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Found 10 results.

Digital elevation model (DEM 1) of the River Rhine floodplain between Iffezheim and Kleve, Germany

This digital elevation model (DEM) describes the topography of the active floodplain of the freeflowing parts of River Rhine between the weir Iffezheim and the German-Dutch border near Kleve with 1 m spatial resolution in coordinate reference system "ETRS 1989 UTM Zone 32 N" and 0.01 m resolution in the German height reference system "Deutsches Haupthöhennetz 1992 (DHHN92)". The dataset was generated in four parts through aerial laser scanning (ALS) for terrestrial parts of the floodplain and echo sounding for aquatic parts of the central water course by the local waterway and navigation authorities (WSV) between 2003 and 2010. Parts not covered by any of the two data collection methods were filled through linear interpolation. A comparison between DEM and reference points confirmed a high accuracy with a mean deviation of elevations of ± 5 cm. Depending on the data source 95% of all checked points show a vertical deviation of less than 15 cm to 50 cm. Since the dataset has a large volume it was split into 40 tiles.

A database of R-R-R triple junction analogue and numerical models

This dataset presents the raw data from two experimental series of analogue models and four numerical models performed to investigate Rift-Rift-Rift triple junction dynamics, supporting the modelling results described in the submitted paper. Numerical models were run in order to support the outcomes obtained from the analogue models. Our experimental series tested the case of a totally symmetric RRR junction (with rift branch angles trending at 120° and direction of stretching similarly trending at 120°; SY Series) or a less symmetric triple junction (with rift branches trending at 120° but with one of these experiencing orthogonal extension; OR Series), and testing the role of a single or two phases of extension coupled with effect of differential velocities between the three moving plates. An overview of the performed analogue and numerical models is provided in Table 1. Analogue models have been analysed quantitatively by means of photogrammetric reconstruction of Digital Elevation Model (DEM) used for 3D quantification of the deformation, and top-view photo analysis for qualitative descriptions. The analogue materials used in the setup of these models are described in Montanari et al. (2017), Del Ventisette et al. (2019) and Maestrelli et al. (2020). Numerical models were run with the finite element software ASPECT (e.g., Kronbichler et al., 2012; Heister et al., 2017; Rose et al., 2017).

Digital elevation model (DEM 1) of the River Elbe floodplain between Schmilka and Geesthacht, Germany

This digital elevation model (DEM) describes the topography of the active floodplain of the middle reaches of River Elbe between the Czech-German border near Schmilka and the weir in Geesthacht with 1 m spatial resolution in coordinate reference system "ETRS 1989 UTM Zone 33 N" and 0.01 m resolution in the German height reference system "Deutsches Haupthöhennetz 1992 (DHHN92)". The dataset was generated through aerial laser scanning (ALS) for terrestrial parts of the floodplain between April 2003 and December 2006 and echo sounding for aquatic parts of the central water course by the local waterway and navigation authorities (WSV) throughout the year 2006. Parts not covered by any of the two data collection methods were filled through linear interpolation. A comparison between DEM and 7476 height reference points confirmed a high accuracy with a mean deviation of elevations of ± 5 cm. Depending on the data source 95% of all checked points show a vertical deviation of less than 15 cm to 50 cm. A small section of the model was updated later to incorporate the dike relocation area Lenzen which became connected to the floodplain in 2011 so that the dataset describes the state of 2011. Since the dataset has a large volume it was split into 49 tiles.

