Advanced Technologies in Spatial Data Collection and Analysis (Volume II)

A special issue of Geographies (ISSN 2673-7086).

Deadline for manuscript submissions: closed (31 August 2024) | Viewed by 3980

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Special Issue Information

Dear Colleagues,

In recent years, the fields of data science and geo-analytics have undergone significant changes, primarily due to the advancements of machine learning, artificial intelligence, natural language processing and the availability of massive pre-trained AI models, such as multimodal foundation models for joint reasoning from vision (audio, images, and videos) and language. Such models, tools, and techniques can help to solve tasks in different domains, and can be leveraged to advance GeoAI in the near future.

Additionally, the rapid development of new hardware, software, and cloud computing technologies have revolutionized the collection and analysis of geographic data to provide state-of-the-art solutions to current issues of grave importance. Examples of such technologies include the integration of global satellite navigation systems (GNSS) into mobile devices, mobile apps for the collection and sharing of volunteered geographic information, geospatial augmented reality, the Internet of Things (IoT), digital twins, immersive technologies, connected vehicles, real-time traffic monitoring, ridesharing systems, and artificial intelligence and deep learning for applications such as disaster monitoring or event prediction.

This Special Issue calls for research contributions presenting novel analysis techniques, applications, sensors, devices, and technologies for the collection of spatial or spatio-temporal data, and effective processing of such data (including big data) through the development or use of new algorithms, software packages, high-performance computing infrastructures or large-scale training models. This Special Issue also welcomes discussion and reviews of previously underexplored open spatial data sets that are of relevance to the geo-science community. We invite contributions from a wide array of academic disciplines including geodesy, geo-information science, computer science, cartography, geography, transportation, environmental science, and health.

Prof. Dr. Hartwig H. Hochmair
Dr. Gerhard Navratil
Prof. Dr. Haosheng Huang
Guest Editors

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Keywords

  • geospatial open source software packages
  • open data
  • innovative data collection methods and devices
  • big data analysis
  • analysis of sensor and network data
  • AI-generated content (AIGC) and foundation models, such as LLMs, for geographic problems
  • geospatial artificial intelligence (GeoAI)
  • geovisual analytics and visual data mining
  • geo-spatial technologies and today’s society

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Related Special Issue

Published Papers (2 papers)

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Research

20 pages, 4283 KiB  
Article
Analyzing the Impact of COVID-19 on Travel and Search Distances for Prominent Landmarks: Insights from Google Trends, X, and Tripadvisor
by Jiping Cao, Hartwig H. Hochmair, Andrei Kirilenko and Innocensia Owuor
Geographies 2024, 4(4), 641-660; https://doi.org/10.3390/geographies4040035 - 17 Oct 2024
Viewed by 839
Abstract
The COVID-19 pandemic profoundly affected people’s travel behavior and travel desires, particularly regarding trips to prominent destinations. This study explores the pandemic’s impact on travel behavior and online search patterns for 12 landmarks across six continents, utilizing data from three online platforms, i.e., [...] Read more.
The COVID-19 pandemic profoundly affected people’s travel behavior and travel desires, particularly regarding trips to prominent destinations. This study explores the pandemic’s impact on travel behavior and online search patterns for 12 landmarks across six continents, utilizing data from three online platforms, i.e., Google Trends, X, and Tripadvisor. By comparing visitation and search behavior before (2019) and during (2020/2021) the pandemic, the study uncovers varying effects on the spatial separation between user location and landmarks. Google Trends data indicated a decline in online searches for nearby landmarks during the pandemic, while data from X showed an increased interest in more distant sites. Conversely, Tripadvisor reviews reflected a decrease in the distance between users’ typical review areas and visited landmarks, underscoring the effects of international travel restrictions on long distance travel. Although the primary focus of this study concerns the years most affected by COVID-19, it will also analyze Tripadvisor data from 2022 to provide valuable insights into the travel recovery beyond the pandemic. Full article
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18 pages, 4317 KiB  
Article
Ranking Opportunities for Autonomous Trucks Using Data Mining and GIS
by Raj Bridgelall, Ryan Jones and Denver Tolliver
Geographies 2023, 3(4), 806-823; https://doi.org/10.3390/geographies3040044 - 17 Dec 2023
Cited by 1 | Viewed by 1886
Abstract
The inefficiency of transporting goods contributes to reduced economic growth and environmental sustainability in a country. Autonomous trucks (ATs) are emerging as a solution, but the imbalance in the weight moved and ton-miles produced by long-haul and short-haul trucking creates a challenge in [...] Read more.
The inefficiency of transporting goods contributes to reduced economic growth and environmental sustainability in a country. Autonomous trucks (ATs) are emerging as a solution, but the imbalance in the weight moved and ton-miles produced by long-haul and short-haul trucking creates a challenge in targeting initial deployments. This study offers a unique solution by presenting a robust method that combines data mining and geographic information systems (GISs) to identify the optimal routes for ATs based on a top-down approach to maximize business benefits. Demonstrated in a U.S. case study, this method revealed that despite accounting for only 16% of the weight moved, long-haul trucking produced 56% of the ton-miles, implying a high potential for ATs in this segment. The method identified eight key freight zones in five U.S. states that accounted for 27% of the long-haul weight and suggested optimal routes for initial AT deployment. Interstate 45 emerged as a pivotal route in the shortest paths among these freight zones. This suggests that stakeholders should seek to prioritize funding for infrastructure upgrades and maintenance along that route and the other routes identified. The findings will potentially benefit a broad range of stakeholders. Companies can strategically focus resources to achieve maximum market share, regulators can streamline policymaking to facilitate AT adoption while ensuring public safety, and transportation agencies can better plan infrastructure upgrades and maintenance. Users globally can apply the methodological framework as a reliable tool for decision-making about where to initially deploy ATs. Full article
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