scholarly journals Impact of input data (in)accuracy on overestimation of visible area in digital viewshed models

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4835 ◽  
Author(s):  
Ondřej Lagner ◽  
Tomáš Klouček ◽  
Petra Šímová
Keyword(s):  
Input Data ◽  
Computational Algorithm ◽  
Surface Model ◽  
Digital Terrain ◽  
Levels Of Detail ◽  
Terrain Models ◽  
Viewshed Analysis ◽  
Elevation Data ◽  
Visible Area

Viewshed analysis is a GIS tool in standard use for more than two decades to perform numerous scientific and practical tasks. The reliability of the resulting viewshed model depends on the computational algorithm and the quality of the input digital surface model (DSM). Although many studies have dealt with improving viewshed algorithms, only a few studies have focused on the effect of the spatial accuracy of input data. Here, we compare simple binary viewshed models based on DSMs having varying levels of detail with viewshed models created using LiDAR DSM. The compared DSMs were calculated as the sums of digital terrain models (DTMs) and layers of forests and buildings with expertly assigned heights. Both elevation data and the visibility obstacle layers were prepared using digital vector maps differing in scale (1:5,000, 1:25,000, and 1:500,000) as well as using a combination of a LiDAR DTM with objects vectorized on an orthophotomap. All analyses were performed for 104 sample locations of 5 km2, covering areas from lowlands to mountains and including farmlands as well as afforested landscapes. We worked with two observer point heights, the first (1.8 m) simulating observation by a person standing on the ground and the second (80 m) as observation from high structures such as wind turbines, and with five estimates of forest heights (15, 20, 25, 30, and 35 m). At all height estimations, all of the vector-based DSMs used resulted in overestimations of visible areas considerably greater than those from the LiDAR DSM. In comparison to the effect from input data scale, the effect from object height estimation was shown to be secondary.

scholarly journals IMG2nDSM: Height Estimation from Single Airborne RGB Images with Deep Learning

2021 ◽  
Vol 13 (12) ◽  
pp. 2417
Author(s):  
Savvas Karatsiolis ◽  
Andreas Kamilaris ◽  
Ian Cole
Keyword(s):  
Deep Learning ◽  
State Of The Art ◽  
Aerial Imagery ◽  
Aerial Images ◽  
Surface Model ◽  
Large Area ◽  
Digital Terrain ◽  
Terrain Models ◽  
Architectural Features ◽  
Rgb Images

Estimating the height of buildings and vegetation in single aerial images is a challenging problem. A task-focused Deep Learning (DL) model that combines architectural features from successful DL models (U-NET and Residual Networks) and learns the mapping from a single aerial imagery to a normalized Digital Surface Model (nDSM) was proposed. The model was trained on aerial images whose corresponding DSM and Digital Terrain Models (DTM) were available and was then used to infer the nDSM of images with no elevation information. The model was evaluated with a dataset covering a large area of Manchester, UK, as well as the 2018 IEEE GRSS Data Fusion Contest LiDAR dataset. The results suggest that the proposed DL architecture is suitable for the task and surpasses other state-of-the-art DL approaches by a large margin.

scholarly journals Single-input, multiple-output iterative algorithm for the calculation of volume, area, elevation, and shape using 3D topobathymetric models

2020 ◽  
Author(s):  
Hugo Luis Rojas-Villalobos ◽  
Blair Stringam ◽  
Zohrab Samani ◽  
Luis Carlos Alatorre Cejudo ◽  
Christopher Brown
Keyword(s):  
Water Body ◽  
Input Data ◽  
Reference Value ◽  
The Body ◽  
Digital Terrain ◽  
Terrain Models ◽  
Input Multiple Output ◽  
Single Input ◽  
The Difference ◽  
Area And Volume

