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2015 International Conference on Circuits and Systems(CAS 2015)

作者： Shangming Qiu Haosheng Huang Department of Computer Guangdong AIB Polytechnic College Research Group Cartography Vienna University of Technology

Compared to desktop geographic information systems(GIS), current Web GIS are still rather poor in terms of interface and functionality. Much of this discrepancy is due to the limitations of current web standard(HTML4). HTML5 is being developed as the new web standard to replace HTML4. It provides plugin-free graphic supports and enhanced functionality, which make it very promising for the future development of Web GIS. This article introduces three case studies to investigate whether HTML5 can work effectively in developing Web GIS. This is necessary as HTML5 is not designed primarily for geospatial domains. Results of the case studies show that HTML5 can help to develop cross-browser and highly interactive Web GIS with true vector graphic capabilities and enhanced functionality(e.g., spatial analysis).

关键词： HTML5 Web GIS spatial data visualization spatial analysis

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visualization of Big spatial data Using Coresets for Kernel Density Estimates

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IEEE TRANSACTIONS ON BIG data 2021年第3期7卷 524-534页

作者： Zheng, Yan Ou, Yi Lex, Alexander Phillips, Jeff M. Visa Res Palo Alto CA 94306 USA Expedia Inc Bellevue WA 98004 USA Univ Utah Salt Lake City UT 84112 USA

The size of large, geo-located datasets has reached scales where visualization of all data points is inefficient. Random sampling is a method to reduce the size of a dataset, yet it can introduce unwanted errors. We describe a method for subsampling of spatial data suitable for creating kernel density estimates from very large data and demonstrate that it results in less error than random sampling. We also introduce a method to ensure that thresholding of low values based on sampled data does not omit any regions above the desired threshold when working with sampled data. We demonstrate the effectiveness of our approach using both, artificial and real-world large geospatial datasets.

关键词： data visualization Kernel spatial databases visualization Big data Geospatial analysis Sociology spatial data visualization sampling big data coresets

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visualization of Big spatial data using Coresets for Kernel Density Estimates

Visualization of Big Spatial Data using Coresets for Kernel ...

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IEEE visualization in data Science (VDS)

作者： Zheng, Yan Ou, Yi Lex, Alexander Phillips, Jeff M. Visa Res Palo Alto CA 94306 USA Expedia Inc Bellevue WA USA Univ Utah Salt Lake City UT 84112 USA

ISBN: (纸本)9781538631850

关键词： spatial data visualization sampling big data coresets

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Integration and visualization of spatial data in LIFE

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IT-INFORMATION TECHNOLOGY 2017年第4期59卷 161-170页

作者： Lin, Ying-Chi Gross, Anika Kirsten, Toralf Univ Leipzig Inst Informat Augustuspl 10 D-04109 Leipzig Germany Univ Leipzig LIFE Res Ctr Civilizat Dis Philipp Rosenthal Str 27 D-04103 Leipzig Germany

It is usually a challenging task to integrate and analyze huge amounts of heterogeneous data in large-medical research projects. Often meaningful new insights can be achieved by visualizing medical data on geographical maps. For instance in epidemiological studies, data is often explored on a spatial dimension. LIFE is a large epidemiological study, managed by the LIFE Research Center for Civilization Diseases at Leipzig University. The study investigates the health-related states of the local population, e.g. by looking at the role of lifestyle factors on major civilization diseases. To allow for an effective data exploration, the development of sophisticated data analysis and spatial visualization techniques is necessary. Here, we present the interactive web application LIFE spatial data visualization System(LIFE-SDVS) that adds a geographical facet to the data integration and analysis workflow of the LIFE research project.

