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Parallel Topology-aware Mesh Simplification on Terrain Trees
We address the problem of performing a topology-aware simplification algorithm on a compact and distributed data structure for triangle meshes, the Terrain trees. Topology-aware operators have been defined to coarsen a Triangulated Irregular Network (TIN) ...
Regionalization-Based Collaborative Filtering: Harnessing Geographical Information in Recommenders
Regionalization, also known as spatially constrained clustering, is an unsupervised machine learning technique used to identify and define spatially contiguous regions. In this work, we introduce a methodology to regionalize recommendation systems (RSs) ...
Mobility Data Science: Perspectives and Challenges
- Mohamed Mokbel,
- Mahmoud Sakr,
- Li Xiong,
- Andreas Züfle,
- Jussara Almeida,
- Taylor Anderson,
- Walid Aref,
- Gennady Andrienko,
- Natalia Andrienko,
- Yang Cao,
- Sanjay Chawla,
- Reynold Cheng,
- Panos Chrysanthis,
- Xiqi Fei,
- Gabriel Ghinita,
- Anita Graser,
- Dimitrios Gunopulos,
- Christian S. Jensen,
- Joon-Seok Kim,
- Kyoung-Sook Kim,
- Peer Kröger,
- John Krumm,
- Johannes Lauer,
- Amr Magdy,
- Mario Nascimento,
- Siva Ravada,
- Matthias Renz,
- Dimitris Sacharidis,
- Flora Salim,
- Mohamed Sarwat,
- Maxime Schoemans,
- Cyrus Shahabi,
- Bettina Speckmann,
- Egemen Tanin,
- Xu Teng,
- Yannis Theodoridis,
- Kristian Torp,
- Goce Trajcevski,
- Marc van Kreveld,
- Carola Wenk,
- Martin Werner,
- Raymond Wong,
- Song Wu,
- Jianqiu Xu,
- Moustafa Youssef,
- Demetris Zeinalipour,
- Mengxuan Zhang,
- Esteban Zimányi
Mobility data captures the locations of moving objects such as humans, animals, and cars. With the availability of Global Positioning System (GPS)–equipped mobile devices and other inexpensive location-tracking technologies, mobility data is collected ...
On the Opportunities and Challenges of Foundation Models for GeoAI (Vision Paper)
- Gengchen Mai,
- Weiming Huang,
- Jin Sun,
- Suhang Song,
- Deepak Mishra,
- Ninghao Liu,
- Song Gao,
- Tianming Liu,
- Gao Cong,
- Yingjie Hu,
- Chris Cundy,
- Ziyuan Li,
- Rui Zhu,
- Ni Lao
Large pre-trained models, also known as foundation models (FMs), are trained in a task-agnostic manner on large-scale data and can be adapted to a wide range of downstream tasks by fine-tuning, few-shot, or even zero-shot learning. Despite their successes ...
Predictability in Human Mobility: From Individual to Collective (Vision Paper)
Human mobility is the foundation of urban dynamics and its prediction significantly benefits various downstream location-based services. Nowadays, while deep learning approaches are dominating the mobility prediction field where various model ...
In Silico Human Mobility Data Science: Leveraging Massive Simulated Mobility Data (Vision Paper)
- Andreas Züfle,
- Dieter Pfoser,
- Carola Wenk,
- Andrew Crooks,
- Hamdi Kavak,
- Taylor Anderson,
- Joon-Seok Kim,
- Nathan Holt,
- Andrew Diantonio
Human mobility data science using trajectories or check-ins of individuals has many applications. Recently, we have seen a plethora of research efforts that tackle these applications. However, research progress in this field is limited by a lack of large ...
(Vision Paper) A Vision for Spatio-Causal Situation Awareness, Forecasting, and Planning
- Fahim Tasneema Azad,
- K. Selçuk Candan,
- Ahmet Kapkiç,
- Mao-Lin Li,
- Huan Liu,
- Pratanu Mandal,
- Paras Sheth,
- Bilgehan Arslan,
- Gerardo Chowell-Puente,
- John Sabo,
- Rebecca Muenich,
- Javier Redondo Anton,
- Maria Luisa Sapino
Successfully tackling many urgent challenges in socio-economically critical domains, such as public health and sustainability, requires a deeper understanding of causal relationships and interactions among a diverse spectrum of spatio-temporally ...
Let's Speak Trajectories: A Vision to Use NLP Models for Trajectory Analysis Tasks
The availability of trajectory data combined with various real-life practical applications has sparked the interest of the research community to design a plethora of algorithms for various trajectory analysis techniques. However, there is an apparent lack ...
The Challenge of Data Analytics with Climate-neutral Urban Mobility (Vision Paper)
Urban mobility is a major contributor to human-induced climate change, a challenge that urban and transport planning and spatial computing academic communities have been actively addressing. In this article we argue, however, that the common data ...
Leveraging Simulation Data to Understand Bias in Predictive Models of Infectious Disease Spread
- Andreas Züfle,
- Flora Salim,
- Taylor Anderson,
- Matthew Scotch,
- Li Xiong,
- Kacper Sokol,
- Hao Xue,
- Ruochen Kong,
- David Heslop,
- Hye-Young Paik,
- C. Raina MacIntyre
The spread of infectious diseases is a highly complex spatiotemporal process, difficult to understand, predict, and effectively respond to. Machine learning and artificial intelligence (AI) have achieved impressive results in other learning and prediction ...