Bezymianny volcano 1967-2017 photogrammetric dataset

Decades of photogrammetric records at Bezymianny, one of the most active volcanoes on Earth, allow unveiling morphological changes, eruption and intrusion dynamics, erosion, lava and tephra deposition processes. This data publication releases an almost 7-decade long record, retrieved from airborne, satellite, and UAV platforms. The Kamchatkan Institute of Volcanology and Seismology released archives of high-resolution aerial images acquired in 1967-2013. We complemented the aerial datasets with 2017 Pleiades tri-stereo satellite and UAV images. The images were processed using Erdas Imagine and Photomod software. Here we publish nine quality-controlled point clouds in LAS format referenced to the WGS84 (UTM zone 57N). By comparing the point clouds we were able to describe topographic changes and calculate volumetric differences, details of which were further analyzed in Shevchenko et al. (2020, https://doi.org/...). The ~5-decade-long photogrammetric record was achieved by 8 aerial and 1 satellite-UAV datasets. The 8 sets of near nadir aerial photographs acquired in 1967, 1968, 1976, 1977, 1982, 1994, 2006, and 2013 were taken with various photogrammetry cameras dedicated for topographic analysis, specifically the AFA 41-10 camera (1967, 1968, 1976, and 1977; focal length = 99.086 mm), the TAFA 10 camera (1982 and 1994; focal length = 99.120 mm), and the AFA TE-140 camera (2006 and 2013; focal length = 139.536 mm). These analog cameras have all an 18×18 cm frame size. The acquisition flight altitude above the mean surface of Bezymianny varied from 1,500-2,500 m above mean surface elevation, translating up to >5,000 m above sea level. For photogrammetric processing, we used 3-4 consecutive shots that provided a 60-70% forward overlap. The analog photo negatives were digitized by scanning with Epson Perfection V750 Pro scanner in a resolution of 2,400 pixels/inch (approx. pixel (px) size = 0.01 mm). The mean scale within a single photograph depends on the distance to the surface and corresponds on average to 1:10,000-1:20,000. Thus, each px in the scanned image represents about 10-20 cm resolution on the ground. The coordinates of 12 ground control points were derived from a Theo 010B theodolite dataset collected at geodetic benchmarks during a 1977 fieldwork. These benchmarks were established on the slopes of Bezymianny before the 1977 aerial survey and then captured with the AFA 41-10 aerial camera. The most recent was a satellite dataset acquired on 2017-09-09 by the PHR 1B sensor aboard the Pleiades satellite (AIRBUS Defence & Space) operated by the French space agency (CNES). The forward, nadir and backward camera configuration allows revisiting any point on earth and was tasked for the acquisition of Bezymianny to provide a 0.5 m resolution panchromatic imagery dataset. In order to improve the Pleiades data, we complemented them with UAV data collected on 2017-07-29 with DJI Mavic Pro during fieldwork at Bezymianny. This data publication includes a description of the data (in pdf format) and the nine processed and controlled three-dimensional point clouds (in LAS format). The point clouds can be easily interpolated and imported into most open and commercially available geographic information system (GIS) software. Further details on data and data handling are provided in Shevchenko et al. (2020).

High resolution Digital Elevation Model of Merapi summit in 2015 generated by UAVs and TLS

