The advancement of Geographic Information Systems(GIS)has brought a wide range of decision-making tools to almost all sectors.However,traditional 2D GIS systems often lack the depth and interconnections that are cruci...The advancement of Geographic Information Systems(GIS)has brought a wide range of decision-making tools to almost all sectors.However,traditional 2D GIS systems often lack the depth and interconnections that are crucial to deep thinking in many applications of GIS,such as urban planning,environmental monitoring and disaster management.This paper describes the use of 3D modelling and Virtual Reality(VR)in GIS platforms as a means of enhancing the full comprehension of complex data.The ability to visualise cities,ecosystems or disaster-prone areas in 3D makes spatial data more intuitive and interactive.VR takes this one step further by allowing stakeholders to move around the virtual environment and interact with data in real time,improving their level of preparedness when making decisions.We discuss the practical applications of these technologies in the fields of urban planning,environmental conservation and disaster management.We also highlight some of the technical challenges involved in building a 3D GIS or VR,such as data processing and user interface design.The paper concludes with some future trends and possible developments in 3D GIS and VR.展开更多
Association rule mining methods, as a set of important data mining tools, could be used for mining spatial association rules of spatial data. However, applications of these methods are limited for mining results conta...Association rule mining methods, as a set of important data mining tools, could be used for mining spatial association rules of spatial data. However, applications of these methods are limited for mining results containing large number of redundant rules. In this paper, a new method named Geo-Filtered Association Rules Mining(GFARM) is proposed to effectively eliminate the redundant rules. An application of GFARM is performed as a case study in which association rules are discovered between building land distribution and potential driving factors in Wuhan, China from 1995 to 2015. Ten sets of regular sampling grids with different sizes are used for detecting the influence of multi-scales on GFARM. Results show that the proposed method can filter 50%–70% of redundant rules. GFARM is also successful in discovering spatial association pattern between building land distribution and driving factors.展开更多
文摘The advancement of Geographic Information Systems(GIS)has brought a wide range of decision-making tools to almost all sectors.However,traditional 2D GIS systems often lack the depth and interconnections that are crucial to deep thinking in many applications of GIS,such as urban planning,environmental monitoring and disaster management.This paper describes the use of 3D modelling and Virtual Reality(VR)in GIS platforms as a means of enhancing the full comprehension of complex data.The ability to visualise cities,ecosystems or disaster-prone areas in 3D makes spatial data more intuitive and interactive.VR takes this one step further by allowing stakeholders to move around the virtual environment and interact with data in real time,improving their level of preparedness when making decisions.We discuss the practical applications of these technologies in the fields of urban planning,environmental conservation and disaster management.We also highlight some of the technical challenges involved in building a 3D GIS or VR,such as data processing and user interface design.The paper concludes with some future trends and possible developments in 3D GIS and VR.
基金Under the auspices of Special Fund of Ministry of Land and Resources of China in Public Interest(No.201511001)
文摘Association rule mining methods, as a set of important data mining tools, could be used for mining spatial association rules of spatial data. However, applications of these methods are limited for mining results containing large number of redundant rules. In this paper, a new method named Geo-Filtered Association Rules Mining(GFARM) is proposed to effectively eliminate the redundant rules. An application of GFARM is performed as a case study in which association rules are discovered between building land distribution and potential driving factors in Wuhan, China from 1995 to 2015. Ten sets of regular sampling grids with different sizes are used for detecting the influence of multi-scales on GFARM. Results show that the proposed method can filter 50%–70% of redundant rules. GFARM is also successful in discovering spatial association pattern between building land distribution and driving factors.
