Mapping the exposure of tourism to weather extremes: the need for a spatially-explicit gridded dataset for disaster risk reduction

Abstract

Tourism is a highly important economic sector worldwide, yet it is often less than optimally represented in terms of detailed spatial information. An accurate spatial representation of tourism can provide valuable insights into the spatial distribution of tourism vulnerabilities and exposure, allowing policymakers to make informed decisions and develop effective strategies for disaster risk reduction and climate change adaptation policies. Here, we stress the need for and propose a first prototype of an open-access spatially-explicit gridded database based on social media data for over 150 different tourism-related classes that depicts tourism density (supply and demand) and perceived satisfaction in Europe. We showcase the potential benefits of such database by mapping the exposure of specific tourism sectors to a range of weather extremes, including floods, windstorms, and heat stress. Based on these results, we argue that a homogeneous spatially-explicit database of tourism is essential to support efficient investments in preparedness and disaster resilience.

Keywords

• weather extremes
• tourism
• spatially-explicit
• climate
• disasters
• big data