This data publication is a high resolution Digital Elevation Model (DEM) generated for the Merapi summit by combining terrestrial laser scanning (TLS) and unmanned aerial vehicles (UAVs) photogrammetry data acquired in 2014 and 2015, respectively. The structures of the data are further analysed in Darmawan et al. 2017 (http://doi.org/10.1016/j.jvolgeores.2017.11.006). The published datasets consist of combined point clouds with ~65 million data points and a DEM with a resampled resolution of 0.5 m. The DEM data covers the complexity of the Merapi summit with area of 2 km2. The coordinate of the datasets is projected to global coordinates (WGS 1984 UTM Zone 49 South). TLS is a topography mapping technique which exploits the travel time of a laser beam to measure the range between the ground-based scanning instrument and the earth’s surface. TLS provides high accuracy, precision, and resolution for topography mapping, however, it requires different scan position to obtain accurate topography model in a complex topography. The TLS dataset was acquired by using a long-range RIEGL VZ-6000 instrument with a Pulse Repetition Rate (PRR) of 30 kHz. The Merapi data includes an observation range of 0.129 – 4393.75 m, a theta range (vertical) of 73 – 120° with a sampling angle of 0.041°, a phi range (horizontal) of 33° - 233° with a sampling angle of 0.05°, and 12 reflectors for each scan. The used TLS dataset was achieved by combining two scan positions, both realized in September 2014. In order to reduce still eminent shadowing, we conducted additionally a UAV photogrammetry survey. The UAV data allows to fill data gaps and generate a complete 3D point cloud. The UAV photogrammetry was conducted by using DJI Phantom 2 quadcopter drone in October 2015. The drone carried GoPro HERO 3+ camera and a H3-3D gimbal to reduce image shaking. We obtained over 300 images which cover the summit area of Merapi. By applying the Structure from Motion algorithm, we are able to generate a 3D point cloud model of Merapi summit. Further details on this procedure are provided in Darmawan et al. (2017). Structure from Motion is a technique to generate a 3D model based on 2D overlapped images. The algorithm detects and matches the same ground features of 2D images, reconstructs a 3D scene, and calculates a depth map for each camera frame. The algorithm used is implemented in Agisoft Photoscan Professional software. After importing the images in Agisoft, we used the ‘align image’ function with high accuracy setting to generate 3D sparse point cloud and ‘build dense cloud’ function with high quality to generate 3D dense point cloud. The 3D point clouds of TLS and UAV photogrammetry were then georeferenced to our georeferenced 3D point cloud which acquired in 2012. The RMS of TLS and UAV photogrammetry during georeferenced is 0.60 and 0.44 m, respectively, as described in Further details on this procedure are provided in Darmawan et al. (2017). After georeferencing, both 3D point clouds were merged and interpolated to a raster format in the ArcMap software.

Digital elevation model (DEM 1) of the River Elbe floodplain between Schmilka and Geesthacht, Germany

This digital elevation model (DEM) describes the topography of the active floodplain of the middle reaches of River Elbe between the Czech-German border near Schmilka and the weir in Geesthacht with 1 m spatial resolution in coordinate reference system "ETRS 1989 UTM Zone 33 N" and 0.01 m resolution in the German height reference system "Deutsches Haupthöhennetz 1992 (DHHN92)". The dataset was generated through aerial laser scanning (ALS) for terrestrial parts of the floodplain between April 2003 and December 2006 and echo sounding for aquatic parts of the central water course by the local waterway and navigation authorities (WSV) throughout the year 2006. Parts not covered by any of the two data collection methods were filled through linear interpolation. A comparison between DEM and 7476 height reference points confirmed a high accuracy with a mean deviation of elevations of ± 5 cm. Depending on the data source 95% of all checked points show a vertical deviation of less than 15 cm to 50 cm. A small section of the model was updated later to incorporate the dike relocation area Lenzen which became connected to the floodplain in 2011 so that the dataset describes the state of 2011. Since the dataset has a large volume it was split into 49 tiles.

Supplementary material for analogue experiments on the interactions of two indenters, and their implications for curved fold-and-thrust-belts

This data publication includes animations and figures of eight scaled analogue models that are used to investigate the evolution of a curved mountain belt akin to the Pamir and Hindu Kush orogenic system and adjacent Tadjik basin. Crustal deformation is simulated by means of indentation of two basement blocks into a sedimentary sequence and the formation of a curved fold-and-thrust belt.The experimental set-up has two adjacent rigid indenters representing the basement blocks moving in parallel with a velocity difference (Figure 1). The slow indenter moves with a relative velocity ranging from 40 to 80% of that of the fast one. A layer of quartz sand in front of the indenters, 1 by 1 meter in size and 1.5 cm thick, represents the sedimentary basin infill. A basal detachment layer is made up of low-friction glass beads or viscous silicone oil representing weak shale or evaporates layers, respectively. The surface evolution by means of topography and strain distribution is derived from 3-D particle image velocimetry (PIV). This allows visualizing and analysing the development of the model surface during the complete model run at high spatio-temporal resolution. All details about the model set-up, modelling results and interpretation can be found in Reiter et al. (2011).The here provided additional material includes time-lapse movies showing the topographic evolution of the eight models. These visualizations are oblique views played back at 60-fold velocity for the “glass beads experiments” (gb40 to gb80) and 3600-fold velocity for the “silicone experiments” (si60, si-gb60).In addition to the experiment movies we provide a set of figures. The figures include surface views as well as cross-sections through the finite models highlighting the link between topography and internal structure of the simulated curved fold-and-thrust belts. Additionally, attribute maps of distinct morphometric measures (curvature, slope) and deformation parameters (uplift, horizontal translation) for the experiments with glass beads detachments are given. Finally, the movie “Experimenting.avi” shows in time-lapse the whole workflow of setting up, conducting and documenting an experiment, which originally required three days (for experiment si-gb60).An overview on the parameters used in the experimental series of the movie sequences is given in the explanatory file (Explanations_Reiter-et-al-2016.pdf). A full list of files is given in “list-of-files-Reiter-et-al-2016.pdf”.