关键词： spatial data visualization medical research data LIFE

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3D scene and geological modeling using integrated multi-source spatial data: Methodology, challenges, and suggestions

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TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY 2020年 100卷

作者： Pan, Dongdong Xu, Zhenhao Lu, Xinming Zhou, Longquan Li, Haiyan Shandong Univ Geotech & Struct Engn Res Ctr Jinan 250061 Shandong Peoples R China Shandong Univ Sci & Technol Coll Comp Sci & Engn Qingdao 250061 Shandong Peoples R China Shandong Univ Sch Qilu Transportat Jinan 250061 Shandong Peoples R China

The visualization and analysis of massive, mull-source, mull-dimensional, heterogeneous, dynamic, and complex spatial data is playing an increasingly important role in 3D scene and geological modeling. There are great differences in various research fields regarding data acquisition techniques, morphological descriptions, and application purposes of spatial objects. Therefore, based on an existing three-dimensional visualization technology and analysis program of spatial data, an integrated processing method for the effective fusion and analysis of mull-source complex spatial data is proposed. This method combines a massive point cloud model with a digital elevation model, in addition to combining the complex stratum with fault modeling technology. The structural grid and geological grid are effectively combined to realize the unified modeling and visualization of natural and artificial objects. This method was then applied to a 3D modeling scene of deeply buried mines and a geological construction model for open pit mines. The comprehensive and effective utilization of multi-source geological data is realized by using this modeling method. Finally, the challenges of spatial data visualization from the aspects of the difficulties in spatial data acquisition, the complexities of the spatial structure, the constraint relations of geological bodies, and the complexity of the 3D modeling process are discussed in this study. Three specific suggestions are proposed. This study enhances the application efficiency of multi-source spatial data modeling technologies already in practice and provides reference for future applications and developments.

关键词： 3D spatial multi-source data data acquisition method 3D scene and geological modeling technology spatial data visualization

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spatial data analysis with R programming for environment

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HUMAN AND ECOLOGICAL RISK ASSESSMENT 2019年第6期25卷 1521-1530页

作者： Kaya, Efdal Agca, Muge Adiguzel, Fatih Cetin, Mehmet Kocaeli Univ Dept Geomat Engn Nat & Appl Sci Kocaeli Turkey Izmir Katip Celebi Univ Dept Geomat Engn Izmir Turkey Nevsehir Haci Bektas Veli Univ Urgup Sebahat & Erol Toksoz Vocat Sch Programs Cultural Heritage & Tourism Nevsehir Nevsehir Turkey Kastamonu Univ Fac Engn & Architecture Dept Landscape Architecture TR-37150 Kastamonu Turkey

The use of open source software, which has been constantly evolving since the mid-2000s, has affected every research discipline. Disciplines using geographic information systems (GIS) and remote sensing (RS) data have been heavily affected owing to this evolution of technology. Researchers working on these data sets have begun to use open source software intensively. The analysis and visualization of spatial data with the help of open source software has caused the emergence of new different features, which are cost effective and editable by other users. In this study, eight sample points have been used for the analysis of water quality in the Mamasin dam in the 2209/A group project of "Assessment and Modeling with GIS and RS data of the Land Use Effects on Water Quality of Mamasin Dam" supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under its program to support graduate students. While visualizing spatial features of the points, QGIS Desktop 2.18.0 and Studio programs with open source code have been used. The RStudio program is an open source software that allows the use of the functions of the R programming language. This study is an ideal application for spatial analysis studies with the R programming language. The sample points used in the study were analyzed in the laboratories of Department of Environmental Engineering, Aksaray University. spatial properties of the analyzed data were examined by coding in the Studio program that is free open source software. In the analysis process, first, the libraries, Leaflet(), ***(), rgdal(), sp(), raster(), and magrittr(), which are used in the study, have been uploaded. With the help of these libraries, the locations of the sample points are transferred to the OpenStreetMap using latitudes and longitudes of the geographic coordinate system as base map. The pH, conductivity, PO4-P, PO4, dissolved oxygen, and temperature information of each sample points are assigned to the va

关键词： spatial data visualization QGIS RStudio R programming open source software

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RViz: a toolkit for real domain data visualization

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TELECOMMUNICATION SYSTEMS 2015年第2期60卷 337-345页

作者： Kam, Hyeong Ryeol Lee, Sung-Ho Park, Taejung Kim, Chang-Hun Korea Univ Dept Comp & Radio Commun Engn Seoul South Korea Korea Univ Dept Visual Informat Proc Seoul South Korea Onsquare Co Seoul South Korea Duksung Womens Univ Dept Digital Media Seoul South Korea

In computational science and computer graphics, there is a strong requirement to represent and visualize information in the real domain, and many visualization data structures and algorithms have been proposed to achieve this aim. Unfortunately, the dataflow model that is often selected to address this issue in visualization systems is not flexible enough to visualize newly invented data structures and algorithms because this scheme can accept only specific data structures. To address this problem, we propose a new visualization tool, RViz, which is independent of the input information data structures. Since there is no requirement for additional efforts to manage the flow networks and the interface to abstracted information is simple in RViz, any scientific information visualization algorithms are easier to implement than the dataflow model. In this paper, we provide case studies in which we have successfully implemented new data structures and related algorithms using RViz, including geometry synthesis, distance field representation, and implicit surface reconstruction. Through these cases, we show how RViz helps users visualize and understand any hidden insights in input information.