Most methods for estimating the morphometric values of water bodies use equations derived from hypsographic curves or digital terrain models (DTMs) that relate depth, volume (V), and area (A) and that model the uncertainty inherent in the complex underwater morphology. This research focuses directly on the use of topobathymetric models that include the bathymetry and topography of the surrounding area next to the water body. The projection of the water surface height (H) on each DTM pixel generates a water column with intrinsic attributes such as volume and area. The process is replicated among all cells and estimates the total area and volume of the water body. If the V or A is the input data, an algorithm that iterates height values is used to generate the new data, which is compared with the entered value that functions as a reference. If the difference between the reference value and the calculated value is less than an error threshold, the iteration stops, and the maximum and average depths are calculated. The raster and the shape that represent the body of water are created. The cross comparison of H-V-A showed that there is an error between 0.0034% and 0.000039% when any of the parameters are used as input data. Performance tests determined that pixel dimensions are directly proportional to the processing time for each iteration. The results of the implementation of this algorithm were satisfactory since, for the DTM of Bustillos Lagoon, Chihuahua, Mexico, the simulation took less than 17 seconds in at most 22 iterations.

Impact of Scale and Quality of Digital Terrain Models on Predictability of Seabed Terrain Types

2013 ◽  
Vol 36 (1) ◽  
pp. 2-21 ◽  
Author(s):  
Lars Erikstad ◽  
Vegar Bakkestuen ◽  
Trine Bekkby ◽  
Rune Halvorsen
Keyword(s):  
Digital Terrain Models ◽  
Digital Terrain ◽  
Terrain Models

scholarly journals THE MODERN MEDIUM-SCALE MAPPING OF THE AVALANCE DANGER IN THE UKRAINIAN CARPATHIANS

2020 ◽  
Author(s):  
Oleksandr Aksiuk ◽  
◽  
Valentyn Lanshyn ◽  
Hanna Honcharenko ◽  
◽  
...  
Keyword(s):  
Thematic Maps ◽  
Mountain Areas ◽  
Digital Maps ◽  
Mountain Landscape ◽  
Avalanche Hazard ◽  
Digital Terrain ◽  
Terrain Models ◽  
Average Maximum ◽  
Mountain Development

There is a characteristic phenomenon of mountain landscape in Avalanche. Mountain development entails the need to take into account the avalanche hazard. The important task of the Hydrometeorological Service of Ukraine is to increase the effectiveness of forecasting avalanche danger in mountainous areas of Ukraine. One of the elements on the way to its solution is the digital display of mountain areas in the form of thematic maps. The intensive development of modern GIS technologies and the availability of digital terrain models make it possible to create various thematic maps. The avalanche activity is affected by meteorological and geomorphological factors. Using DEM based on SRTM 1, an avalanche hazard map of Ukrainian Carpathians was compiled. The map is based on the average maximum snow height and the steepness of the slopes. The proposed map will improve the quality of avalanche forecasts and will allow you to determine the need for avalanche exploration if the intended area of construction falls into the avalanche zone and protect users from unnecessary danger. An algorithm for constructing thematic (avalanche) digital maps using satellite data SRTM 1 has been elaborated.

scholarly journals Simulation of Images and Digital Terrain Models for the Mission BepiColombo

2021 ◽  
Author(s):  
Nicolò Borin ◽  
Cristina Re ◽  
Emanuele Simioni ◽  
Stefano Debei ◽  
Gabriele Cremonese
Keyword(s):  
High Resolution ◽  
Input Data ◽  
Image Simulation ◽  
Digital Terrain Models ◽  
Digital Terrain ◽  
Terrain Models ◽  
Novel Approach ◽  
Stereo Reconstruction ◽  
Acquisition Strategy ◽  
The Creation

AbstractBepiColombo mission will provide Digital Terrain Models of the surface of Mercury by means of the stereo channel of the SIMBIO-SYS (Spectrometer and Imaging for MPO BepiColombo Integrated Observatory SYStem) imaging package onboard. The work here described presents a novel approach for the creation of higher resolution stereo products using the high-resolution channel of SIMBIO-SYS. Being the camera rigidly integrated with the spacecraft, this latter must be tilted to acquire stereo pairs necessary for the 3D reconstruction. A new method for image simulation and stereo reconstruction is presented in this work, where the input data are chosen as closely as possible to the real mission parameters. Different simulations are executed changing the illumination conditions and the stereo angles. The Digital Terrain Models obtained are evaluated and an analysis of the best acquisition conditions is performed, helping to improve the image acquisition strategy of BepiColombo mission. In addition, a strategy for the creation of a mosaic from different images acquired with the high-resolution channel of SIMBIO-SYS is explained, giving the possibility to obtain tridimensional products of extended targets.

