Generating an interactive online map of future sea level rise along the North Shore of Vancouver: methods and insights on enabling geovisualisation for coastal communities

• URL: http://arxiv.org/abs/2304.07469v1
• Date: Sat, 15 Apr 2023 04:12:55 GMT
• Title: Generating an interactive online map of future sea level rise along the North Shore of Vancouver: methods and insights on enabling geovisualisation for coastal communities
• Authors: Forrest DiPaola, Anshuman Bhardwaj and Lydia Sam
• Abstract summary: The study area was the North Shore of Vancouver, British Columbia, Canada. We explored an open access airborne 1 metre LiDAR which has a higher resolution and vertical accuracy. A bathtub method model with hydrologic connectivity was used to delineate the inundation zones for various SLR scenarios. Deep Learning and 3D visualizations were used to create past, present, and modelled future Land Use/Land Cover and 3Ds.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Contemporary sea level rise (SLR) research seldom considers enabling effective geovisualisation for the communities. This lack of knowledge transfer impedes raising awareness on climate change and its impacts. The goal of this study is to produce an online SLR map accessible to the public that allows them to interact with evolving high-resolution geospatial data and techniques. The study area was the North Shore of Vancouver, British Columbia, Canada. While typically coarser resolution (10m+/pixel) Digital Elevation Models have been used by previous studies, we explored an open access airborne 1 metre LiDAR which has a higher resolution and vertical accuracy and can penetrate tree cover at a higher degree than most satellite imagery. A bathtub method model with hydrologic connectivity was used to delineate the inundation zones for various SLR scenarios which allows for a not overly complex model and process using standard tools such as ArcGIS and QGIS with similar levels of accuracy as more complex models, especially with the high-resolution data. Deep Learning and 3D visualizations were used to create past, present, and modelled future Land Use/Land Cover and 3D flyovers. Analysis of the possible impacts of 1m, 2m, 3m, and 4m SLR over the unique coastline, terrain and land use was detailed. The generated interactive online map helps local communities visualise and understand the future of their coastlines. We have provided a detailed methodology and the methods and results are easily reproducible for other regions. Such initiatives can help popularise community-focused geovisualisation to raise awareness about SLR.

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