) is the best global, high-resolution DEM currently available at a 3 arc-seconds (90 m) resolution. This is an improved product as multiple error components have been corrected from the underlying Shuttle Radar Topography Mission (SRTM3) and ALOS World 3D - 30 m (AW3D30) DEMs. To depict topographical variations worldwide, we developed the Geomorpho90m dataset comprising of different geomorphometry features derived from the MERIT-DEM. The fully standardised geomorphometry variables consist of layers that describe (i) the rate of change using the first and second order derivatives, (ii) the ruggedness, and (iii) the geomorphology landform. To assess how remaining artefacts in the MERIT-DEM could affect the derived topographic variables, we compared our results with the same variables generated using the 3D Elevation Program (3DEP) DEM, which is the highest quality DEM for the United States of America. We compared the two data sources by calculating the first order derivative (i.e., the rate of change through space measured in degrees) of the difference between a MERIT-derived vs. a 3DEP-derived topographic variable. All newly-created topographic variables are readily available at resolutions of 3 and 7.5 arc-seconds under the WGS84 geographic system, and at a spatial resolution of 100 m under the Equi7 projection. The newly-developed Geomorpho90m dataset provides a globally standardised dataset for environmental models and analyses in the field of geography, geology, hydrology, ecology and biogeography.


2010 ◽  
Vol 7 (1) ◽  
pp. 135-177
Author(s):  
M. El Haj Tahir ◽  
A. Kääb ◽  
C.-Y. Xu

Abstract. This paper is part of a set of studies to evaluate the spatial and temporal variability of soil water in terms of natural as well as land-use changes as fundamental factors for vegetation regeneration in arid ecosystems in the Blue Nile-Sudan. The specific aim is to indicate the spatial distribution of soil erosion caused by the rains of 2006. The current study is conducted to determine whether automatic classification of multispectral Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER) imagery could accurately discriminate erosion gullies. Shuttle Radar Topography Mission (SRTM) is used to orthoproject ASTER data. A maximum likelihood classifier is trained with four classes, Gullies, Flat_Land, Mountains and Water and applied to images from March and December 2006. Validation is done with field data from December and January 2006/2007, and using drainage network analysis of SRTM digital elevation model. The results allow the identification of erosion gullies and subsequent estimation of eroded area. Consequently the results were up-scaled using Moderate Resolution Imaging Spectroradiometer (MODIS) images of the same dates. Because the selected study site is representative of the wider Blue Nile province, it is expected that the approach presented could be applied to larger areas.


Author(s):  
Hailu Zewde Abili

DEM can be generated from a wide range of sources including land surveys, Photogrammetry, and Remote sensing satellites. SRTM 30m DEM by The Shuttle Radar Topography Mission (SRTM), the Global Digital Elevation Model by Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER GDEM) and a global surface model called ALOS Worldview 3D 30 meter (AW3D30) by Advanced Land Observing Satellite (ALOS) are satellite-based global DEMs open-source DEM datasets. This study aims to assess the vertical accuracy of ASTER GDEM2, SRTM 30m, and ALOS (AW3D30) global DEMs over Ethiopia in the study area-Adama by using DGPS points and available accurate reference DEM data. The method used to evaluate the vertical accuracy of those DEMs ranges from simple visual comparison to relative and absolute comparisons providing quantitative assessment (Statistical) that used the elevation differences between DEM datasets and reference datasets. The result of this assessment showed better accuracy of SRTM 30m DEM (having RMSE of ± 4.63 m) and closely followed by ALOS (AW3D30) DEM which scored RMSE of ± 5.25 m respectively. ASTER GDEM 2 showed the least accuracy by scoring RMSE of ± 11.18 m in the study area. The second accuracy assessment was done by the analysis of derived products such as slope and drainage networks. This also resulted in a better quality of DEM derived products for SRTM than ALOS DEM and ASTER GDEM.


