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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 鄭佳昆(Chia-Kuen Cheng) | |
dc.contributor.author | Wan-Hsuan Wu | en |
dc.contributor.author | 吳婉瑄 | zh_TW |
dc.date.accessioned | 2021-06-17T08:12:50Z | - |
dc.date.available | 2024-08-20 | |
dc.date.copyright | 2019-08-20 | |
dc.date.issued | 2019 | |
dc.date.submitted | 2019-08-14 | |
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Y., & Luo, X. Y. (2018). The effect of virtual reality forest and urban environments on physiological and psychological responses. Urban forestry & urban greening, 35, 106-114. Zehrer, A., & Raich, F. (2016). The impact of perceived crowding on customer satisfaction. Journal of Hospitality and Tourism Management, 29, 88-98. Zhang, L., & Chung, S. J. E. m. (2015). Assessing the social carrying capacity of diving sites in Mabul Island, Malaysia. 56(6), 1467-1477. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/73886 | - |
dc.description.abstract | 近年來遊憩需求快速的增長,自然資源與生態都逐漸遭受到破壞,進而影響遊憩的品質,因此有了遊憩容許量的概念,其中擁擠知覺是環境品質的評量因子之一。然而目前尚未有研究探討密度中使用者在空間中的分佈模式對擁擠感是否有影響;而推測主要的原因之一可能是常見的照片模擬較難模擬出空間中使用者分佈的模式,而現地也難以操弄使用者的位置。
沈浸式虛擬實境技術(Immersive Virtual Reality, IVR)已經逐漸普及,可讓受測者融於模擬真實情況的虛擬環境中。然而實際上IVR是否能替代現有的研究工具應用在擁擠知覺的研究中,尚未有充份的研究證明,因此本篇主要分為兩個研究,研究一為確認IVR作為工具測量景觀擁擠知覺上的效度,研究二為使用IVR技術探討使用者的分佈模式對擁擠知覺是否有影響。 在研究一中,以配對比較結果顯示照片評估法與IVR評估法在擁擠感及接受度上皆有顯著差異;然而IVR測量的擁擠感及接受度,與現地及真實場景照之結果皆無顯著差異。且三個實驗中的兩種評估都顯著相關,說明每位受測者的評值趨勢類似。 研究二結果顯示相同人數平均/集中分佈在擁擠感及接受度上皆有明顯不同。而近景人數到達一定人數時,遠景增加人數對於接受度及擁擠感都沒有影響。此外,相同人數分別在受測者前/後方會造成不同的擁擠感及接受度。 以上兩個研究實證IVR是測量擁擠知覺有效的工具,而同時也証明了使用者的分佈模式會影響擁擠知覺。因此未來在調查遊憩容許量方面,可以 IVR 作為實際人群的替代媒介,並提供研究最大的實驗控制。相較過去的研究將能夠更有效的模擬出預想的狀況,在未來應用上可以更進一步的了解使用者行為。 | zh_TW |
dc.description.abstract | Owing to the rapid growth in recreational demand, excessive visitors and disrupted environment have brought negative recreational experiences. To retain its quality, concept of recreational carrying capacity was developed using perceived crowding (PC) as an indicator. In other words, PC has been viewed as an important standard in the field of recreation. Furthermore, no empirical evidence had shown if the distribution patterns of surrounding people would influence PC. A possible reason is the difficulty of manipulating distribution pattern of surrounding people both in 2D photo simulations and on-site experiments.
Immersive Virtual Reality (IVR) has become a popular research equipment which allows subjects to integrate into virtual environments that simulate real-world situations. However, doubts are still existed that if IVR could be an acceptable substitution for real environment in crowding studies, since its validity has not been tested empirically. For the issues aforementioned, this thesis consisted of two major parts. The first part tested the validity of IVR technique for applying in PC research. The second part intend to explore the influence of user distribution patterns on PC using IVR technique. In the first study, paired comparisons indicated that photographic and IVR evaluations were significantly different, regardless of PC and acceptability. Furthermore, there is no significant difference between IVR evaluations and either on-site or panoramic picture evaluations. All of the paired evaluations in the three experiments were significantly correlated, which indicated the similar trends of the different methods. The results of the second study revealed that the dispersed/concentrated distribution pattern of the surrounding people would induce different levels of PC and acceptability. Results also showed the increasing number of far-range people