关键词： spatial data visualization visualization toolkit Decorator pattern Lightweight framework

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tramoTDA: A trajectory monitoring system using Topological data Analysis

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SOFTWAREX 2024年 28卷

作者： Esteve, Miriam Falco, Antonio CEU Univ Univ Cardenal Herrera CEU Dept Matemat Fis & Ciencias Tecnol Valencia Spain

Due to the rapid proliferation of mobile devices and advanced tracking sensors, there is a significant increase in data production daily. In response, we have created tramoTDA, a Python library that uses Topological data Analysis (TDA) to enable intuitive and visually-oriented classification of trajectory data. This tool offers a unique approach by focusing on the data's topological properties, which enables the identification of subtle and critical patterns often missed by conventional methods. tramoTDA combines scientific rigor with userfriendly design, making it suitable for both technical and non-technical users in diverse applications such as urban planning and maritime navigation. Through its innovative use of TDA, tramoTDA not only enhances data interpretation but also facilitates new research opportunities in complex system analysis, positioning it as a pivotal resource in data science and analytics.

关键词： Topological data Analysis Trajectory classification spatial data visualization Urban planning

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An interactive visual analysis tool for investigating teleconnections in climate simulations

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ENVIRONMENTAL EARTH SCIENCES 2019年第10期78卷 294-294页

作者： Antonov, Anatoliy Lohmann, Gerrit Ionita, Monica Dima, Mihai Linsen, Lars Jacobs Univ Bremen Germany Alfred Wegener Inst Bremerhaven Germany Univ Bucharest Bucharest Romania Westfalische Wilhelms Univ Munster Munster Germany

Teleconnections refer to links between regions that are distant to each other, but nevertheless exhibit some relation. The study of such teleconnections is a well-known task in climate research. Climate simulation shall model known teleconnections. Detecting teleconnections in climate simulations is a crucial aspect in judging the quality of the simulation output. It is common practice to run scripts to execute a sequence of analysis steps on the climate simulations to search for teleconnections. Such a scripting approach is not flexible and targeted towards one specific goal. It is desirable to have one tool that allows for a flexible analysis of all teleconnection patterns with a dataset. We present such a tool, where the extracted information is provided in an intuitive visual form to users, who then can interactively explore the data. We developed an analysis workflow that is modeled around four views showing different facets of the data with coordinated interaction. We present a teleconnection study with simulation ensembles and reanalysis data obtained by data assimilation to observe how well the teleconnectivity patterns match and to demonstrate the effectiveness of our tool.

关键词： Interactive visual analysis Teleconnections Coordinated views spatial data visualization Multidimensional data projection Segmentation

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Quantitative visualization of biological data in Google Earth using R2G2, an R CRAN package

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MOLECULAR ECOLOGY RESOURCES 2012年第6期12卷 1177-1179页

作者： Arrigo, Nils Albert, Loren P. Mickelson, Pascal G. Barker, Michael S. Univ Arizona Dept Ecol & Evolutionary Biol Tucson AZ 85721 USA Univ Arizona Coll Opt Sci Tucson AZ 85721 USA

We briefly introduce R2G2, an R CRAN package to visualize spatially explicit biological data within the Google Earth interface. Our package combines a collection of basic graph-editing features, including automated placement of dots, segments, polygons, images (including graphs produced with R), along with several complex three-dimensional (3D) representations such as phylogenies, histograms and pie charts. We briefly present some example data sets and show the immediate benefits in communication gained from using the Google Earth interface to visually explore biological results. The package is distributed with detailed help pages providing examples and annotated source scripts with the hope that users will have an easy time using and further developing this package. R2G2 is distributed on http://***/web/packages.

关键词： keyhole markup language phylogeny R package spatial data visualization species diversity

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