Fast urbanization produces a large and growing population in coastal areas. However, the increasing rise in sea levels, one of the most impacts of global warming, makes coastal communities much more vulnerable to flooding than before. While most existing work focuses on understanding the large-scale impacts of sea-level rise, this paper investigates parcel-level property impacts, using a specific coastal city, Tampa, Florida, USA, as an empirical study. This research adopts a spatial-temporal analysis method to identify locations of flooded properties and their costs over a future period. A corrected sea-level rise model based on satellite altimeter data is first used to predict future global mean sea levels. Based on high-resolution LiDAR digital elevation data and property maps, properties to be flooded are identified to evaluate property damage cost. This empirical analysis provides deep understanding of potential flooding risks for individual properties with detailed spatial information, including residential, commercial, industrial, agriculture, and governmental buildings, at a fine spatial scale under three different levels of global warming. The flooded property maps not only help residents to choose location of their properties, but also enable local governments to prevent potential sea-level rising risks for better urban planning. Both spatial and temporal analyses can be easily applied by researchers or governments to other coastal cities for sea-level rise- and climate change-related urban planning and management.
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