This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1088/2515-7620/ad15ab. This is version 2 of this Preprint.
You must log in to post a comment.
Natural hazards pose significant risks to human lives, infrastructure, and ecosystems, necessitating a comprehensive understanding of climate risks for effective adaptation planning and risk management. However, climate risk assessments mostly focus on economic asset values and infrastructures such as roads and buildings, because publicly available data on more diverse exposures are scarce. The increasing availability of crowd-sourced geospatial data, notably from OpenStreetMap, opens up a novel means for assessing climate risk to a large range of physical assets. To this end, we present a stand-alone, lightweight, and highly flexible Python-based OpenStreetMap data extraction tool: OSM-flex. We demonstrate the potential and limitations of OpenStreetMap data for risk assessments by coupling OSM-flex to the open-source natural hazard risk assessment platform CLIMADA, and computing the current climate's winter storm risk and event impacts from the severe winter storm Lothar across Switzerland. Specifically, we evaluate the risks and impacts on forests, UNESCO heritage sites, railways, healthcare facilities, and airports, and compare them with traditional impact metrics such as asset damages and affected population. This study aims to provide researchers, practitioners, and decision-makers with insights into utilizing open-source data and software tools for conducting multi-faceted and high-resolution climate risk assessments.
Environmental Sciences, Geographic Information Sciences, Risk Analysis
OpenStreetMap, GIS, risk assessment, natural hazards, Open-source Tools
Published: 2023-06-29 07:43
Last Updated: 2023-09-04 14:53
Data Availability (Reason not available):