Abstract

Spatial characteristics of leisure tourism resources is essential for human life, the urban economy, and tourism planning. This paper presents a novel framework to explore these characteristics based on multi-source data, such as points of interest (POIs), OpenStreetMap roads, Sentinel-2 Multispectral Instrument (MSI) images, and other data, and proposes a new tourism area identification method by integrating attractiveness of attractions with term frequency–inverse document frequency. The roles of the influencing factors were measured by using the geodetector and related statistical analyses. The results showed that the resources were centered on Jiaozhou Bay, and their axial direction was “northeast to southwest.” The distribution of the overall resources was characterized by “one cluster with multiple core points,” and different types of resources had different aggregation distributions. The Recreational Recreation (RR) and Cultural Leisure (CL) zones were more likely to be distributed in and near the center of each district, and their numbers were high, while the Shopping Leisure (SL) and Natural Recreation (NR) zones were the opposite. The distribution of each type of resource was the result of a combination of factors working together, except for NR resources, which were mainly influenced by natural factors, while others were mainly affected by socioeconomic factors. The study findings are instructive for tourism planning.

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