Digital elevation model (DEM 1) of the River Rhine floodplain between Iffezheim and Kleve, Germany

This digital elevation model (DEM) describes the topography of the active floodplain of the freeflowing parts of River Rhine between the weir Iffezheim and the German-Dutch border near Kleve with 1 m spatial resolution in coordinate reference system "ETRS 1989 UTM Zone 32 N" and 0.01 m resolution in the German height reference system "Deutsches Haupthöhennetz 1992 (DHHN92)". The dataset was generated in four parts through aerial laser scanning (ALS) for terrestrial parts of the floodplain and echo sounding for aquatic parts of the central water course by the local waterway and navigation authorities (WSV) between 2003 and 2010. Parts not covered by any of the two data collection methods were filled through linear interpolation. A comparison between DEM and reference points confirmed a high accuracy with a mean deviation of elevations of ± 5 cm. Depending on the data source 95% of all checked points show a vertical deviation of less than 15 cm to 50 cm. Since the dataset has a large volume it was split into 40 tiles.

Evaluation of the terrain model influence on the Orthorectification of Sentinel-2 satellite images over Austria (S2OrthoQDTM)

Aim of the project is to address the concerns on Sentinel-2 geolocation accuracy over the area of Austria. Within Austria's alpine region steep slopes occur. This means that errors in terrain model elevation have a severe effect on lateral displacement, as displacement because of elevation error and because of slope can add up. Errors are expected from SRTM due to radar shadows (InSAR viewing geometry) and other effects. Output of the project is a report, which assesses the geolocation errors expected because of PlanetDEM for the area of Austria. This will be compared to geolocation errors to be expected with a terrain model of superior quality. Errors of the superior model are not determinable, it will act as reference ('ground truth') for PlanetDEM. A second, equally important, output is a suggestion on how to improve the geolocation quality of Sentinel-2 data over Austria. Possibilities on how to improve the product will be discussed. Next to repeating the orthorectification pocress with a better DTM and thus derive a new orthoimage, the grid-shift mechanism5 will be explored, as it might be used for on-the-fly transformation within a GIS. Practical consequences of using the different options will be explored.

Improved detection of changes through integrated 3-D information and remote sensing data

Change detection is a very important challenge. Various change detection methods are documented in the literature but most of them focus on two-dimensional data which limit their applicability. Therefore, in this project we focus on the development of three-dimensional change detection methods considering three different scenarios. First, we assume that there is no three-dimensional information for both old and new scenes to detect changes. We propose using twodimensional change detection algorithms followed by approximate three-dimension extraction of the changed regions. Here, we will develop novel depth estimation methods based on shadow and shape information. Second, we assume that we have the three-dimensional information (in terms of stereo image pairs) to be available either for the old or the new scene only. To detect changes in three-dimensions, we will construct the digital elevation model (DEM) based on the stereo image matching principle. For the scene having mono image, we will generate the DEM data by shadow and shape information. Using novel three-dimensional change detection methods, we plan to detect changes on these data sets. ...

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