Spatial and temporal processes visualization for marine environmental data using particle system

Zhang, Feng; Mao, Ruichen; Du, Zhenhong; Liu, Renyi

doi:10.1016/j.cageo.2019.02.012

Cited by 14 publications

(7 citation statements)

References 35 publications

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“…Zheng and Xie reviewed the predicament of the rural development environment based on the background of Hewlett-Packard Finance and put forward corresponding countermeasures and suggestions [ 2 ]. Zhang et al believed that the differences between different time dimensions in the economy and society had a certain impact on environmental visualization [ 3 ]. Chun identified and revealed the coupling relationship between urban development and ecological environment visualization under the HP financial economic effect and its formation mechanism and then proposed control measures conducive to urban management decision-making [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Influence of HP Financial Economic Effect on Environmental Visualization under Sustainable Development

2022

Journal of Environmental and Public Health

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With the proposal of a sustainable development strategy, HP Finance has received extensive attention in the market, and its economic effects have also promoted the vitality of social development. However, the core of sustainable development is to achieve a two-dimensional balance between economic effects and the environment. In recent years, ecological and environmental problems have become more and more prominent and continue to bring challenges to the sustainable development of society. Environmental visualization plays an increasingly important role in the development of the times. Only by understanding the influencing factors of environmental visualization and promoting the healthy development of environmental visualization can social development goals be achieved. In the context of the social implementation of sustainable development strategies, this article deeply studies the impact of HP's financial economic effects on environmental visualization. Based on analyzing the development characteristics and status quo of the two, a fixed-effect model and a spatial model were constructed, and the specific impact of economic effects on environmental visualization was further explored. It was found through regression analysis that the breadth of coverage of economic effects and the depth of use improved the development efficiency of environmental visualization at the significance level of 0.05, respectively. However, the degree of opening to the outside world and the industrial structure in the economic effect hindered the development of environmental visualization. Its regression coefficients were −0.142, −0.134 and −0.527, −0.537. In the regression analysis of the spatial effect with a significance level of 0.01, the HP financial economic effect could promote the development of local environmental visualization, but it also hindered the development of adjacent environmental visualization. It shows that only the balanced development of economic efficiency among various regions can promote the positive improvement of the level of environmental visualization.

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Section: Introductionmentioning

confidence: 99%

[Retracted] Influence of HP Financial Economic Effect on Environmental Visualization under Sustainable Development

2022

Journal of Environmental and Public Health

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“…Particle tracking is a well-known technique for the determination of velocity vectors according to the local velocity observations in a flow field [20]. Cellular Automaton (CA) is adopted to simulate the spatio-temporal interactions between cells [35].…”

Section: Particle Trackingmentioning

confidence: 99%

“…Scientific flow visualization is used to show the distribution of various data, such as water level, water depth, flow velocity, and pollutant concentration. Particle tracking, streamline rendering, and contour surface rendering are most commonly used to present flow conditions [17][18][19][20][21]. Visual flow effects are used to simulate water surface changes using computer graphics technology, enhancing the sense of reality in a virtual geographic environment [22][23][24][25][26].…”

Section: Introductionmentioning

confidence: 99%

Flow Modeling and Rendering to Support 3D River Shipping Based on Cross-Sectional Observation Data

Zhang

Liu

et al. 2020

IJGI

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The flow in meandering rivers is characterized by rapid changes in flow velocity and water level, especially in flooded environments. Accurate cross-sectional observation data enable continuous monitoring of flow conditions, which is important for river navigation. In this paper, cross-sectional data based flow modeling and rendering methods are studied to build an interactive hybrid flow environment for three-dimensional river shipping. First, the sparse cross-sectional data are extrapolated and interpolated to provide dense sampling points. Then, the data are visualized separately by dynamic texture mapping, particle tracking, streamline rendering, and contour surface rendering. Finally, the rendering models are integrated with ship animation to build a comprehensive hybrid river navigation scenario. The proposed methods are tested by visualizing measured cross-sectional data in the Yangtze River using an open-source software, called World Wind. The experimental results demonstrate that the hybrid flow rendering achieves comprehensive visual effect and the rendering frame rate is greater than 30. The interactive hybrid flow visualization is beneficial to support river shipping analysis.

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“…To reveal the dynamic characteristics of geographic phenomena and discover their association patterns, they proposed an event-based spatiotemporal association rule mining framework with two strategies; a sequence and an episode [47]. To visualize marine dynamic environments, the three-dimensional temporal-spatial process visualization component based on particle system was designed [48], also the interactive multi-scale, multivariate visualization system with a unified visual data service and a component-based visualization structure was developed [49].…”

Section: Introductionmentioning

confidence: 99%

PoSDMS: A Mining System for Oceanic Dynamics with Time Series of Raster-Formatted Datasets

Xue

et al. 2022

Remote Sensing

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Many effective and advanced methods have been developed to explore oceanic dynamics using time series of raster-formatted datasets; however, they have generally been designed at a scale suitable for data observation and used independently of each other, despite the potential advantages of combining different modules into an integrated system at a scale suited for dynamic evolution. From raster-formatted datasets to marine knowledge, we developed and integrated several mining algorithms at a dynamic evolutionary scale and combined them into six modules: a module of raster-formatted dataset pretreatment; a module of process-oriented object extraction; a module of process-oriented representation and management (process-oriented graph database); a module of process-oriented clustering; a module of process-oriented association rule mining; and a module of process-oriented visualization. On the basis of such modules, we developed a process-oriented spatiotemporal dynamic mining system named PoSDMS (Process-oriented Spatiotemporal Dynamics Mining System). PoSDMS was designed to have the capacity to deal with at least six environments of marine anomalies with 40 years of raster-formatted datasets, including their extraction, representation, storage, clustering, association and visualization. The effectiveness of the integrated system was evaluated in a case study of sea surface temperature datasets during the period from January 1982 to December 2021 in global oceans. The main contribution of this study was the development of a mining system at a scale suited for dynamic evolution, providing an analyzing platform or tool to deal with time series of raster-formatted datasets to aid in obtaining marine knowledge.

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Spatial and temporal processes visualization for marine environmental data using particle system

Cited by 14 publications

References 35 publications

[Retracted] Influence of HP Financial Economic Effect on Environmental Visualization under Sustainable Development

[Retracted] Influence of HP Financial Economic Effect on Environmental Visualization under Sustainable Development

Flow Modeling and Rendering to Support 3D River Shipping Based on Cross-Sectional Observation Data

PoSDMS: A Mining System for Oceanic Dynamics with Time Series of Raster-Formatted Datasets

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