基于自发地理信息的旅游地景观关注度研究——以九寨沟为例

自发地理信息作为旅游地理学研究的全新数据源,具有多时间尺度和多级空间尺度的特点。文章以九寨沟为例,通过采集旅游者上传的VGI照片数据,运用核密度估计方法挖掘多种时空尺度下旅游者关注度空间格局及其演化过程;同时,以互联网用户对照片的访问量为权重,进一步描述潜在旅游者的景观关注度。研究表明,旅游者对九寨沟的关注度格局相对稳定,旅游地尺度下的关注热点是树正沟、日则沟两条风景线,则查洼沟仅有少量景段关注度较高;风景线尺度下,树正沟的盆景滩-犀牛海景段,日则沟的诺日朗群海-镜海、珍珠滩瀑布-五花海、熊猫海瀑布-箭竹海景段,则查洼沟的五彩池-长海景段以及景区入口段等,均是旅游者关注度较高的热区;景点尺度下的树正群海、诺日朗群海、珍珠滩、五花海、熊猫海、箭竹海等水景观关注度日益提高,成为九寨沟的核心吸引物,而以藏族文化为主的人文景观关注度较低。研究同时发现,潜在旅游者受到照片上传者引导,其景观关注度格局也表现出层次性。

A Study of the Spatial Patterns of Tourist Sightseeing based on Volunteered Geographic Information=The Case of the Jiuzhai Valley

Volunteered Geographic Information （VGI） is a new data source for tourism geography research, and has multi-temporal and multi-spatial elements. It is an effective supplement when conducting fieldwork and questionnaire tourism data surveys, particularly in the research fields of tourism destination image and tourist behavior. Photographs containing coordinates, points of interest, travel tags, and travel notes describing various locations that are uploaded by tourists to the Internet are all examples of VGIs. A realization that VGI data contains important information and an analysis of respective tourist behavior allows tourism managers to develop a reasonable ＂ Spatiotemporal Separation＂ policy during peak tourist seasons. Moreover, it helps tourism planners in designing a destination image and those in tourism marketing to communicate and market the tourism product. This paper takes China＇ s Jiuzhai Valley, a premier national park located in the Min Shan mountain range in the Northern Sichuan region of southwestern China, as a case study. We discuss the spatial patterns of sightseeing at multiple temporal-spatial scales within the Jiuzhai Valley, and analyze changes in recent years using all the VGI photographs that tourists had uploaded to Google Earth （ an online virtual geographic information program） within the Jiuzhai Valley area. We processed their attributes, such as tags, location coordinates, author information, and upload time. Using a kernel density estimation model, we calculated the photograph distribution patterns that indirectly indicated the tourists＇ sightseeing patterns. We analyzed the number of views of each photograph by other Internet users and took these results as a weight to calculate a density distribution map. This provides a visual representation of sightseeing distribution patterns for prospective or future tourists. The sightseeing spatial pattern within the Jiuzhai Valley can be analyzed from three spatial scales： the overall destination, the sightseeing routes, and the scenery spots. From an overall destination perspective, we found that the tourist hot spots were mainly located on two sightseeing routes, Shuzheng Valley and Rize Valley. There were few scenic spots that attracted such high levels of attention in other sightseeing routes in the area, including the Zeehawa Valley. From a sightseeing route perspective, areas that attracted high levels of attention were located in the Potted Beach Rhinoceros Lake region within the Shuzheng Valley; the Nuorilang Lakes Mirror Lake, the Pearl Waterfall Five Flower Lake, the Panda Lake Waterfall and the Arrow Bamboo Lake regions within the Rize Valley; the Five Colors Lake Long Lake region within the Zechawa Valley; and the Jiuzhai Valley entrance. From a scenery spot perspective, specific features such as the Shuzheng Lakes, the Nuorilang Lakes, the Pearl Shoal, the Five Flower Lake, the Panda Lake and the Arrow Bamboo Lake attract high levels of attention and are core Jiuzhai Valley attractions. The Semo and Yuzhigonggai mountains are beautiful ecotourism landscapes; however, they received less attention because of their high elevations. Areas famous for Tibetan culture, such as the Lotus Valley, Jianpan Village and Panya Village also attracted lower levels of attention. The weighted analysis of photograph views by Internet users showed that prospective tourists are guided by the photographs uploaded by previous tourists. The prospective tourist spatial pattern analysis showed hierarchical characteristics.