A METHOD TO GEOSPATIALLY INVENTORY CRITICAL COASTAL INFRASTRUCTURE: PILOT STUDY FOR THE CARIBBEAN

Abstract:

Planning for a disaster-resilient future requires high-resolution, standardized data on a regional scale. However, few standardized approaches exist for identifying, inventorying, and quantifying regional land and infrastructure at risk from natural hazards. Hurricanes and sea level rise pose a significant threat to infrastructure and critical services (e.g., water telecommunications, energy, and international commerce), and can hinder sustainable development of major economic sectors (e.g., tourism, agriculture, and international commerce). This research presents a standardized and replicable method to geospatially inventory critical coastal infrastructure land use and components. The resulting data can be used for natural hazard vulnerability assessment, as well as other applications, on a regional scale. As a pilot to develop an approach that can be replicated for other regions, this project focuses on the Caribbean. Island economies such as those in the Caribbean rely on their critical coastal infrastructure, such as airports, seaports, power plants, water and wastewater treatment facilities. Due to its geographic location and topography, the Caribbean is one of the most natural-disaster prone regions worldwide. Climate related hazards threaten sustainable development and economic growth in the Caribbean. For example, the Caribbean could face climate-related losses in excess of $22 billion annually by 2050 (IADB). This region, like many others, lacks a comprehensive inventory of the land, infrastructure, and assets at risk. Identifying and prioritizing infrastructure at risk is the first step towards preserving the region’s economy and planning for a disaster resilient future. Using the most up-to-date high resolution satellite imagery, heads-up digitizing is employed to identify and geo-spatially classify critical infrastructure, their land area and assets, such as structures, equipment, and impervious surfaces. The approach used establishes a new standard for the creation of geospatial data that can be used to asses land use change, risk, and other research questions suitable for the regional scale, but with sufficient resolution such that individual facilities can utilize the data for local-scale analysis.