This paper reports an application of uncertainty visualisation of a regional scale(1:50000)3 D geological geometry model to be involved in GIS-based 3 D mineral potential assessment of the Xiangxibei lead-zinc mineral...This paper reports an application of uncertainty visualisation of a regional scale(1:50000)3 D geological geometry model to be involved in GIS-based 3 D mineral potential assessment of the Xiangxibei lead-zinc mineral concentration area in northwestern Hunan District,China.Three-dimensional(3 D)geological modelling is a process of interpretation that combines a set of input measurements in geometry.Today,technology has become a necessary part of GIS-based deep prospecting.However,issues of sparse data and imperfect understanding exist in the process so that there are several uncertainties in 3 D geological modelling.And these uncertainties are inevitably transmitted into the post-processing applications,such as model-based mineral resource assessment.Thus,in this paper,first,a big-data-based method was used to estimate the uncertainty of a 3 D geological model;second,a group of expectations of geological geometry uncertainty were calculated and integrated into ore-bearing stratoisohypse modelling,which is one of the major favourable parameters of assessment for Lead-Zinc(Pb-Zn)deep prospectivity mapping in northwestern Hunan;and finally,prospecting targets were improved.展开更多
This paper presents the result of an investigation into the utility of the Structure Sensor developed by Occipital Inc.and accuracy of its output for 3D surveying of interiors of buildings in relation to Surveying(Cad...This paper presents the result of an investigation into the utility of the Structure Sensor developed by Occipital Inc.and accuracy of its output for 3D surveying of interiors of buildings in relation to Surveying(Cadastral Survey)Regulation 2005 in Victoria,Australia.The paper investigates data acquisition issues,defines guidelines to obtain the best reconstruction result,and evaluates the result against the requirements set by the Regulation.The findings suggest a mixed result.The sensor delivers more accurate outputs for the smaller room sizes.Also,the accuracy does not meet the requirements,but it was found to be close to what is expected in the Regulation.Finally,the paper argues that the device is user-friendly enough to be used by non-experts for crowdsourcing indoor information and,the accuracy of its output can meet the needs of other domains such as indoor navigation and public safety.展开更多
Today’s era of big data is witnessing a gradual increase in the amount of data,more correlations between data,as well as growth in their spatial dimension.Conventional linear statistical models applied to mineral pro...Today’s era of big data is witnessing a gradual increase in the amount of data,more correlations between data,as well as growth in their spatial dimension.Conventional linear statistical models applied to mineral prospectivity mapping(MPM)perform poorly because of the random and nonlinear nature of metallogenic processes.To overcome this performance degradation,deep learning models have been introduced in 3 D MPM.In this study,taking the Huayuan sedimentary Mn deposit in Hunan Province as an example,we construct a 3 D digital model of this deposit based on the prospectivity model of the study area.In this approach,3 D predictor layers are converted from the conceptual model and employed in a 3 D convolutional neural network(3 D CNN).The characteristics of the spatial distribution are extracted by the 3 D CNN.Subsequently,we divide the 22 extracted ore-controlling variables into six groups for contrast experiments based on various combinations and further apply the 3 D CNN model and weight of evidence(WofE)method on each group.The predictive model is trained on the basis of the coupling correlation between the spatial distributions of the variables and the underground occurrence space of the Mn orebodies,and the correlation between different ore-controlling factors.The analysis of 12 factors indicates that the 3 D CNN model performs well in the 3 D MPM,achieving a promising accuracy of up to 100%and a loss value below 0.001.A comparison shows that the 3 D CNN model outperforms the WofE model in terms of predictive evaluation indexes,namely the success rate and ore-controlling rate.In particular,the 1–12 ore-controlling factors selected in experiment 5 provide a significantly better prediction effect than the other factors.Consequently,we conclude that the Mn deposit in the study area is not only related to the stratum and interlaminar anomalous bodies but also to the spatial distribution of the faults.The experimental results confirm that the proposed 3 D CNN is promising for 3 D MPM as it eliminates the interference factors.展开更多
3D geo spatial data have become the normal.However,to view the data,usually expert software is required,which have up to now hindered the wide spread use of 3D scenes for the display of geological data.The internet re...3D geo spatial data have become the normal.However,to view the data,usually expert software is required,which have up to now hindered the wide spread use of 3D scenes for the display of geological data.The internet real time 3D rendering framework X3D is assessed regarding its suitability for building a geological GIS on the internet.Especially important for geological data,3D rendering enhances the intuitive grasp of the data and enables the user to interactively explore it.It is often necessary to find a solution to distribute this data to a wide range of interested parties,experts and non-experts alike.According to the nature of 3D data,the best technique to display geo-data,the modeling of objects and unresolved issues have to be taken into consideration.The internet is the apparent tool for the public distribution and visualization of 3D data and it was found that through the open ISO-standardized format X3D it offers a multitude of possibilities.A 3D geological interactive map was created with these prerequisites to identify challenges and possibilities through this process.It was found that the use of lead to satisfactory results,that could probably not have been achieved with another technology.展开更多
基金financially supported by the National Natural Science Foundation of China(Nos.41972311,41672330)the National Key Research and Development Program of China(No.2017YFC0601501)the National Key Technology Research and Development Program of the Ministry of Science and Technology of China(No.2006BAB01A01)。
文摘This paper reports an application of uncertainty visualisation of a regional scale(1:50000)3 D geological geometry model to be involved in GIS-based 3 D mineral potential assessment of the Xiangxibei lead-zinc mineral concentration area in northwestern Hunan District,China.Three-dimensional(3 D)geological modelling is a process of interpretation that combines a set of input measurements in geometry.Today,technology has become a necessary part of GIS-based deep prospecting.However,issues of sparse data and imperfect understanding exist in the process so that there are several uncertainties in 3 D geological modelling.And these uncertainties are inevitably transmitted into the post-processing applications,such as model-based mineral resource assessment.Thus,in this paper,first,a big-data-based method was used to estimate the uncertainty of a 3 D geological model;second,a group of expectations of geological geometry uncertainty were calculated and integrated into ore-bearing stratoisohypse modelling,which is one of the major favourable parameters of assessment for Lead-Zinc(Pb-Zn)deep prospectivity mapping in northwestern Hunan;and finally,prospecting targets were improved.
