A coastal hospitality sector database for vulnerability assessments in Veneto and Emilia-Romagna, ItalyZenodo
This article presents a comprehensive geospatial database documenting the coastal hospitality sector across Veneto and Emilia-Romagna regions in Northern Italy. The dataset integrates information on 5030 accommodation establishments and 4992 service facilities, providing detailed spatial and attribu...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-10-01
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| Series: | Data in Brief |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340925006456 |
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| Summary: | This article presents a comprehensive geospatial database documenting the coastal hospitality sector across Veneto and Emilia-Romagna regions in Northern Italy. The dataset integrates information on 5030 accommodation establishments and 4992 service facilities, providing detailed spatial and attribute data essential for vulnerability assessments in the context of climate change and sea-level rise projections. Data collection employed a multi-source approach combining web scraping, API queries from Google Places, and crowdsourced repositories (Eubucco, Overture Maps), with meticulous validation protocols ensuring robust data quality. Each record includes precise geolocation, structural characteristics, proximity to coastal features, elevation metrics derived from the TINITALY digital terrain model, sea-level rise projections based on IPCC-AR5 ensemble models, sustainability certifications, and amenity information. The dataset facilitates spatial analysis of hospitality infrastructure vulnerability to coastal hazards, including sea-level rise, erosion, and storm surges. This comprehensive coverage of Northern Adriatic coastal tourism infrastructure offers significant potential for multi-disciplinary applications, including climate adaptation planning, tourism management, and disaster risk reduction for one of Europe's most economically significant coastal tourism regions. |
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| ISSN: | 2352-3409 |