In the context of rapid urbanization,cities must leverage their unique advantages to enhance their competitiveness.It has become a prevalent practice to integrate Chinese cultural elements into a city’s brand identit...In the context of rapid urbanization,cities must leverage their unique advantages to enhance their competitiveness.It has become a prevalent practice to integrate Chinese cultural elements into a city’s brand identity,as well as to transform and elevate the existing landscape.This paper examines the landscape evolution of Nanchang Bayi Park(Baihuazhou)and the associated measures for its transformation and enhancement.The findings indicate that,from the perspective of urban visual art,these transformations significantly enhance the city’s aesthetic perception and more effectively address the needs of people.Consequently,this contributes to the ongoing improvement and development of the city’s brand image.By modifying the urban structure,enhancing the urban environment,upgrading infrastructure,and elevating the cultural levels within urban areas,the objective of transforming and upgrading urban landscapes can be realized.展开更多
Complex urban scenery is generally composed of gigantic amount of detailed buildings, efficient representation and rendering are essential for its visualization. We present an accelerating method for urban visualizati...Complex urban scenery is generally composed of gigantic amount of detailed buildings, efficient representation and rendering are essential for its visualization. We present an accelerating method for urban visualization. Our approach can optimize the organization of models in accordance with the quadtree based terrain, which makes the parallelization easier. Through minimizing the draw call within one rendering process, our approach can reduce the time cost of each frame and improve the framerate greatly. Hereby, our system can handle large-scale detailed models with high diversity and also can afford the ability to adjust the rendering strategy automatically according to the state of the hardware.展开更多
Higher-order patterns reveal sequential multistep state transitions,which are usually superior to origin-destination analyses that depict only first-order geospatial movement patterns.Conventional methods for higher-o...Higher-order patterns reveal sequential multistep state transitions,which are usually superior to origin-destination analyses that depict only first-order geospatial movement patterns.Conventional methods for higher-order movement modeling first construct a directed acyclic graph(DAG)of movements and then extract higher-order patterns from the DAG.However,DAG-based methods rely heavily on identifying movement keypoints,which are challenging for sparse movements and fail to consider the temporal variants critical for movements in urban environments.To overcome these limitations,we propose HoLens,a novel approach for modeling and visualizing higher-order movement patterns in the context of an urban environment.HoLens mainly makes twofold contributions:First,we designed an auto-adaptive movement aggregation algorithm that self-organizes movements hierarchically by considering spatial proximity,contextual information,and tem-poral variability.Second,we developed an interactive visual analytics interface comprising well-established visualization techniques,including the H-Flow for visualizing the higher-order patterns on the map and the higher-order state sequence chart for representing the higher-order state transitions.Two real-world case studies demonstrate that the method can adaptively aggregate data and exhibit the process of exploring higher-order patterns using HoLens.We also demonstrate the feasibility,usability,and effectiveness of our approach through expert interviews with three domain experts.展开更多
Recent years have witnessed the rapid development and wide adoption of immersive head-mounted devices,such as HTC VIVE,Oculus Rift,and Microsoft HoloLens.These immersive devices have the potential to significantly ext...Recent years have witnessed the rapid development and wide adoption of immersive head-mounted devices,such as HTC VIVE,Oculus Rift,and Microsoft HoloLens.These immersive devices have the potential to significantly extend the methodology of urban visual analytics by providing critical 3D context information and creating a sense of presence.In this paper,we propose a theoretical model to characterize the visualizations in immersive urban analytics.Furthermore,based on our comprehensive and concise model,we contribute a typology of combination methods of 2D and 3D visualizations that distinguishes between linked views,embedded views,and mixed views.We also propose a supporting guideline to assist users in selecting a proper view under certain circumstances by considering visual geometry and spatial distribution of the 2D and 3D visualizations.Finally,based on existing work,possible future research opportunities are explored and discussed.展开更多
Recent achievements in deep learning(DL)have demonstrated its potential in predicting traffic flows.Such predictions are beneficial for understanding the situation and making traffic control decisions.However,most sta...Recent achievements in deep learning(DL)have demonstrated its potential in predicting traffic flows.Such predictions are beneficial for understanding the situation and making traffic control decisions.However,most state-of-the-art DL models are consi-dered“black boxes”with little to no transparency of the underlying mechanisms for end users.Some previous studies attempted to“open the black box”and increase the interpretability of generated predictions.However,handling complex models on large-scale spatiotemporal data and discovering salient spatial and temporal patterns that significantly influence traffic flow remain challenging.To overcome these challenges,we present TrafPS,a visual analytics approach for interpreting traffic prediction outcomes to support decision-making in traffic management and urban planning.The measurements region SHAP and trajectory SHAP are proposed to quantify the impact of flow patterns on urban traffic at different levels.Based on the task requirements from domain experts,we employed an interactive visual interface for the multi-aspect exploration and analysis of significant flow patterns.Two real-world case studies demonstrate the effectiveness of TrafPS in identifying key routes and providing decision-making support for urban planning.展开更多
文摘In the context of rapid urbanization,cities must leverage their unique advantages to enhance their competitiveness.It has become a prevalent practice to integrate Chinese cultural elements into a city’s brand identity,as well as to transform and elevate the existing landscape.This paper examines the landscape evolution of Nanchang Bayi Park(Baihuazhou)and the associated measures for its transformation and enhancement.The findings indicate that,from the perspective of urban visual art,these transformations significantly enhance the city’s aesthetic perception and more effectively address the needs of people.Consequently,this contributes to the ongoing improvement and development of the city’s brand image.By modifying the urban structure,enhancing the urban environment,upgrading infrastructure,and elevating the cultural levels within urban areas,the objective of transforming and upgrading urban landscapes can be realized.
