Floris Goerlandt | Searcharxiv

arXiv2025

Community-Centered Spatial Intelligence for Climate Adaptation at Nova Scotia's Eastern Shore

This paper presents an overview of a human-centered initiative aimed at strengthening climate resilience along Nova Scotia's Eastern Shore. This region, a collection of rural villages with deep ties to the sea, faces existential threats from climate change that endanger its way of life. Our project moves beyond a purely technical response, weaving together expertise from Computer Science, Industrial Engineering, and Coastal Geography to co-create tools with the community. By integrating generational knowledge of residents, particularly elders, through the Eastern Shore Citizen Science Coastal Monitoring Network, this project aims to collaborate in building a living digital archive. This effort is hosted under Dalhousie University's Transforming Climate Action (TCA) initiative, specifically through its Transformative Adaptations to Social-Ecological Climate Change Trajectories (TranSECT) and TCA Artificial Intelligence (TCA-AI) projects. This work is driven by a collaboration model in which student teams work directly with residents. We present a detailed project timeline and a replicable model for how technology can support traditional communities, enabling them to navigate climate transformation more effectively.

cs.HC↗

arXiv2025

Modeling Maritime Transportation Behavior Using AIS Trajectories and Markovian Processes in the Gulf of St. Lawrence

Maritime transportation is central to the global economy, and analyzing its large-scale behavioral data is critical for operational planning, environmental stewardship, and governance. This work presents a spatio-temporal analytical framework based on discrete-time Markov chains to model vessel movement patterns in the Gulf of St. Lawrence, with particular emphasis on disruptions induced by the COVID-19 pandemic. We discretize the maritime domain into hexagonal cells and construct mobility signatures for distinct vessel types using cell transition frequencies and dwell times. These features are used to build origin-destination matrices and spatial transition probability models that characterize maritime dynamics across multiple temporal resolutions. Focusing on commercial, fishing, and passenger vessels, we analyze the temporal evolution of mobility behaviors during the pandemic, highlighting significant yet transient disruptions to recurring transport patterns. The methodology we contribute to this paper allows for an extensive behavioral analytics key for transportation planning. Accordingly, our findings reveal vessel-specific mobility signatures that persist across spatially disjoint regions, suggesting behaviors invariant to time. In contrast, we observe temporal deviations among passenger and fishing vessels during the pandemic, reflecting the influence of social isolation measures and operational constraints on non-essential maritime transport in this region.

stat.AP↗