基于大数据的城市森林公园旅游流特征研究——以紫金山国家森林公园为例

Research on characteristics of tourism flow in urban forest parks based on big data——A case study in Purple Mountain National Forest Park

假期短期出行造成森林公园拥堵现象严重,为促进城市森林公园可持续发展,对城市森林旅游流的时空变化规律特征及其影响因素进行定量研究。基于携程旅行监测平台数据,以紫金山国家森林公园为例,应用时间分层法、季节性强度指数法、核密度分析法及卷积神经网络(CNN),研究旅游流时空分布特征及其影响因素。结果表明:(1)受假期制度、气候舒适度、动植物特色和地方文化的综合影响,紫金山国家森林公园旅游流日内分布呈现“多峰型”的特征,表现为“周期性效应”“假日效应”及“刹车效应”;季节性强度指数偏大,淡、旺季明显且呈周期性波动;(2)出游热潮下的森林公园旅游流呈“多核心化”的时空分布特征,游客主要聚集在紫金山南面的3个景区,与北面具有明显的分化;(3)旅游者出行意愿受旅游目的地的季节性因子影响最大,游客偏好文化特色丰富、景色优美、季相变化丰富、基础设施优越、空间范围广阔、空气清新、体验感强的地段。

Short-term travel during holidays caused serious congestion in forest parks.In order to promote the sustainable development of urban forest parks,quantitative research was conducted on the characteristics of spatial and temporal change patterns of urban forest tourism flows and their influencing factors.Based on Ctrip's travel monitoring platform data,applied the time stratification method,seasonal intensity index method,nuclear density analysis method,and the convolutional neural network(CNN) to study the spatiol-temporal distribution characteristics of tourism flow in Purple Mountain National Forest Park in Nanjing City,China.The results showed that:(1) Due to the comprehensive influence of holiday system,climate condition,animal and plant richness and local culture,the intra-day distribution of tourist in Purple Mountain National Forest Park was generally characterized by a curve of "multi-peaks",which was characterized by "cyclical effect" "holiday effect" and "brake effect".Seasonal intensity index was large,and the peak and valley seasons were obvious and showed periodic fluctuations.(2) Under the travel boom,the tourism flows in the park showed a spatial pattern of multi-core aggregation.The number of tourist gathering around three scenic spots in the southern part of the park far exceeded that in the northern part.(3) The willingness of tourists to travel and the spatial distribution were significantly affected by the seasonal factors of tourist destinations.Most tourists were willing to gather in areas with rich cultural heritages,beautiful scenery,rich seasonal changes,superior infrastructure,fresh air and broad space.