基金This work was supported by the University of Melbourne[grant number 501327].
文摘This paper presents the result of an investigation into the utility of the Structure Sensor developed by Occipital Inc.and accuracy of its output for 3D surveying of interiors of buildings in relation to Surveying(Cadastral Survey)Regulation 2005 in Victoria,Australia.The paper investigates data acquisition issues,defines guidelines to obtain the best reconstruction result,and evaluates the result against the requirements set by the Regulation.The findings suggest a mixed result.The sensor delivers more accurate outputs for the smaller room sizes.Also,the accuracy does not meet the requirements,but it was found to be close to what is expected in the Regulation.Finally,the paper argues that the device is user-friendly enough to be used by non-experts for crowdsourcing indoor information and,the accuracy of its output can meet the needs of other domains such as indoor navigation and public safety.
基金financially supported by the Chinese MOST project“Methods and Models for Quantitative Prediction of Deep Metallogenic Geological Anomalies”(No.2017YFC0601502)and“Research on key technology of mineral prediction based on geological big data analysis”(No.6142A01190104)。
文摘Today’s era of big data is witnessing a gradual increase in the amount of data,more correlations between data,as well as growth in their spatial dimension.Conventional linear statistical models applied to mineral prospectivity mapping(MPM)perform poorly because of the random and nonlinear nature of metallogenic processes.To overcome this performance degradation,deep learning models have been introduced in 3 D MPM.In this study,taking the Huayuan sedimentary Mn deposit in Hunan Province as an example,we construct a 3 D digital model of this deposit based on the prospectivity model of the study area.In this approach,3 D predictor layers are converted from the conceptual model and employed in a 3 D convolutional neural network(3 D CNN).The characteristics of the spatial distribution are extracted by the 3 D CNN.Subsequently,we divide the 22 extracted ore-controlling variables into six groups for contrast experiments based on various combinations and further apply the 3 D CNN model and weight of evidence(WofE)method on each group.The predictive model is trained on the basis of the coupling correlation between the spatial distributions of the variables and the underground occurrence space of the Mn orebodies,and the correlation between different ore-controlling factors.The analysis of 12 factors indicates that the 3 D CNN model performs well in the 3 D MPM,achieving a promising accuracy of up to 100%and a loss value below 0.001.A comparison shows that the 3 D CNN model outperforms the WofE model in terms of predictive evaluation indexes,namely the success rate and ore-controlling rate.In particular,the 1–12 ore-controlling factors selected in experiment 5 provide a significantly better prediction effect than the other factors.Consequently,we conclude that the Mn deposit in the study area is not only related to the stratum and interlaminar anomalous bodies but also to the spatial distribution of the faults.The experimental results confirm that the proposed 3 D CNN is promising for 3 D MPM as it eliminates the interference factors.
文摘3D geo spatial data have become the normal.However,to view the data,usually expert software is required,which have up to now hindered the wide spread use of 3D scenes for the display of geological data.The internet real time 3D rendering framework X3D is assessed regarding its suitability for building a geological GIS on the internet.Especially important for geological data,3D rendering enhances the intuitive grasp of the data and enables the user to interactively explore it.It is often necessary to find a solution to distribute this data to a wide range of interested parties,experts and non-experts alike.According to the nature of 3D data,the best technique to display geo-data,the modeling of objects and unresolved issues have to be taken into consideration.The internet is the apparent tool for the public distribution and visualization of 3D data and it was found that through the open ISO-standardized format X3D it offers a multitude of possibilities.A 3D geological interactive map was created with these prerequisites to identify challenges and possibilities through this process.It was found that the use of lead to satisfactory results,that could probably not have been achieved with another technology.
