A Study On The Concern Of Tourism Destination In Shanghai Based On Public Geographic Data

In recent years, crowdsourcing geography data is a new concept in the field of geo-information science. It consists of crowdsourcing combined with traditional geographic data, which collected by a large number of non-professional volunteers and supplied to the public via the Internet. Since it has a larger volume, information-rich, low-cost, and up-to-date, compared with customary geographic data it has a lot of advantages, which contain a great potential for development and application of value.During the travel, more and more tourists want to take photos, check in and send weibos at the travel destination, which produces a distinctive crowdsourcing geography data, poi check-in data. It can be considered as a range of the larger, more subtle means of recording, becoming to spy upon tourist behavior, and representing a tourist destination awareness effectively and intuitively. Tourist destination awareness is the tourist destination watched index of the tourist. Based on crowdsourcing geography data, tourist destination awareness can reflect the destinations of tourists in densely populated, estimate tourist information,and provide early warning of destination services.Based on these crowdsourcing geography data like poi check-in data, the nonporous theory and practical application, this paper analysis and research on tourist destination awareness, which focuses on the following three aspects:1. By discussing public source of geographic data analysis concepts and characteristics of attention and tourist destination, this paper chooses Mongo DB which applies to the crowdsourcing geography data as the data storage media, uses the optimal collecting and storing method. Through the Place APIs of weibo, this paper collected 1364 tourist destinations and about 800,000 poi check-in data in shanghai.2. By the timing, source and space aspects, this paper found tourist destination awareness peaked most appears around April of each year, in May and October, and highly relevant to China’s national holiday; most tourists are fromlocal and domestic, and has close links with mobile Internet development. Based on the hot cluster methods and exploratory spatial data analysis, it is extreme concentration form, which mainly concentrated in urban areas, and has a sporadic distribution in the suburban area, especially at the people’s Square area and the Bund and the Lujiazui zoneon both sides of the Huangpu River peak. At last this paper collected 22 attentions hotspots of the tourist destination.3. In this paper based on crowdsourcing geography data, an online visualization system for shanghai tourist destination awareness has been designed, developed and implemented. By this system, Users can access current and historical tourist destination awareness, analyze tourist destination popularity trends, monitor tourist destination awareness, and destinations-warning. Comparative analysis of actual data and “12?31” Crowded Stampede Event on the Bund, touristdestination awareness can speculate the stream intensity and provide warning services for tourist destinations.