| Tourism spatial evolution has characterized in spatial turn and scale restructuring during the past thirty years:Toursim activities’ organization method has been in the transition from extensive point to ine based mode to intensive region-based mode. Moreover, confined to limited tourism resources, exhausted policy dividend, fragile ecology capacity, conventional rban tourism which is relying on single-uclei metropolis is urgent to divert tourists to lower-tier cities or county, towns for the purpose of deeper and broader tourism territorial system.As a higher stage of urbanization evolution, urban agglomeration has been highly supported with a wide variety of regional economic policies. With several national strategies such as Silk Road Economic Belt, Maritime Silk Route, Beijing-Tianjin-Hebei Integration, Yangtze River Economic Zone and National New-type Urbanization Planning(from 2014 to 2020) have been formulated and implemented successively, regional integration and joint development underpinned by urban agglomerations will be an constant concern in the thirteenth five-year plan. Urbanization process in China has been transforming from single city’s urbanization to city groups’ urbanization.Tourism has been working as leading industry of morden service industry and pillar industry of national economy, which combines attributes of both producers services and consumer services. Therefore, tourism industry is more incline to serve as pioneer field in the process of regional economic synergetic development due to its urgent demand for spatial liquidity and powerful function for resource integration. With support of integrated transport network’s advancement, it has been an inevitable trend for sustainable tourism via transformation from urban tourism with single center to megapolis tourism with core-periphery structure, then progresses to urban agglomeration tourism with network structure by cultivating secondary tourism centre cities.This paper gets tourism spatial filed concept system and functional mechanism on the basis of theories originated from Regional Economics, Economic Geography, Physics. Then it conducts an empirical study on thirteen city groups’ tourism field potential energy measurement through quantitative analysis with Arcgis 10.0 and SPSS 19.0. And in addition, this paper elaborates tourism potential energy’s spatial configuration, dispersal pattern and rules of territorial differentiation, proposes solutions for enhancing tourism field energy level for the purpose of healthy tourism development among city clusters. Four main parts are included in this paper:(1) Tourism resources—industry—market analysis in urban agglomerations. First, explore invisible factors resulting in city group’s formation by placeality analysis, and evaluate tourism attractions spatial concentration level by using Gini Index and Primacy Ratio. Second, measure industrial concentration and city network connectivity by using Herfindahl-Hirschman Index and Peter Taylor Model respecitively. Third, evaluate tourism market share, growth rate and level of market maturity by using Theil Index. And those indices play an essential and inevitable role in analyzing city clusters’ tourism function, attributes and characteristics.(2) Measure and evaluate tourism nodality and time accessibility. First, tourism nodality measurement. Select twenty one indicators from four areas, namely, tourim economy, social economy, traffic infrastructure, cultural and education to construct tourism nodality evaluation system, and then apply nondimensionalization as well as principal component analysis to evaluate degree of tourism cohesiveness and balanced development. Second, time accessibility measurement. Divide time accessibility circle within six hours by every half an hour via adopting GIS spatial analysis on the basis of road traffic and waterway traffic network, and put an emphasis on one to three hours’ coverage to test and verify urban agglomerations’ spatial and temporal convergence.(3)Tourism field potential energy measurement and evaluation. First, measure tourism field potential energy by using raster calculator, extract by mask and zonal statistics modules in Arcgis 10.0, then differentiate tourism field potential energy’s dispersal patterns into five types and grades. Second, divide county tourism field potential energy level into five major types, namely, higher, high, average, low, lower by natural breaks method, and anylyze their rule and mechanism of spatial differentiation. Third, measure degree of coupling and coordinate between tourism nodality and time accessibility, thus to distinguish the major factor that affects tourism field potential energy level.(4) Strategies to enhance tourism filed potential energy. First, boost inter-city traffic to promote tourism market integration, especially lay emphasis on functions and repercussions of intercity rail, suburban rail, intercity bus. Second, foster nested tourism field potential energy growth system with counties, towns and villages to establish and cultivate new growth points which are deep and broad to hinterlands through networking penetration. Third, set up closely linked tourism clusters and higher tourim field potential energy connecting area by supporting secondary tourism cities and city-town concentrated areas’ development. Fourth, integration based on industrial division. Smash Administrative Regional Economy by preempting traffic integration for the sake of deeper and full scale industrial division and cooperation system.
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