scholarly journals WORLDDEM – A NOVEL GLOBAL FOUNDATION LAYER

2015 ◽  
Vol XL-3/W2 ◽  
pp. 183-187 ◽  
Author(s):  
G. Riegler ◽  
S. D. Hennig ◽  
M. Weber
Keyword(s):  
Digital Terrain Model ◽  
Current Status ◽  
Disruptive Technology ◽  
Surface Model ◽  
Terrain Model ◽  
Digital Terrain ◽  
Digital Elevation ◽  
Elevation Data ◽  
Elevation Model ◽  
German Aerospace

Airbus Defence and Space’s WorldDEM™ provides a global Digital Elevation Model of unprecedented quality, accuracy, and coverage. The product will feature a vertical accuracy of 2m (relative) and better than 6m (absolute) in a 12m x 12m raster. The accuracy will surpass that of any global satellite-based elevation model available. WorldDEM is a game-changing disruptive technology and will define a new standard in global elevation models. <br><br> The German radar satellites TerraSAR-X and TanDEM-X form a high-precision radar interferometer in space and acquire the data basis for the WorldDEM. This mission is performed jointly with the German Aerospace Center (DLR). Airbus DS refines the Digital Surface Model (e.g. editing of acquisition, processing artefacts and water surfaces) or generates a Digital Terrain Model. Three product levels are offered: WorldDEMcore (output of the processing, no editing is applied), WorldDEM™ (guarantees a void-free terrain description and hydrological consistency) and WorldDEM DTM (represents bare Earth elevation). <br><br> Precise elevation data is the initial foundation of any accurate geospatial product, particularly when the integration of multi-source imagery and data is performed based upon it. Fused data provides for improved reliability, increased confidence and reduced ambiguity. This paper will present the current status of product development activities including methodologies and tool to generate these, like terrain and water bodies editing and DTM generation. In addition, the studies on verification & validation of the WorldDEM products will be presented.

scholarly journals The application of the scale-space theory for medium-resolution DTM in geological and geotectonic studies

2019 ◽  
pp. 68-78
Author(s):  
O. V. Rybas ◽  
G. Z. Gilmanova
Keyword(s):  
Scale Space ◽  
Geological Structure ◽  
Geological Mapping ◽  
Space Theory ◽  
Structural Elements ◽  
Digital Terrain ◽  
Terrain Models ◽  
Medium Resolution ◽  
Scale Spaces

The article presents a technique for identifying structural elements and details of the geological structure in digital terrain models (DTM) based on the theory of scale spaces. With its help, linear, dome-shaped and textural features are singled out from medium-resolution DTM (for example, SRTM03, GMTED2010), allowing to significantly improve the quality of studies related to tectonic and geological mapping and zoning. In general, the theory of scale — spaces is described in application to the solution of these problems and illustarted on the examples of a number of case studies.

scholarly journals FEATURES OF CONSTRUCTION OF DIGITAL RELIEF MODEL ACCORDING TO THE RESULTS OF GEODESIC SURVEYING LOCATIONS

2021 ◽  
Vol 1 (161) ◽  
pp. 104-108
Author(s):  
A. Batrakova ◽  
Y. Dorozhko ◽  
V. Yemets
Keyword(s):  
Surface Display ◽  
Digital Terrain Model ◽  
Topographic Maps ◽  
Surface Model ◽  
Terrain Model ◽  
Model Based ◽  
Digital Terrain ◽  
Geodetic Measurements ◽  
Geodetic Surveying

