Utilizing Urban Geospatial Data to Understand Heritage Attractiveness in Amsterdam

Touristic cities are home to historical landmarks and irreplaceable urban heritages. Although tourism brings financial advantages, mass creates pressure on cities. Therefore, “attractiveness” is one of the key elements explain dynamics. User-contributed geospatial data provide an evidence-based understanding people’s responses these places. In this article, combination multisource information about national monuments, supporting products (i.e., attractions, museums), utilized understand attractive heritage locations factors that make them attractive. We retrieved geotagged photographs from Flickr API, then employed density-based spatial clustering applications with noise (DBSCAN) algorithm find clusters. Then combined clusters Amsterdam processed ordinary least square (OLS) geographically weighted regression (GWR) identify attractiveness relevance in Amsterdam. The results show heritages according their types surrounding built environment provides insights increase unattractive heritages’ attractiveness. That may help diminish burden overly visited locations. less strong influential could pave way for more sustainable