scholarly journals The Technique of Creating a Digital Terrain Model Based on Open Geodata Source (on the Example of Bural-Sardag Field)

Georesursy ◽  
2013 ◽  
Vol 53 (3) ◽  
pp. 36-40
Author(s):  
O.I. Demina ◽  
◽  
A.V. Parshin ◽  
A.M. Fedorov ◽  
S.A. Shestakov ◽  
...  
Keyword(s):  
Digital Terrain Model ◽  
Terrain Model ◽  
Model Based ◽  
Digital Terrain

scholarly journals Nově objevené hradiště Čerťák u obce Sovolusky v kontextu halštatského osídlení regionu

2021 ◽  
Vol 6 (1-2) ◽  
pp. 159-176
Author(s):  
Filip Prekop ◽  
Petr Krištuf
Keyword(s):  
Laser Scanning ◽  
Digital Terrain Model ◽  
Field Research ◽  
Airborne Laser Scanning ◽  
Terrain Model ◽  
Model Based ◽  
Digital Terrain ◽  
Airborne Laser ◽  
Scanning Lidar ◽  
Hallstatt Period

This paper presents a new hillfort site which is situated on top of „Čerťák“ Hill (651 m n. m.), Sovolusky municipality, Karlovy Vary district. It has been identified with the help of a digital terrain model based on Airborne Laser Scanning (LiDAR). Two separate lines of stone ramparts have been confirmed on top of the Čerťák Hill, formed by a significant right bank meander in the upper course of the river Střela. The inner area reaches 1.4 ha and the external enclosed area spreads to 2.3 ha. Subsequent field research yielded a collection of more than 500 pottery fragments from the Late Hallstatt period. The dispersion of finds shows relatively intensive settlement. The paper also discusses other sites in the surrounding region which date to the same period. The Hallstatt settlement seems to have been a structurally connected complex in the presented area.

scholarly journals Development of a digital surface model and a digital terrain model based on ERS data

2020 ◽  
Vol 905 ◽  
pp. 012025
Author(s):  
I G Gairabekov ◽  
A I Hamzatov ◽  
A T Mishieva ◽  
E I Ibragimova ◽  
M-B I Gairabekov ◽  
...  
Keyword(s):  
Digital Terrain Model ◽  
Surface Model ◽  
Digital Surface Model ◽  
Terrain Model ◽  
Model Based ◽  
Digital Terrain

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.

Extraction of digital terrain model based on regular mesh generation in mountainous areas

2017 ◽  
Vol 77 (5) ◽  
pp. 6267-6286
Author(s):  
Wenhui Li ◽  
Daifeng Han ◽  
Huiying Li ◽  
Xuezhi Wang ◽  
Jinlong Zhu
Keyword(s):  
Mesh Generation ◽  
Digital Terrain Model ◽  
Mountainous Areas ◽  
Terrain Model ◽  
Model Based ◽  
Digital Terrain

scholarly journals The Effect of LiDAR Sampling Density on DTM Accuracy for Areas with Heavy Forest Cover

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 265
Author(s):  
Mihnea Cățeanu ◽  
Arcadie Ciubotaru
Keyword(s):  
Forest Cover ◽  
Initial Point ◽  
Ground Surface ◽  
Digital Terrain Model ◽  
Morphological Data ◽  
Sampling Density ◽  
Terrain Model ◽  
Digital Terrain ◽  
Point Density ◽  
The Impact

Laser scanning via LiDAR is a powerful technique for collecting data necessary for Digital Terrain Model (DTM) generation, even in densely forested areas. LiDAR observations located at the ground level can be separated from the initial point cloud and used as input for the generation of a Digital Terrain Model (DTM) via interpolation. This paper proposes a quantitative analysis of the accuracy of DTMs (and derived slope maps) obtained from LiDAR data and is focused on conditions common to most forestry activities (rough, steep terrain with forest cover). Three interpolation algorithms were tested: Inverse Distance Weighted (IDW), Natural Neighbour (NN) and Thin-Plate Spline (TPS). Research was mainly focused on the issue of point data density. To analyze its impact on the quality of ground surface modelling, the density of the filtered data set was artificially lowered (from 0.89 to 0.09 points/m2) by randomly removing point observations in 10% increments. This provides a comprehensive method of evaluating the impact of LiDAR ground point density on DTM accuracy. While the reduction of point density leads to a less accurate DTM in all cases (as expected), the exact pattern varies by algorithm. The accuracy of the LiDAR-derived DTMs is relatively good even when LiDAR sampling density is reduced to 0.40–0.50 points/m2 (50–60 % of the initial point density), as long as a suitable interpolation algorithm is used (as IDW proved to be less resilient to density reductions below approximately 0.60 points/m2). In the case of slope estimation, the pattern is relatively similar, except the difference in accuracy between IDW and the other two algorithms is even more pronounced than in the case of DTM accuracy. Based on this research, we conclude that LiDAR is an adequate method for collecting morphological data necessary for modelling the ground surface, even when the sampling density is significantly reduced.

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