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

中文翻译：

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利用城市地理空间数据了解阿姆斯特丹的遗产吸引力

旅游城市是历史地标和不可替代的城市遗产的所在地。尽管旅游业带来了财务优势，但大众旅游业对历史名城造成了压力。因此，“吸引力”是解释旅游动态的关键要素之一。用户提供的地理空间数据可以对人们对这些地方的反应提供基于证据的理解。在本文中，有关国家历史遗迹，辅助产品（即景点，博物馆）和地理空间数据的多源信息的组合被用于了解有吸引力的遗产位置以及使它们具有吸引力的因素。我们从Flickr API中检索了带有地理标签的照片，然后采用基于密度的应用程序空间聚类与噪声（DBSCAN）算法来查找聚类。然后，将聚类与阿姆斯特丹遗产数据进行组合，并使用普通最小二乘（OLS）和地理加权回归（GWR）处理组合后的数据，以确定遗产吸引力和阿姆斯特丹支持产品的相关性。结果表明，根据遗产的类型和周围建筑环境中的配套产品来了解遗产的吸引力，可以提供洞察力，以增加吸引力较低的遗产的吸引力。这可能有助于减轻过度游览地区的旅游负担。吸引力不强的遗产与有影响力的辅助产品的结合可以为阿姆斯特丹更可持续的旅游业铺平道路。