Summary
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.
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| Web resources: | https://cordis.europa.eu/project/id/101106544 |
| Start date: | 01-06-2023 |
| End date: | 31-05-2025 |
| Total budget - Public funding: | - 188 590,00 Euro |
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Original description
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.Status
SIGNEDCall topic
HORIZON-MSCA-2022-PF-01-01Update Date
31-07-2023
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