scholarly journals EVALUATION OF DIGITAL ELEVATION MODELS FOR GEOMORPHOMETRIC ANALYSES ON DIFFERENT SCALES FOR NORTHERN CHILE

Author(s):  
T. Kramm ◽  
D. Hoffmeister

<p><strong>Abstract.</strong> The resolution and accuracy of digital elevation models (DEMs) have direct influence on further geoscientific computations like landform classifications and hydrologic modelling results. Thus, it is crucial to analyse the accuracy of DEMs to select the most suitable elevation model regarding aim, accuracy and scale of the study. Nowadays several worldwide DEMs are available, as well as DEMs covering regional or local extents. In this study a variety of globally available elevation models were evaluated for an area of about 190,000&amp;thinsp;km<sup>2</sup>. Data from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) 30 m, Shuttle Radar Topography Mission (SRTM) 30&amp;thinsp;m and 90&amp;thinsp;m, Advanced Land Observing Satellite (ALOS) World 3D 30&amp;thinsp;m and TanDEM-X WorldDEM&amp;trade; &amp;ndash; 12&amp;thinsp;m and 90&amp;thinsp;m resolution were obtained. Additionally, several very high resolution DEM data were derived from stereo satellite imagery from SPOT 6/7 and Pléiades for smaller areas of about 100&amp;ndash;400&amp;thinsp;km<sup>2</sup> for each dataset. All datasets were evaluated with height points of the Geoscience Laser Altimeter System (GLAS) instrument aboard the NASA Ice, Cloud, and land Elevation (ICESat) satellite on a regional scale and with nine very high resolution elevation models from UAV-based photogrammetry on a very large scale. For all datasets the root mean square error (RMSE) and normalized median absolute deviation (NMAD) was calculated. Furthermore, the association of errors to specific terrain was conducted by assigning these errors to landforms from the topographic position index (TPI), topographic roughness index (TRI) and slope. For all datasets with a global availability the results show the highest overall accuracies for the TanDEM-X 12&amp;thinsp;m (RMSE: 2.3&amp;thinsp;m, NMAD: 0.8&amp;thinsp;m). The lowest accuracies were detected for the 30&amp;thinsp;m ASTER GDEM v3 (RMSE: 8.9&amp;thinsp;m, NMAD: 7.1&amp;thinsp;m). Depending on the landscape the accuracies are higher for all DEMs in flat landscapes and the errors rise significantly in rougher terrain. Local scale DEMs derived from stereo satellite imagery show a varying overall accuracy, mainly depending on the topography covered by the scene.</p>

2011 ◽  
Vol 8 (3) ◽  
pp. 5497-5522 ◽  
Author(s):  
A. Hasan ◽  
P. Pilesjö ◽  
A. Persson

Abstract. It is important to study the factors affecting estimates of wetness since wetness is crucial in climate change studies. The availability of digital elevation models (DEMs) generated with high resolution data is increasing, and their use is expanding. LIDAR earth elevation data have been used to create several DEMs with different resolutions, using various interpolation parameters, in order to compare the models with collected surface data. The aim is to study the accuracy of DEMs in relation to topographical attributes such as slope and drainage area, which are normally used to estimate the wetness in terms of topographic wetness indices. Evaluation points were chosen from the high-resolution LIDAR dataset at a maximum distance of 10 mm from the cell center for each DEM resolution studied, 0.5, 1, 5, 10, 30 and 90 m. The interpolation method used was inverse distance weighting method with four search radii: 1, 2, 5 and 10 m. The DEM was evaluated using a quantile-quantile test and the normalized median absolute deviation. The accuracy of the estimated elevation for different slopes was tested using the DEM with 0.5 m resolution. Drainage areas were investigated at three resolutions, with coinciding evaluation points. The ability of the model to generate the drainage area at each resolution was obtained by pairwise comparison of three data subsets. The results show that the accuracy of the elevations obtained with the DEM model are the same for different resolutions, but vary with search radius. The accuracy of the values (NMAD of errors) varies from 29.7 mm to 88.9 mm, being higher for flatter areas. It was also found that the accuracy of the drainage area is highly dependent on DEM resolution. Coarse resolution yielded larger estimates of the drainage area but lower slope values. This may lead to overestimation of wetness values when using a coarse resolution DEM.


2020 ◽  
Author(s):  
Thomas Pollhammer ◽  
Bernhard Salcher ◽  
Florian Kober ◽  
Gaudenz Deplazes

&lt;p&gt;Glacial and glaciofluvial sediments of the North Alpine Foreland have been subject to extensive quaternary research for more than a century. Nevertheless, a regional scale stratigraphic model has not been proposed since Penk &amp; Br&amp;#252;ckner (1909). Since then, geological evidence were fit into local stratigraphic classifications, leading to severe inconsistencies across different countries/regions. The following study aims to solve inconsistencies by a morphostratigraphical approach, applying innovative methods utilizing new high-resolution digital elevation models, existing geodata and information from literature.&lt;/p&gt;&lt;p&gt;First, the abundant information from literature was reviewed to create a synopsis of commonly used terrace stratigraphic classifications. Second, geologic maps and (high-resolution) digital elevation models were compiled in a GIS database. To process this data, a new toolset was developed (using software R), fitting the requirements of morphostratigraphic analyses. These mainly involve the processing and statistic evaluation of terrace-top surfaces. Based on these analyses, we discussed fluvial, glacial and geodynamic factors, controlling the observed hypsometric parameters (concavity, slope, relative heights). To stratigraphically compare results across catchments and regions, the modern Danube and Rhine River were used as &amp;#8220;fixed&amp;#8221; base-levels to which tributary terrace tops were extrapolated. Terrace elevations above these base-levels were used as proxy to evaluate the rare absolute and otherwise inferred terrace ages from literature. Derived morphostratigraphic evidence provides an objective basis to discuss and harmonise the highly complex and diverging stratigraphic classification schemes across North Alpine Foreland regions.&lt;/p&gt;&lt;p&gt;Penck, A., &amp; Br&amp;#252;ckner, E. (1909). Die Alpen im Eiszeitalter. Leipzig: Tauchnitz.&lt;/p&gt;


