基于地理标记照片的入境游客空间特征与移动轨迹——以南京市为例

随着互联网与社交媒体的兴起,用户分享内容中的地理标记数据成为旅游流研究的重要对象。以南京入境旅游流空间特征为研究对象,以2010—2018年Flickr平台内南京地理标记照片为基础,利用DBSCAN算法、ArcGIS 10.2等方法与技术探究南京入境旅游热点区域、游客移动轨迹特征及模式。研究结果显示：（1）南京入境游客访问峰值出现在3-6月及10月,以一日游为主。（2）南京AOI空间分布差异明显,历史城区是南京入境旅游最热门区域,其AOI分布与旅游景区、商业购物等相关产业空间高度重合;中心城区的AOI分布数量次之,钟山风景区是其热度核心,深受热衷历史文化的游客追捧;郊区的AOI分布数量最少,基本与当地旅游景区相吻合。（3）单日游和多日游的游客移动轨迹网具有显著差异性,分别体现在网络范围、网络体系、旅游对流及转移差值4个方面。（4）南京入境游客移动轨迹模式可划分为区域内部移动轨迹模式和区域间移动轨迹模式。根据上述研究结果,分别针对历史城区、中心城区及郊区提出相应的发展建议。

Spatial patterns and moving trajectory of inbound tourists based on geo-tagged photos:A case study of Nanjing city

With the rise of the Internet and social media, geo-tagged data in the sharing of users has become an important content of tourism flow research. Based on the photos of on the Flickr platform during 2010-2018, this study takes the spatial characteristics of Nanjing inbound tourism flow as the research object, and uses the methods of DBSCAN algorithm, ArcGIS 10.2 and others to explore inbound tourism hotspots area, the features of moving trajectory and patterns of Nanjing. The results of the study show that:(1) The peak of inbound visits occurred in March-June and October, and the tourists mainly took one-day trips.(2) There are obvious differences in the spatial distribution of Area of Interest(AOI) in Nanjing. The historical urban district(HUD) is most popular for inbound tourists, and has the largest number of AOI,followed by the central urban area(CUA), and the suburbs. The distribution of AOI in the HUD is highly coincident with its related industrial space, such as tourist attractions and commercial shopping centers;Zhongshan Scenic Area in the CUA is a hotspot for tourists who are interested in history and culture;the distribution of AOI in the suburbs is basically consistent with that of local tourist attractions.(3) There are great differences in moving trajectories between single-day and multi-day trips, which are reflected in the network scope,network system, tourism inflow and outflow, and transfer difference.(4) The patterns of inbound moving trajectory can be divided into intra-area pattern and inter-area pattern. Based on the above results, suggestions are proposed for development of historical urban area, central urban area and the suburbs.