| Summary: | Driven by a combination of ice sheet loss, ocean thermal expansion, and changes in land water storage, sea levels are expected to rise, though local rates of change vary considerably. Historically, small island nations have been understudied despite disproportionate impacts relative to their emissions contributions. This paper presents a case study of Mo’orea, a small South Pacific island in French Polynesia. Using LIDAR data collected in 2015 and IPCC regional sea level rise models, we evaluate how local sea level rise will inundate land, buildings, and displace people. LIDAR data was used to create a Digital Elevation Model (DEM) with a 5 m resolution, giving us the ability to resolve the scale of the built environment. The IPCC 4.5 and 8.5 sea level rise models were applied to the DEM at decadal intervals using an 8 point model. If decadal sea level rise was greater than the elevation of that pixel and the pixel boundary touched the ocean or an adjacent inundated pixel, the pixel was classified as inundated. In order to classify buildings as inundated, each building was sampled through the inundation datasets and buildings were classified as inundated if the center of the structure intersected with the inundation layer. Human displacement was modeled using publicly available census data from 2017. The census data was divided into each of the five watersheds of the island: Afareaitu, Haapiti, Papetoai, Paopao, and Teavaro. The average number of people in each watershed was averaged by the number of pixels in the watershed that were classified as residential buildings. Human displacement was calculated by summing of the pixels classified as both residential and inundated in a given decade. By 2100, our models show that 462 ha of land will be inundated by 2100 under RCP 8.5 and 248 ha under RCP 4.5. While this inundation represents less than 4% of the island, the island is mountainous, with the majority of the island having more than 20 m of elevation. In contrast, 95% of all infrastructure is located in areas ...
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