would not influence PC and acceptability, when the amount of the near-range people reached a certain level. Furthermore, the study also found subjects’ evaluation were different when same amount of people distributed in front or behind the subjects. The results from the above two studies confirmed IVR technique could be a valid tool in measuring PC. In the same time, this study also proved that one’s evaluation of PC and acceptability would be influenced by the distribution patterns of surrounding people. Therefore, IVR could serve as an ideal research tool in recreational studies, which could provide representative results while providing sufficient study controls. Comparing to past researches, it could simulate expected situations effectively, and facilitate our understandings of user behavior in future applications. | en |
dc.description.provenance | Made available in DSpace on 2021-06-17T08:12:50Z (GMT). No. of bitstreams: 1 ntu-108-R06628307-1.pdf: 4783508 bytes, checksum: fb612c4e6108062c4d807fdd10bfdbde (MD5) Previous issue date: 2019 | en |
dc.description.tableofcontents | 中文摘要 II
Abstract III 第一章 緒論 1 第一節 研究緣起 1 第二節 研究目的 3 第三節 研究流程 3 第二章 文獻回顧 5 第一節 擁擠知覺與擁擠理論 5 一、 擁擠知覺 5 二、 擁擠知覺影響因子 8 三、 擁擠的相關研究 15 第二節 沈浸式虛擬實境 18 一、 虛擬實境的定義 18 二、 虛擬實境的種類與應用 19 三、 沈浸式虛擬實境的相關研究 21 第三節 小結 24 第三章 以沈浸式虛擬實境探討景觀擁擠知覺的效度 27 第一節 研究背景 27 第二節 研究目的 28 第三節 研究方法 30 一、 實驗一 30 二、 實驗二 35 三、 實驗三 37 第四節 研究結果 38 一、 受測者背景/基本資料 38 二、 不同視覺評估法測量擁擠知覺以及接受度的差異 38 三、 不同視覺評估法測量相關性分析 41 第五節 小結 43 第四章 使用者的分佈模式對擁擠感的影響 45 第一節 研究背景 45 第二節 研究方法 46 一、 研究流程 46 第三節 研究結果 51 一、 受測者背景 51 二、 使用者分佈模式擁擠感及接受度之比較 51 三、 使用者分佈模式相關性分析 53 四、 小結 54 第五章 結論與建議 56 第一節 結論與討論 56 一、 研究一:以沉浸式虛擬實境探討景觀擁擠知覺之效度 56 二、 研究二:使用者的分佈模式對與擁擠感之影響 57 第二節 未來研究建議與應用 59 一、 未來研究建議 59 引用文獻 61 附錄一:以沈浸式虛擬實境探討景觀擁擠知覺之效度 79 附錄二、使用者分佈模式對擁擠感之影響 91 圖目錄 圖1- 1研究流程圖 3 圖3- 1受測場景拍攝及挑選示意圖 31 圖3- 2照片評估法之受測照片挑選示意圖 31 圖3- 3照片評估法(左)與IVR評估法之受測實驗照片(右) 33 圖3- 4實驗一以照片評估法測量擁擠知覺之受測照片範例 33 圖3- 5 Gear 360環景相機(左)與HTC-VIVE設備(右) 34 圖3- 6實驗一以IVR評估法測量擁擠知覺之場景範例 34 圖3- 7(左)研究地點(中)生態池旁步道(右)生態池旁木平臺 36 圖3- 8實驗二Lumion 8.0模擬現地相對應的VE 36 圖3- 9實驗三Lumion 8.0模擬現地場景照相對應的VE示意圖 37 圖3- 10研究一關係圖 44 圖4- 1個人空間範圍定義平面圖 47 圖4- 2集中分佈與平均分佈使用者位置平面圖 47 圖4- 3遠景及近景使用者位置平面圖 48 圖4- 4不同方向上使用者位置平面圖 48 圖4- 5虛擬研究場景 49 圖4- 6使用者位置場景製作示意圖 49 圖4- 7擁擠知覺0分與100分場景 50 表目錄 表2- 1擁擠相關研究之測量方法整理 25 表3- 1 擁擠知覺與接受度量表……………………………………………………….34 表3- 2三個實驗研究樣本受測基本資料統計 38 表3- 3人多場景(B)之照片與IVR評估擁擠知覺與接受度成對樣本t檢定(N=400) 39 表3- 4照片與IVR評估擁擠知覺與接受度成對樣本t檢定(N=1150) 40 表3- 5現地評估與IVR評估擁擠知覺與接受度成對樣本t檢定(N=90) 40 表3- 6實驗二場景人數統計平均數 40 表3- 7真實場景照與虛擬場景(VE)評估擁擠知覺與接受度成對樣本t檢定(N=240) 41 表3- 8不同視覺評估法及其擁擠感與接受度之相關性 41 表3- 9研究問題與研究結果整理 42 表4- 1 研究樣本受測者基本資料統計(N=66)……………………………………….51 表4- 2集中分佈與平均分佈之擁擠知覺及接受度平均樣本t檢定(N=66) 52 表4- 3遠景及近景不同人數之擁擠知覺及接受度平均樣本t檢定(N=66) 52 表4- 4不同方向之擁擠知覺及接受度平均樣本t檢定(N=66) 53 表4- 5使用者分佈模式之擁擠知覺及接受度相關性分析(N=66) 53 表4- 6研究問題與研究結果整理 54 | |
dc.language.iso | zh-TW | |
dc.title | 使用者的分佈模式對於擁擠感的影響 | zh_TW |
dc.title | The influence of human distribution patterns on perceived crowding | en |
dc.type | Thesis | |
dc.date.schoolyear | 107-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 歐聖榮(Sheng-Jung Ou),顏宏旭(Hung-Hsu Yen),張俊彥(Chun-Yen Chang),林晏州(Yann-Jou Lin) | |
dc.subject.keyword | 擁擠知覺,沉浸式虛擬實境,視覺評估法,虛擬環境,效度,個人空間, | zh_TW |
dc.subject.keyword | Perceived Crowding,Immersive Virtual Reality,Visual approach,Validity,Personal space, | en |
dc.relation.page | 92 | |
dc.identifier.doi | 10.6342/NTU201903740 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2019-08-15 | |
dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
dc.contributor.author-dept | 園藝暨景觀學系 | zh_TW |
顯示於系所單位: | 園藝暨景觀學系 |
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