Author(s):  
Bambang Trisakti ◽  
Ita Carolita ◽  
Firsan Ardi Pradana

Digital Elevation Model (DEM) is a source to produce contour map, slope, and aspect information, which is needed for other information such as disaster and water resources management. DEM can be generated by several methods. One of them is parallax calculations from stereoscopic data of optical sensor. Panchromatic Remote-Sensing Instrument for Stereo Mapping (PRISM) sensor from Advanced LAnd Observation Satellite (ALOS) satellite and advance space borne Thermal Emission and Reflection Radiometer (ASTER) sensor from Terra Satellite is Japanese optical satellite sensor which have abilityto produce stereoscopic data. This study showed DEM generations from PRISM (2.5 m spatial resolution) and ASTER (15m spatial resolution) stereoscopic data using image matching and collinear model based on Orthobase-pro software. The Generated DEM from each sensor was compared to the DEM from Shuttle Radar Topography Mission (SRTM) X-C band with 30 m spatial resolution. The dependent on the pixel size from the DEM produced were also discussed. The result showed that both DEMs have similiar elevation and distribution pattern to the referenced DEM, but DEM for PRISM had higher relative accuracy (RMSE is 6.5 m) and Smoother pattern comparing to DEM from ASTER (RMSE is 10.2 m) Keyword : ASTER, DEM, PRISM, SRTM, Stereoscopic satellite data


Author(s):  
C. C. Carabajal ◽  
J.-P. Boy

We have used a set of Ground Control Points (GCPs) derived from altimetry measurements from the Ice, Cloud and land Elevation Satellite (ICESat) to evaluate the quality of the 30 m posting ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) Global Digital Elevation Model (GDEM) V3 elevation products produced by NASA/METI for Greenland and Antarctica. These data represent the highest quality globally distributed altimetry measurements that can be used for geodetic ground control, selected by applying rigorous editing criteria, useful at high latitudes, where other topographic control is scarce. Even if large outliers still remain in all ASTER GDEM V3 data for both, Greenland and Antarctica, they are significantly reduced when editing ASTER by number of scenes (N≥5) included in the elevation processing. For 667,354 GCPs in Greenland, differences show a mean of 13.74 m, a median of -6.37 m, with an RMSE of 109.65 m. For Antarctica, 6,976,703 GCPs show a mean of 0.41 m, with a median of -4.66 m, and a 54.85 m RMSE, displaying smaller means, similar medians, and less scatter than GDEM V2. Mean and median differences between ASTER and ICESat are lower than 10 m, and RMSEs lower than 10 m for Greenland, and 20 m for Antarctica when only 9 to 31 scenes are included.


2019 ◽  
Vol 25 (8) ◽  
pp. 100-112
Author(s):  
Raghad Hadi Hasan

This study aims to estimate the accuracy of digital elevation models (DEM) which are created with exploitation of open source Google Earth data and comparing with the widely available DEM datasets, Shuttle Radar Topography Mission (SRTM), version 3, and Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM), version 2. The GPS technique is used in this study to produce digital elevation raster with a high level of accuracy, as reference raster, compared to the DEM datasets. Baghdad University, Al Jadriya campus, is selected as a study area. Besides, 151 reference points were created within the study area to evaluate the results based on the values of RMS.Furthermore, the Geographic Information System (GIS) was utilized to analyze, imagine and interpolate data in this study. The result of the statistical analysis revealed that RMSE of DEM related to the differences between the reference points and Google Earth, SRTM DEM and ASTER GDEM are 6.9, 5.5 and 4.8, respectively. What is more, a finding of this study shows convergence the level of accuracy for all open sources used in this study.  


Author(s):  
J. Takaku ◽  
T. Tadono ◽  
M. Doutsu ◽  
F. Ohgushi ◽  
H. Kai

Abstract. In 2016, the first processing of the semi-global digital surface models (DSMs) utilizing all the archives of stereo imageries derived from the Panchromatic Remote sensing Instrument for Stereo Mapping (PRISM) onboard the Advanced Land Observing Satellite (ALOS) was successfully completed. The dataset was freely released to the public in 30 m grid spacing as the ‘ALOS World 3D - 30m (AW3D30)’, which was generated from its original version processed in 5 m or 2.5 m grid spacing. The dataset has been updated since then to improve the absolute/relative height accuracies with additional calibrations. However, the most significant update that should be applied for improving the data usability is the filling of void areas, which correspond to approx. 10% of semiglobal coverage, mostly due to cloud covers. In 2020, we completed the filling process by using other open-access digital elevation models (DEMs) such as Shuttle Radar Topography Mission (SRTM) DEM, Advanced Spaceborne Thermal Emission and Reflection Radiometer Global DEM (ASTER GDEM), ArcticDEM, etc., except for Antarctica. In this paper, we report on the filling process of the remaining voids in Antarctica by using other open-access DEMs such as Reference Elevation Model of Antarctica (REMA) DSM, TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X, TDX) 90m DEM, and ASTER GDEM to complete the void-free semi-global AW3D30 datasets.