基金Supported by National Natural Science Foundation of China(Nos.61170205,61232014,61472010 and 61421062)National Key Technology Support Program of China(No.2013BAK03B07)
文摘Complex urban scenery is generally composed of gigantic amount of detailed buildings, efficient representation and rendering are essential for its visualization. We present an accelerating method for urban visualization. Our approach can optimize the organization of models in accordance with the quadtree based terrain, which makes the parallelization easier. Through minimizing the draw call within one rendering process, our approach can reduce the time cost of each frame and improve the framerate greatly. Hereby, our system can handle large-scale detailed models with high diversity and also can afford the ability to adjust the rendering strategy automatically according to the state of the hardware.
基金supported in part by the Shenzhen Science and Technology Program(No.ZDSYS20210623092007023)in part by the National Natural Science Foundation of China(No.62172398)the Guangdong Basic and Applied Basic Research Foundation(No.2021A1515011700).
文摘Higher-order patterns reveal sequential multistep state transitions,which are usually superior to origin-destination analyses that depict only first-order geospatial movement patterns.Conventional methods for higher-order movement modeling first construct a directed acyclic graph(DAG)of movements and then extract higher-order patterns from the DAG.However,DAG-based methods rely heavily on identifying movement keypoints,which are challenging for sparse movements and fail to consider the temporal variants critical for movements in urban environments.To overcome these limitations,we propose HoLens,a novel approach for modeling and visualizing higher-order movement patterns in the context of an urban environment.HoLens mainly makes twofold contributions:First,we designed an auto-adaptive movement aggregation algorithm that self-organizes movements hierarchically by considering spatial proximity,contextual information,and tem-poral variability.Second,we developed an interactive visual analytics interface comprising well-established visualization techniques,including the H-Flow for visualizing the higher-order patterns on the map and the higher-order state sequence chart for representing the higher-order state transitions.Two real-world case studies demonstrate that the method can adaptively aggregate data and exhibit the process of exploring higher-order patterns using HoLens.We also demonstrate the feasibility,usability,and effectiveness of our approach through expert interviews with three domain experts.
基金The work was supported by National 973 Program of China(2015CB352503)National Natural Science Foundation of China(61772456,U1609217)+5 种基金NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization(U1609217)NSFC(61502416)Zhejiang Provincial Natural Science Foundation(LR18F020001)the Fundamental Research Funds for Central Universities(2016QNA5014)the research fund of the Ministry of Education of China(188170-170160502)the 100 Talents Program of Zhejiang University.This project is also partially funded by Microsoft Research Asia.
文摘Recent years have witnessed the rapid development and wide adoption of immersive head-mounted devices,such as HTC VIVE,Oculus Rift,and Microsoft HoloLens.These immersive devices have the potential to significantly extend the methodology of urban visual analytics by providing critical 3D context information and creating a sense of presence.In this paper,we propose a theoretical model to characterize the visualizations in immersive urban analytics.Furthermore,based on our comprehensive and concise model,we contribute a typology of combination methods of 2D and 3D visualizations that distinguishes between linked views,embedded views,and mixed views.We also propose a supporting guideline to assist users in selecting a proper view under certain circumstances by considering visual geometry and spatial distribution of the 2D and 3D visualizations.Finally,based on existing work,possible future research opportunities are explored and discussed.
基金supported in part by a Grant in-Aid for Scientific Research B(22H03573)of the Japan Society for the Promotion of Science(JSPS)in part by the National Natural Science Foundation of China(92067109,61873119)+1 种基金in part by Shenzhen Science and Technology Program(ZDSYS20210623092007023,GJHZ20210705141808024)in part by Guangdong Key Program(2021QN02X794)。
文摘Recent achievements in deep learning(DL)have demonstrated its potential in predicting traffic flows.Such predictions are beneficial for understanding the situation and making traffic control decisions.However,most state-of-the-art DL models are consi-dered“black boxes”with little to no transparency of the underlying mechanisms for end users.Some previous studies attempted to“open the black box”and increase the interpretability of generated predictions.However,handling complex models on large-scale spatiotemporal data and discovering salient spatial and temporal patterns that significantly influence traffic flow remain challenging.To overcome these challenges,we present TrafPS,a visual analytics approach for interpreting traffic prediction outcomes to support decision-making in traffic management and urban planning.The measurements region SHAP and trajectory SHAP are proposed to quantify the impact of flow patterns on urban traffic at different levels.Based on the task requirements from domain experts,we employed an interactive visual interface for the multi-aspect exploration and analysis of significant flow patterns.Two real-world case studies demonstrate the effectiveness of TrafPS in identifying key routes and providing decision-making support for urban planning.
