Factors of spatial distribution of recreation areas in peri-urban Beijing |
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| Authors: | LIU Jiaming WANG Run CHEN Tian |
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| Institution: | 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
2. Graduate University of Chinese Academy of Sciences, Beijing 100049, China |
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| Abstract: | Based on the case study of peripheral urban areas in Beijing, this paper aims to identify the factors which will influence the spatial distribution of peri-urban recreation areas, by analyzing the collected data from questionnaires, online survey, documentation and field investigations (2007). In order to achieve sound information, relevant data from different management departments, owners and land-use types involved in the case study area are collected. A sampling database for peri-urban recreation areas in Beijing is established, and GIS spatial analyses as well as statistic analyses are applied. The result indicates that spatial distribution of recreation areas is majorly influenced by four factors, e.g. tourism attractions and environmental conditions, policy and spatial governance, consumption demand and preference, land price and availability. Tourism attractions and environmental conditions are dominant factors for public recreation areas. Commercial recreation areas are highly related with accessibility. Agricultural recreation areas are usually attached to special farmlands near large-scaled scenic areas. Meanwhile, recreational business clusters have appeared in suburbs influenced by mass recreation market growth. Controlled by the land price, commercial recreation areas are differentiated on their scales and developing intensity. Policy and spatial governance have made arrangements of recreation areas more balancing and more human- oriented. A peri-urban recreation area model is therefore established on the basis of this analysis, which can guide urban planning and designing, land-use planning and recreation resource development. |
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| Keywords: | Beijing peri-urban recreation areas spatial distribution influencing factor |
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