Geospatial Big Data: Theory, Methods, and Applications I
The session recording will be archived on the site until June 25th, 2023
This session was streamed but not recorded
Date: 3/27/2023
Time: 8:30 AM - 9:50 AM
Room: Governors Square 15, Sheraton, Concourse Level
Type: Paper,
Theme:
Curated Track: AAG's GeoEthics Initiative and Related Effort
Sponsor Group(s):
Geographic Information Science and Systems Specialty Group, Remote Sensing Specialty Group, Spatial Analysis and Modeling Specialty Group
Organizer(s):
Lei Zou Texas A&M University
A-Xing Zhu University of Wisconsin - Madison
Harvey Miller The Ohio State University
Guido Cervone The Pennsylvania State University
Yongze Song Curtin University
Chair(s):
Lei Zou Texas A&M University
Description:
The recent digital technological revolution has enabled the creation and collection of large, diverse geospatial data from satellite and drone images, social and news media platforms, smartphone applications, onsite or portable devices, surveillance vehicles, sensor networks, and crowdsourcing tools. These data, referred to as geospatial big data, offer a unique lens to rapidly, timely, and multi-dimensionally observe the dynamics of human behaviors, urban development, and environmental systems. Consequently, a growing interest from academia, government, organizations, and the general public leverages geospatial big data to observe the social and environmental systems and support decision-making.
Previous research and practices have successfully applied geospatial big data in solving multiple real-world challenges, e.g., disaster management, pandemic control, smart city, urban planning, precise agriculture, etc. However, existing literature also identifies limitations and new challenges in the theory, methods, and applications of geospatial big data. Initially, the definition of geospatial big data is conceptualized from the four Vs of big data, but the definition is vague and inconsistent. In addition, although the use of geospatial big data has been ubiquitous, the methodologies of collecting, analyzing, and visualizing geospatial big data, especially those newly emerged data, remain technically challenging and are usually subjectively determined by researchers or practitioners. Meanwhile, uncertainties and ethical concerns should be considered in geospatial big data and analysis methods but are paid less attention in previous studies. Finally, more interdisciplinary explorations of geospatial big data applications in different fields are needed to fully unleash their potential.
Presentations (if applicable) and Session Agenda:
Yue Lin, University of Chicago |
Exploring the Tradeoff Between Privacy and Utility of Geographic Data Using a Multiobjective Optimization Approach |
Hongyu Zhang, University of Massachusetts - Amherst |
A spatial-temporal public opinion analysis of IP location disclosure on Chinese social media platforms using Weibo data |
Theodros Woldeyohannes, University of New Mexico |
A multi-scalar geographic mixed method approach to assess environmental justice issues for unregulated waste disposal sites |
Anqi Zhang |
Relationships between 3D urban form and ground-level fine particulate matter at street block level: Evidence from fifteen metropolises in China |
Lei Zou, Texas A&M |
Social Media Data Mining with GeoAI: Opportunities and Challenges |
Non-Presenting Participants
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Geospatial Big Data: Theory, Methods, and Applications I
Description
Type: Paper,
Date: 3/27/2023
Time: 8:30 AM - 9:50 AM
Room: Governors Square 15, Sheraton, Concourse Level
Contact the Primary Organizer
Lei Zou Texas A&M University
lzou@tamu.edu
Session Sponsored By