Topographic maps in digital and electronic forms are created on the basis of available paper topographic maps or on the basis of primary materials of geodetic surveys. Geodetic surveys are performed both by ground methods, without the use of photogrammetric materials, and on the basis of materials obtained as a result of ground phototheodolite or aerial photography. The construction of a digital terrain model is a multi-stage process, which consists of a significant number of interconnected operations performed at the stage of in-house processing of the results of geodetic measurements carried out during engineering and geodetic surveys. The quality of the final result of modeling depends on the quality of each stage of construction of a digital terrain model, so it is extremely important to pay attention to all technological processes of model construction. The digital relief model is considered as an ordered set of triangular faces constructed by the Delaunay algorithm. The main condition of this type of triangulation is that in the middle of the circle described around any triangle can not be the vertex of another triangle. Construction of a digital terrain model based on the results of geodetic surveying of the area in the general case can be divided into several stages. At the beginning, an automated construction of triangulation is performed on the basis of the results of geodetic measurements, which carry information about three-dimensional coordinates of survey points. Allotments adjust the display of horizontals. Regardless of the selected surface display style, the surface model is a grid of triangles. At the next stage of construction of the digital model of a relief carry out visual control of the created model and if necessary carry out editing of elements of a surface and change of position of edges of triangulation for change of position of horizontals. The last stage of building a digital terrain model based on the results of geodetic surveying of the area is the design of modeling results, the application of individual styles of reflection for individual areas of the surface and the creation of mountain strokes and signatures of horizontals.

scholarly journals Pixel-Based Geometric Assessment of Channel Networks/Orders Derived from Global Spaceborne Digital Elevation Models

2019 ◽  
Vol 11 (3) ◽  
pp. 235 ◽  
Author(s):  
Mohamed Shawky ◽  
Adel Moussa ◽  
Quazi K. Hassan ◽  
Naser El-Sheimy
Keyword(s):  
Remote Sensing ◽  
Digital Elevation Models ◽  
Shuttle Radar Topography Mission ◽  
Surface Model ◽  
Kappa Index ◽  
Channel Networks ◽  
Digital Terrain ◽  
Terrain Models ◽  
Digital Elevation ◽  
Confusion Matrices

Digital Elevation Models (DEMs) contribute to geomorphological and hydrological applications. DEMs can be derived using different remote sensing-based datasets, such as Interferometric Synthetic Aperture Radar (InSAR) (e.g., Advanced Land Observing Satellite (ALOS) Phased Array type L-band SAR (PALSAR) and Shuttle Radar Topography Mission (SRTM) DEMs). In addition, there is also the Digital Surface Model (DSM) derived from optical tri-stereo ALOS Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) imagery. In this study, we evaluated satellite-based DEMs, SRTM (Global) GL1 DEM V003 28.5 m, ALOS DSM 28.5 m, and PALSAR DEMs 12.5 m and 28.5 m, and their derived channel networks/orders. We carried out these assessments using Light Detection and Ranging (LiDAR) Digital Surface Models (DSMs) and Digital Terrain Models (DTMs) and their derived channel networks and Strahler orders as reference datasets at comparable spatial resolutions. We introduced a pixel-based method for the quantitative horizontal evaluation of the channel networks and Strahler orders derived from global DEMs utilizing confusion matrices at different flow accumulation area thresholds (ATs) and pixel buffer tolerance values (PBTVs) in both ±X and ±Y directions. A new Python toolbox for ArcGIS was developed to automate the introduced method. A set of evaluation metrics—(i) producer accuracy (PA), (ii) user accuracy (UA), (iii) F-score (F), and (iv) Cohen’s kappa index (KI)—were computed to evaluate the accuracy of the horizontal matching between channel networks/orders extracted from global DEMs and those derived from LiDAR DTMs and DSMs. PALSAR DEM 12.5 m ranked first among the other global DEMs with the lowest root mean square error (RMSE) and mean difference (MD) values of 4.57 m and 0.78 m, respectively, when compared to the LiDAR DTM 12.5 m. The ALOS DSM 28.5 m had the highest vertical accuracy with the lowest recorded RMSE and MD values of 4.01 m and –0.29 m, respectively, when compared to the LiDAR DSM 28.5 m. PALSAR DEM 12.5 m and ALOS DSM 28.5 m-derived channel networks/orders yielded the highest horizontal accuracy when compared to those delineated from LiDAR DTM 12.5 m and LiDAR DSM 28.5 m, respectively. The number of unmatched channels decreased when the PBTV increased from 0 to 3 pixels using different ATs.

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