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  1. NTU Theses and Dissertations Repository
  2. 理學院
  3. 地理環境資源學系
Please use this identifier to cite or link to this item: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/65708
Title: 使用GPS軌跡資料推估遊客空間分布—以野柳地質公園為例
Using GPS Logging Data to Estimate Spatial Distribution of Visitors: A Case Study of Yehliu Geopark
Authors: Ying-Hao Hu
胡英浩
Advisor: 朱子豪
Keyword: 軌跡記錄器,核密度推估,空間分布,遊客密度,野柳地質公園,
GPS data logger,kernel density estimation (KDE),spatial distribution,visitor’s density,Yehliu Geopark,
Publication Year : 2012
Degree: 碩士
Abstract: 本研究建立一套分析全球衛星定位系統 (GPS) 軌跡資料的方法,透過GPS軌跡記錄器收集野柳地質公園遊客參觀軌跡後,利用核密度推估法 (kernel density estimation, KDE) 計算可能的遊客空間分布,再加入時間因子計算景點人潮變化與遊客空間分布的變化,最後則模擬不同時段的園區遊客空間分布密度。
  野柳地質公園的特殊地景吸引大量遊客參觀,造成部分園區擁擠,自然環境與軟硬體設施的負擔增加,影響遊憩品質,甚至出現地景保育與遊客安全的疑慮。為了景區資源保護與永續發展,野柳地質公園的經營管理必須考量園區空間使用狀況,了解遊客的空間分布的情形,所以必須發展出應用軌跡資料的方法,有效率的理解課題現象主軸。
  遊客為了滿足各種需求而在園區內移動,這樣的資訊被記錄下來後,即為遊客軌跡資料。他們在不同時間分布於野柳地質公園內的不同空間位置,所以遊客軌跡資料隱含有遊客空間分布的資訊,同時帶有時間資訊,對理解遊客空間分布與密度有著高度應用價值,但仍待進一步的研究,發展有效率的方法,將資料加值成為有效知識。
  我們使用GPS軌跡記錄器,以每秒記錄一筆資料的頻率收集遊客在野柳地質公園的參觀路線點位,接著運用核密度估計法,針對點資料進行分析,產出核密度表面 (kernel density surface) 以分析遊客在野柳地質公園參觀時的可能空間分布與密度,並透過景點環域分析估計特色景點周邊遊客停留狀況,再加入時間因素分析遊客數量與位置的變化,以模擬不同時段野柳地質公園遊客的空間分布,探討軌跡資料應用的可能性。
We developed a procedure that uses GPS data logger to collect visitor tracks in Yehliu geopark, and interpolate the data by using kernel density estimation method to evaluate visitors’ spatial distribution of different time. This procedure can assist authorities in managing the park. The special landscapes of Yehliu attract more and more visitors each year. Some places in the park have become overly crowded, exceeding the capacity that the environment holds. This may affect the visiting quality and visitors’ safety.
  For sustainable development of the park, we should pay closer attention to space usage in Yehliu. In other words, we have to monitor the spatial distribution of visitors. Not only to diminish the destruction of the environmental, but also to promote the quality of visit. Visitors do many different activities in the park. Their motions can be recorded as visitor tracks, which contain information of visitor spatial distribution and have the potential to be used for space management in the park.
  We use GPS data logger to collect location data of visitors every second, then analyses the data by using kernel density estimation. It can create kernel density surface demonstrating the distribution of visitors to show the density of the space. It can also estimate stationary duration of visitors near those popular scenic spots by buffer zone analysis. By adding the temporal factors, we can simulate visitor’s density in different period of time. This will help us in discussing the variation of the crowded location and the amount of the visitors. With this information and method, we will be able to manage spatial issues of the park more efficiently and reasonably.
URI: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/65708
Fulltext Rights: 有償授權
Appears in Collections:地理環境資源學系

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