Symposium on CyberGIS and Spatial Data Science: Geocomputation for Processing Spatial Big Data

Type: Paper
Theme:
Sponsor Groups: Spatial Analysis and Modeling Specialty Group, Cyberinfrastructure Specialty Group, Geographic Information Science and Systems Specialty Group
Poster #:
Day: 4/10/2018
Start / End Time: 4:40 PM / 6:20 PM
Room: Grand Ballroom A, Astor, 2nd Floor
Organizers: Hao Hu, Dalia Varanka, Chuanrong Zhang
Chairs: Chuanrong Zhang

Description

Spatial data collected through remote sensing, smart phone, geo-located sensors, laser scanning, navigation satellite system, and social network grow rapidly. The big spatial data has great potentials to be used for addressing grand challenges ranging from energy and environmental sustainability to health and wellness. However, the rapid growth of spatial data presents challenges in processing and analyzing the data. Although significant progress has been made in geocomputation methods and techniques for spatial data analysis, dynamic modeling, and visualization, challenges are posed in developing new geocomputation methods/algorithms that can handle very diverse big spatial data with high spatial and temporal scales. Traditional geocomputation techniques such as spatial statistics, neural networks, heuristic search, cellular automata, and agent-based models requires new geocomputation algorithms and distributed parallel architecture for handling structured and unstructured datasets with massive data volumes. As part of the AAG 2018 Symposium on CyberGIS and Spatial Data Science, this session will assemble talks that present innovative geocomputation methods and techniques for handling big spatial data.

In this session, we invite papers focusing on, but are not limited to, the following topics:
• Spatial statistics suitable for big spatial data analysis
• Semantics and ontologies for big spatial data
• Spatial indexing methods for big spatial data query and analysis
• Efficient spatial simulation models and algorithms for big spatial data
• Novel approaches for assessing big spatial data quality
• Advances in scientific visualization of big spatial data
• Efficient methods for heterogeneous big spatial data integration and query
• Parallel and distributed programming for large spatial data sets
• Spatial data mining and machine learning methods and techniques for handing big spatial data


Agenda

Type Details Minutes Start Time
Presenter Chuanrong Zhang*, University of Connecticut, Department of Geography, Tian Zhao, Department of Computer Science, University of Wisconsin, Milwaukee, USA, Weidong Li, Department of Geography & Center of Environmental Sciences and Engineering, University of Connecticut, Storrs, USA, Efficient spatial knowledge queries of The National Map using Geospatial Semantic Web technologies 20 4:40 PM
Presenter Ruiting Zhai*, Department of Geography, University of Connecticut, Weidong Li, Department of Geography, University of Connecticut, Chuanrong Zhang, Department of Geography, University of Connecticut, Transiogram: the new index to quantify spatial patterns of landscapes 20 5:00 PM
Presenter Shuyu Zhang*, Zhejiang University, Zhenhong Du, Zhejiang University, Zhongyi Wang, Zhejiang University, Parallel Method for Big Spatial Data Processing with the Consideration of Spatial Distribution 20 5:20 PM
Presenter Halgamage Malinda Siriwardana*, Graduate School of Life and Environmental Science, Division of Spatial Information Science, University of Tsukuba, Japan., Yuji Murayama, Graduate School of Life and Environmental Science, Division of Spatial Information Science, University of Tsukuba, Japan., Extending the dissemination of spatial data in big-data era 20 5:40 PM
Presenter Zhe Zhang*, University of Illinois at Urbana-Champaign, Kirsi Virrantaus, Aalto University of Finland, Dandong Yin, University of Illinois at Urbana-Champaign, Aiman Soliman, University of Illinois at Urbana-Champaign, Shaowen Wang, University of Illinois at Urbana-Champaign, A CyberGIS Enabled Spatiotemporal Population Model for Emergency Management Based on Social Media and Urban Infrastructure Data 20 6:00 PM

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