Work place: School of Geoscience and Info-physics Central South University Changsha, Hunan Province, 410083, China
E-mail: you-xiwenfeng@163.com
Website:
Research Interests: Earth Sciences, Earth & Environmental Sciences
Biography
Wenfeng Xi, was born in Ji’an in Jiangxi Province in 1989, finished her undergraduate study in Jilin Institute of Architecture and Civil Engineering in 2010, Now is studying in Central South University, is majoring in Cartography and Geographical Information System.
By Yanhong Zou Xiancheng Mao Wenfeng Xi
DOI: https://doi.org/10.5815/ijem.2012.03.09, Pub. Date: 29 Jun. 2012
Aiming at the spatial shape analysis of complex geological bodies in stereoscopic quantitative prediction of concealed ore bodies, a three-dimensional morphological analysis method for geological bodies based on 3-dimensional raster model under visualization environment was put forward by combining mathematical morphology with Euclidean distance transform theory. Firstly, the 3-dimensional visualization models for geological bodies were constructed on the basis of the 3-dimensional geological modeling (3DGM) technology; Secondly, the algorithm for extracting the surface shape trend of geological body with the 3-dimensional raster model was proposed by using mathematical morphology filtering. By the combination of morphological filtering, global set operation and three-dimensional Euclidean distance transform, the models for the quantitative analysis and extraction of the shape undulance were established. Lastly, as a case study, the three-dimensional morphological analysis method was applied in analyzing quantitatively the Xinwuli magmatic body in Fenghuangshan ore field in Tongling, Anhui Province. By means of the calculation model of Euclidean distance field, the quantitative extraction of the shape trend and shape undulance as the quantitative indexes of geological ore-controlling factors were achieved after building the 3D raster models of the magmatic body. The results show that the morphological analysis method is feasible to calculate various morphological parameters of complex geological bodies and extract quantitative indexes of geological ore-controlling factors successfully for stereoscopic quantitative predication of concealed ore bodies.
[...] Read more.By Yanhong Zou Xiancheng Mao Wenfeng Xi
DOI: https://doi.org/10.5815/ijigsp.2011.04.08, Pub. Date: 8 Jun. 2011
To address the spatial Morphological analysis of complex geological bodies in stereoscopic quantitative prediction of concealed ore bodies, a three-dimensional morphological analysis method for geological bodies based on 3-dimensional raster model under visualization environment was put forward by combining mathematical morphology with Euclidean distance transform theory. Firstly, the 3-dimensional visualization models for geological bodies were constructed on the basis of the 3-dimensional geological modeling (3DGM) technology; Secondly, the algorithm for extracting the surface shape trend of geological body with the 3-dimensional raster model was proposed by using mathematical morphology filtering. By the combination of morphological filtering, global set operation and three-dimensional Euclidean distance transform, the models for the quantitative analysis and hierarchical extraction of the shape undulance were established. Lastly, as a case study, the three-dimensional morphological analysis method was applied in analyzing quantitatively the Xinwuli magmatic body in Fenghuangshan ore field in Tongling, Anhui Province. By means of the calculation model of Euclidean distance field, the quantitative extraction of the shape trend and shape undulance as well as the angle between geological interface and trend surface, as the quantitative indexes of geological ore-controlling factors, were achieved after building the 3D raster models of the magmatic body. The results show that the morphological analysis method is feasible to calculate various morphological parameters of complex geological bodies and extract quantitative indexes of geological ore-controlling factors successfully for stereoscopic quantitative predication of concealed ore bodies.
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