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

• URL: http://arxiv.org/abs/2509.01845v2
• Date: Wed, 08 Oct 2025 14:10:18 GMT
• Title: Community-Centered Spatial Intelligence for Climate Adaptation at Nova Scotia's Eastern Shore
• Authors: Gabriel Spadon, Oladapo Oyebode, Camilo M. Botero, Tushar Sharma, Floris Goerlandt, Ronald Pelot,
• Abstract summary: This paper presents an overview of a human-centered initiative aimed at strengthening climate resilience along Nova Scotia's Eastern Shore.<n>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.<n>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.
• Score: 2.1250493293583514
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

Related papers

• A Roadmap for Climate-Relevant Robotics Research [46.61789624823832]
  This paper presents a roadmap for climate-relevant robotics research.<n>It identifies high-impact opportunities for collaboration between roboticists and experts across climate domains.<n>These applications include problems such as energy systems optimization, construction, precision agriculture, building envelope retrofits, autonomous trucking, and large-scale environmental monitoring.
  arXiv  Detail & Related papers  (2025-07-15T18:01:49Z)
• Earth Virtualization Engines -- A Technical Perspective [11.370541118978181]
  EVEs aim to provide interactive and accessible climate simulations and data for a wide range of users. They combine high-resolution physics-based models with machine learning techniques to improve the fidelity, efficiency, and interpretability of climate projections.
  arXiv  Detail & Related papers  (2023-09-16T14:14:39Z)
• Multi-scale Digital Twin: Developing a fast and physics-informed surrogate model for groundwater contamination with uncertain climate models [53.44486283038738]
  Climate change exacerbates the long-term soil management problem of groundwater contamination. We develop a physics-informed machine learning surrogate model using U-Net enhanced Fourier Neural Contaminated (PDENO) In parallel, we develop a convolutional autoencoder combined with climate data to reduce the dimensionality of climatic region similarities across the United States.
  arXiv  Detail & Related papers  (2022-11-20T06:46:35Z)
• AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-N [75.67460895629348]
  Achieving long-term cooperation on climate change mitigation with n strategic agents poses a complex game-theoretic problem. We introduce RICE-N, a multi-region integrated assessment model that simulates the global climate and economy. We describe how to use multi-agent reinforcement learning to train rational agents using RICE-N.
  arXiv  Detail & Related papers  (2022-08-15T04:38:06Z)
• Collaborating with communities: Citizen Science Flood Monitoring in Urban Informal Settlements [0.0]
  Article uses the Revitalising Informal Settlements and their Environment (RISE) Program as a case study. This project collected more than 5000 photos taken by 26 community members living in 13 informal settlements in Fiji and Indonesia between 2018 and 2020. The case study indicates that the engagement model and the technology used were key to the success of the flood-monitoring project.
  arXiv  Detail & Related papers  (2021-12-14T02:59:36Z)
• ClimateGAN: Raising Climate Change Awareness by Generating Images of Floods [89.61670857155173]
  We present our solution to simulate photo-realistic floods on authentic images. We propose ClimateGAN, a model that leverages both simulated and real data for unsupervised domain adaptation and conditional image generation.
  arXiv  Detail & Related papers  (2021-10-06T15:54:57Z)
• Empowering Local Communities Using Artificial Intelligence [70.17085406202368]
  It has become an important topic to explore the impact of AI on society from a people-centered perspective. Previous works in citizen science have identified methods of using AI to engage the public in research. This article discusses the challenges of applying AI in Community Citizen Science.
  arXiv  Detail & Related papers  (2021-10-05T12:51:11Z)
• Powering Effective Climate Communication with a Climate Knowledge Base [1.951890354110457]
  We aim to build a system that presents to any individual the climate information predicted to best motivate and inspire them to take action given their unique set of personal values. The system relies on a knowledge base (ClimateKB) of causes and effects of climate change, and their associations to personal values. We plan to open source the ClimateKB and associated code to encourage future research and applications.
  arXiv  Detail & Related papers  (2021-07-23T17:02:06Z)
• Quantum technologies for climate change: Preliminary assessment [0.0]
  Climate change presents an existential threat to human societies and the Earth's ecosystems. Quantum technologies in computing, sensing, and communication could become useful tools to diagnose and help mitigate the effects of climate change. This report aims to identify potential high-impact use-cases of quantum technologies for climate change with a focus on four main areas.
  arXiv  Detail & Related papers  (2021-06-23T18:02:19Z)
• CLIMATE-FEVER: A Dataset for Verification of Real-World Climate Claims [4.574830585715129]
  We introduce CLIMATE-FEVER, a new dataset for verification of climate change-related claims. We adapt the methodology of FEVER [1], the largest dataset of artificially designed claims, to real-life claims collected from the Internet. We discuss the surprising, subtle complexity of modeling real-world climate-related claims within the textscfever framework.
  arXiv  Detail & Related papers  (2020-12-01T16:32:54Z)
• Physics-informed GANs for Coastal Flood Visualization [65.54626149826066]
  We create a deep learning pipeline that generates visual satellite images of current and future coastal flooding. By evaluating the imagery relative to physics-based flood maps, we find that our proposed framework outperforms baseline models in both physical-consistency and photorealism. While this work focused on the visualization of coastal floods, we envision the creation of a global visualization of how climate change will shape our earth.
  arXiv  Detail & Related papers  (2020-10-16T02:15:34Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.