2012 ◽  
Vol 32 (5) ◽  
pp. 932-943 ◽  
Author(s):  
Hugo A. S. Guedes ◽  
Demetrius D. da Silva

The aim of this study was to compare the hydrographically conditioned digital elevation models (HCDEMs) generated from data of VNIR (Visible Near Infrared) sensor of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), of SRTM (Shuttle Radar Topography Mission) and topographical maps from IBGE in a scale of 1:50,000, processed in the Geographical Information System (GIS), aiming the morphometric characterization of watersheds. It was taken as basis the Sub-basin of São Bartolomeu River, obtaining morphometric characteristics from HCDEMs. Root Mean Square Error (RMSE) and cross validation were the statistics indexes used to evaluate the quality of HCDEMs. The percentage differences in the morphometric parameters obtained from these three different data sets were less than 10%, except for the mean slope (21%). In general, it was observed a good agreement between HCDEMs generated from remote sensing data and IBGE maps. The result of HCDEM ASTER was slightly higher than that from HCDEM SRTM. The HCDEM ASTER was more accurate than the HCDEM SRTM in basins with high altitudes and rugged terrain, by presenting frequency altimetry nearest to HCDEM IBGE, considered standard in this study.


2019 ◽  
Vol 8 (10) ◽  
pp. 430 ◽  
Author(s):  
Kramm ◽  
Hoffmeister

Many geoscientific computations are directly influenced by the resolution and accuracy of digital elevation models (DEMs). Therefore, knowledge about the accuracy of DEMs is essential to avoid misleading results. In this study, a comprehensive evaluation of the vertical accuracy of globally available DEMs from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Shuttle Radar Topography Mission (SRTM), Advanced Land Observing Satellite (ALOS) World 3D and TanDEM-X WorldDEM™ was conducted for a large region in Northern Chile. Additionally, several very high-resolution DEM datasets were derived from Satellite Pour l’Observation de la Terre (SPOT) 6/7 and Pléiades stereo satellite imagery for smaller areas. All datasets were evaluated with three reference datasets, namely elevation points from both Ice, Cloud, and land Elevation (ICESat) satellites, as well as very accurate high-resolution elevation data derived by unmanned aerial vehicle (UAV)-based photogrammetry and terrestrial laser scanning (TLS). The accuracy was also evaluated with regard to the existing relief by relating the accuracy results to slope, terrain ruggedness index (TRI) and topographic position index (TPI). For all datasets with global availability, the highest overall accuracies are reached by TanDEM-X WorldDEM™ and the lowest by ASTER Global DEM (GDEM). On the local scale, Pléiades DEMs showed a slightly higher accuracy as SPOT imagery. Generally, accuracy highly depends on topography and the error is rising up to four times for high resolution DEMs and up to eight times for low-resolution DEMs in steeply sloped terrain compared to flat landscapes.


Water ◽  
2021 ◽  
Vol 13 (19) ◽  
pp. 2632
Author(s):  
Javed Mallick ◽  
Swapan Talukdar ◽  
Nabil Ben Kahla ◽  
Mohd. Ahmed ◽  
Majed Alsubih ◽  
...  

The present work aims to build a unique hybrid model by combining six fuzzy operator feature selection-based techniques with logistic regression (LR) for producing groundwater potential models (GPMs) utilising high resolution DEM-derived parameters in Saudi Arabia’s Bisha area. The current work focuses exclusively on the influence of DEM-derived parameters on GPMs modelling, without considering other variables. AND, OR, GAMMA 0.75, GAMMA 0.8, GAMMA 0.85, and GAMMA 0.9 are six hybrid models based on fuzzy feature selection. The GPMs were validated by using empirical and binormal receiver operating characteristic curves (ROC). An RF-based sensitivity analysis was performed in order to examine the influence of GPM settings. Six hybrid algorithms and one unique hybrid model have predicted 1835–2149 km2 as very high and 3235–4585 km2 as high groundwater potential regions. The AND model (ROCe-AUC: 0.81; ROCb-AUC: 0.804) outperformed the other models based on ROC’s area under curve (AUC). A novel hybrid model was constructed by combining six GPMs (considering as variables) with the LR model. The AUC of ROCe and ROCb revealed that the novel hybrid model outperformed existing fuzzy-based GPMs (ROCe: 0.866; ROCb: 0.892). With DEM-derived parameters, the present work will help to improve the effectiveness of GPMs for developing sustainable groundwater management plans.


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