Descripción del proyecto
Una solución para los hoteles costeros italianos en peligro
A pesar de que las playas italianas son el sustento de su sector hotelero, no se presta atención al riesgo que representa el cambio climático. Curiosamente, apenas se han evaluado las repercusiones económicas y medioambientales de la subida del nivel del mar en la industria hotelera. Con el apoyo de las Acciones Marie Skłodowska-Curie, el proyecto SEA-LIMITHS utilizará la inteligencia artificial y el aprendizaje automático para investigar las consecuencias económicas de la subida del nivel del mar en las playas arenosas de Véneto y Emilia-Romaña. Mediante el cotejo de datos generados por los usuarios con mapas de ocupación y uso del suelo, el equipo de SEA-LIMITHS evaluará las pérdidas económicas en el sector de la hostelería de 2050 a 2100 en diferentes escenarios climáticos y sin medidas de adaptación. Estas predicciones se contrastarán con el coste de adoptar soluciones de adaptación alternativas.
Objetivo
There has been no evaluation of the economic and environmental impacts of coastal sea-level rise on the hotel industry utilising Artificial Intelligence (A.I.) to analyse the whole transmission channel. The SEA-LIMITHS project will contribute to the expanding but still limited body of information on climate change and tourism losses. Despite the importance of sand beaches to the hotel sector in the vast majority of Italian beaches, tragically few policymakers incorporate quantifiable risk assessments of sand beach loss due to climate change. This study investigates the impacts and economic consequences of sea level rise on sandy beaches and beach hospitality losses owing to beach erosion and flooding in two economically important Italian coastal areas, Veneto and Emilia-Romagna. Combining sandy beaches with a proposed rich dataset based on machine learning and artificial intelligence, user-generated data is matched to the land cover/land use map to separate the hospitality sectors (accommodation, food and drink, sports and leisure) in order to assess economic losses in the hospitality industry from 2050 to 2100 using representative concentration pathways (RCP 4.5 and RCP 8.5). Taking into consideration no adaptation measures, the predicted cumulative damage costs per hospitality industry are analysed and contrasted to the investment cost of adopting alternative adaption solutions. Using an Italy-specific computable general equilibrium model, the estimated direct costs will be used in a macroeconomic assessment as input to determine how changes in hospitality activities effect regional value added. The fact that this proposal pertains to several disciplines of study is what gives it its creative interdisciplinarity. The combination of economic and environmental research, together with the developing and increasing methods of machine learning, will produce an outstanding piece of work and significantly advance the author's scientific career.
Ámbito científico
- natural sciencesearth and related environmental sciencesphysical geographycoastal geography
- natural sciencesearth and related environmental sciencessoil sciencesland-based treatment
- natural sciencesearth and related environmental sciencesatmospheric sciencesclimatologyclimatic changes
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Palabras clave
Programa(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Régimen de financiación
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European FellowshipsCoordinador
30123 Venezia
Italia