Automatically Construct the Surface Visualization Model with DEM and the Geological Survey Data

2013 ◽  
pp. 594-602
Author(s):  
Xiangyu Yu ◽  
Yixian Xu
Keyword(s):  
Survey Data ◽  
Geological Survey ◽  
Surface Visualization

scholarly journals 3D Geological Implicit Modeling Method of Regular Voxel Splitting Based on Layered Interpolation Data

2021 ◽  
Author(s):  
jian li ◽  
pei-rong liu ◽  
xinyu wang ◽  
hao cui ◽  
yurong ma
Keyword(s):  
Survey Data ◽  
Structure Design ◽  
Modeling Method ◽  
Geological Survey ◽  
Data Conversion ◽  
Geological Body ◽  
Section Data ◽  
Stratigraphic Model ◽  
Implicit Modeling ◽  
Fast Rendering

Abstract In view of the problems in traditional geological modeling methods, such as the insufficient utilization of geological survey data, the inaccurate expression of a stratigraphic model, and the large amount of model data, a 3D geological model cannot be smoothly loaded and rendered on the web end. In this paper, a 3D geological implicit modeling method of regular voxel splitting based on hierarchical interpolation data is proposed. This method first uses the boreholes and geological section data from a geological survey for data conversion and fusion, compares the applicability of different interpolation algorithms through cross-validation research, and uses the best fitting algorithm to interpolate and encrypt discrete points in the formation. Then, it constructs the regular voxels, designs five different regular voxel split types, and divides the voxels. In addition, the data structure design of the voxel split model is implemented, and the irregular voxel metadata structure is analyzed and displayed through Three.js. Using this method, based on the survey data of an area in Zhengzhou, the global workflow from data processing to model construction and visualization is demonstrated. The experimental results show that the model can integrate multisource hierarchical interpolation data; express different stratum structures accurately and smoothly, and can realize the fast rendering, spatial query and analysis of the internal information of a geological body in a browser.

scholarly journals Spatial and correlation analysis of engineering-geological survey data for logistics center construction

Vestnik MGSU ◽  
2019 ◽  
pp. 976-990
Author(s):  
Konstantin V. Kurguzov ◽  
Igor K. Fomenko
Keyword(s):  
Statistical Analysis ◽  
Survey Data ◽  
Spatial Correlation ◽  
Geostatistical Analysis ◽  
Geological Survey ◽  
Spatial Structures ◽  
Geostatistical Methods ◽  
Lack Of Information ◽  
Survey Report ◽  
Deformation Features

Introduction: at present, the geostatistical methodology is broadly used abroad for constructing spatial-correlation and spatial-stochastic models of lithoengineering systems, including description and analysis of soil body heterogeneity. The main goal of this work is an attempt to evaluate the possibility of generating a spatial-correlation model of lithoengineering space based on survey data which could be used for subsequent simulation and deterministic-stochastic analysis of geotechnical structures as well as when designing bases and foundations. Materials and methods: main input parameters for spatial analysis were geological survey report and cone-penetration test (CPT) data. The data were analyzed using descriptive statistic methods, with the calculation of particular and ambiguous values and using statistical software STATISTICA. Later use of the results of the statistical analysis aims at the application of geostatistical interpolation models (kriging) for generating spatial structures of deformation features. The article elaborates experimental correlation functions (variograms) to validate the developed spatial structures. The functions show not only the validity of the spatial simulation but also a level of heterogeneity of the researched soil body. Results: the statistical analysis of the initial data showed relative homogeneity of the researched soil body properties what is substantiated by GOST 20522 instructions. Nevertheless, the geostatistical analysis resulted in the opposite conclusion. Principally, this is due to the lack of information on the researched geological medium. Conclusions: requirements of current Russian standard GOST 20522 do not contain a sufficient amount of information for geostatistical analysis and simulation of a soil body based on modern geostatistical methods. As a result, data of standard engineering-geological researches cannot be used for developing digital foundation models as well as for using probabilistic approaches in geotechnics.

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