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机构地区:[1]北京大学城市与环境学院、地表过程分析与模拟教育部重点实验室,北京100871 [2]四川大学工商管理学院,成都610064 [3]九寨沟世界遗产管理局,漳扎623402
出 处:《北京大学学报(自然科学版)》2009年第1期171-177,共7页Acta Scientiarum Naturalium Universitatis Pekinensis
基 金:国家科技支撑计划项目(2006BAD20B07)资助
摘 要:引入4种指数和小波分析工具定量探讨九寨沟旅游流的时间特性。以morlet母小波对1994--2006年逐月和2003--2006年逐日两个旅游流时间序列实施小波变换,揭示了九寨沟旅游流多时间尺度的复杂结构,分析了不同尺度下的周期性。结果表明:在年际尺度上,旅游流呈现出三次函数增长方式,其年内分布为明显的三峰型;在月际尺度上,旅游流季节波动特性逐步变小;近13年来,旅游流存在1年左右的变动周期,尤在近4年表现强烈,此外该时段还在50~70天小尺度上存在周期现象。小波分析的时频局部化特性可以展现旅游流时间序列的精细结构,为分析旅游流时间特性提供了一种新途径。This paper introduces the wavelet tool and 4 indexes to quantify the temporal characteristics of tourist flows. Based on the monthly visitor data from 1994-2006 and daily visitor data from 2003-2006 which were mainly collected through JDS (Jiuzhaigou digital system), the multi-time scales characteristics of tourist flow along the time series were analyzed by using the morlet wavelet transform. The complex structure of multi-time scales are exhibited, also, the periodic oscillation and the main periods of tourist flows at different scales are identified through Wavelet Toolbox in MATALAB 7.3. The results show that 1 ) during 1994-2006, the number of tourists increased rapidly in the way of cubic function and curve of tourists had apparently 3 peaks in July-August, October, and May respectively; 2) at the month scale, the trend of tourist fluctuation decreased overtime; 3) in the past 13 years, there was an approximately 1 year period in the tourist time series. Furthermore, 50-70 days was another period in 2003-2006. After applying wavelet tool to analysis tourist flows, this article argues that the localization characteristics of time-frequency for wavelet analysis can effectively demonstrate the detailed structures of tourist flows. Wavelet is a promising method to analyze temporal characteristics of tourist flows, and the findings can provide a scientific guideline for adjusting and controlling tourist flows.
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