2019 ◽  
Vol 11 (14) ◽  
pp. 1660
Author(s):  
Partovi ◽  
Fraundorfer ◽  
Bahmanyar ◽  
Huang ◽  
Reinartz

Recent advances in the availability of very high-resolution (VHR) satellite data together withefficient data acquisition and large area coverage have led to an upward trend in their applicationsfor automatic 3-D building model reconstruction which require large-scale and frequent updates,such as disaster monitoring and urban management. Digital Surface Models (DSMs) generatedfrom stereo satellite imagery suffer from mismatches, missing values, or blunders, resulting inrough building shape representations. To handle 3-D building model reconstruction using suchlow-quality DSMs, we propose a novel automatic multistage hybrid method using DSMs togetherwith orthorectified panchromatic (PAN) and pansharpened data (PS) of multispectral (MS) satelliteimagery. The algorithm consists of multiple steps including building boundary extraction anddecomposition, image-based roof type classification, and initial roof parameter computation whichare prior knowledge for the 3-D model fitting step. To fit 3-D models to the normalized DSM(nDSM) and to select the best one, a parameter optimization method based on exhaustive searchis used sequentially in 2-D and 3-D. Finally, the neighboring building models in a building blockare intersected to reconstruct the 3-D model of connecting roofs. All corresponding experimentsare conducted on a dataset including four different areas of Munich city containing 208 buildingswith different degrees of complexity. The results are evaluated both qualitatively and quantitatively.According to the results, the proposed approach can reliably reconstruct 3-D building models, eventhe complex ones with several inner yards and multiple orientations. Furthermore, the proposedapproach provides a high level of automation by limiting the number of primitive roof types and byperforming automatic parameter initialization.


2011 ◽  
Vol 115 (4) ◽  
pp. 1025-1033 ◽  
Author(s):  
Gherardo Chirici ◽  
Diego Giuliarelli ◽  
Daniele Biscontini ◽  
Daniela Tonti ◽  
Walter Mattioli ◽  
...  

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.


Geosciences ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 256
Author(s):  
Maria P. Kakavas ◽  
Konstantinos G. Nikolakopoulos

The scope of this paper is to summarize previous research pertaining to the use of digital elevation models (DEMs) and digital terrain models (DTMs) in the study of rockfalls and landslides. Research from 1983 to 2020 was surveyed in order to understand how the spatial resolution of DEMs and DTMs affects landslide detection, validation, and mapping. Another major question examined was the relationship between the DEM resolution and the extent of the rockfall or landslide event. It emerged from the study that, for landslides, the majority of researchers used DEMs with a spatial resolution of between 10 m and 30 m, while for rockfalls, they used DEMs with a spatial resolution of between 5 m and 20 m. We concluded that DEMs with a very high resolution (less than 5 m) are suitable for local-scale occurrences, while medium-resolution (from 20 m to 30 m) DEMs are suitable for regional-scale events. High resolution is associated with high accuracy and detailed structural characteristics, while medium accuracy better illustrates the topographic features. A low pixel size (more than 90 m) is not recommended for this type of research. Susceptibility maps, inventory maps, hazard risk zones, and vulnerability assessments are some of the main tools used in landslide/rockfall investigations, and topographic indexes, methods, models, and software optimize the reliability of the results. All of these parameters are closely related to DEMs and DTMs as the cell size affects the credibility of the final outcome.


2020 ◽  
Vol 5 (1) ◽  
pp. 1
Author(s):  
Minakshi Kumar ◽  
Ashutosh Bhardwaj

The availability of very high resolution (VHR) satellite imagery (<1 m) has opened new vistas in large-scale mapping and information management in urban environments. Buildings are the most essential dynamic incremental factor in the urban environment, and hence their extraction is the most challenging activity. Extracting the urban features, particularly buildings using traditional pixel-based classification approaches as a function of spectral tonal value, produces relatively less accurate results for these VHR Imageries. The present study demonstrates building extraction using Pleiades panchromatic (PAN) and multispectral stereo satellite datasets of highly planned and dense urban areas in parts of Chandigarh, India. The stereo datasets were processed in a photogrammetric environment to obtain the digital elevation model (DEM) and corresponding orthoimages. DEM’s were generated at 0.5 m and 2.0 m from stereo PAN and multispectral datasets, respectively. The orthoimages thus generated were segmented using object-based image analysis (OBIA) tools. The object primitives such as scale parameter, shape, textural parameters, and DEM derivatives were used for segmentation and subsequently to determine threshold values for building fuzzy rules for building extraction and classification. The rule-based classification was carried out with defined decision rules based on object primitives and fuzzy rules. Two different methods were utilized for the performance evaluation of the proposed automatic building approach. Overall accuracy, correctness, and completeness were evaluated for extracted buildings. It was observed that overall accuracy was higher (>93%) in areas having larger buildings and that were sparsely built-up as compared to areas having smaller buildings and being densely built-up.


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