本文選題：典型城市 + 氣候舒適度��； 參考：《陜西師范大學(xué)》2012年博士論文

【摘要】：氣候與旅游是近年來國(guó)內(nèi)外旅游研究的一個(gè)熱點(diǎn)問題,國(guó)內(nèi)外旅游研究者在旅游氣候資源評(píng)價(jià)與開發(fā)、氣候變化對(duì)旅游資源的影響、氣候變化對(duì)旅游需求的影響、氣候變化對(duì)目的地客流量接待及旅游流的影響等方面進(jìn)行了深入的研究。旅游氣候舒適度是氣候與旅游研究的一個(gè)重要內(nèi)容,然而相關(guān)研究多為現(xiàn)狀的分析和評(píng)價(jià),沒有從一個(gè)較長(zhǎng)時(shí)間尺度上考察氣候舒適度的變化及其規(guī)律,且就氣候論“氣候”,較少將氣候舒適度與客流量年內(nèi)變化聯(lián)系起來,探討氣候舒適度與客流量年內(nèi)變化的關(guān)系。本文以典型城市為研究對(duì)象,在系統(tǒng)收集相關(guān)數(shù)據(jù)資料的基礎(chǔ)上,主要完成了城市氣候舒適度的現(xiàn)狀評(píng)價(jià)及30年來城市旅游氣候舒適度的變化分析、游客對(duì)氣候變化的感知及其對(duì)出游行為影響的調(diào)查研究、氣候舒適度與客流量、游客網(wǎng)絡(luò)關(guān)注度時(shí)空相關(guān)關(guān)系分析、氣候舒適度變化對(duì)客流量的影響分析等幾個(gè)方面的研究,主要結(jié)論如下： (1)西安市居民年內(nèi)氣候變化感知與實(shí)際年內(nèi)氣候變化狀況基本一致。西安市居民年內(nèi)氣候變化感知與出游季節(jié)偏好具有較強(qiáng)的一致性,氣候最舒適的季節(jié)是居民最愿意出游的季節(jié),最不舒適的季節(jié)是居民最不愿意出游的季節(jié),說明氣候舒適性是影響游客出游時(shí)間選擇的重要因素。氣候是影響居民旅游目的地選擇的重要因素,其它條件相同的情況下,居民偏好于氣候舒適的旅游目的地。氣候是影響居民旅游項(xiàng)目選擇的重要因素,不同季節(jié)居民對(duì)旅游項(xiàng)目的偏好不同,春季和秋季居民對(duì)不同旅游項(xiàng)目的偏好較為一致,有相同的變化趨勢(shì),且偏好程度相差不大,夏季和冬季居民對(duì)不同旅游項(xiàng)目的偏好波動(dòng)較大。 (2)緯度和海拔高度是影響城市旅游氣候舒適度的重要因素。城市年綜合氣候舒適指數(shù)隨緯度的降低先升高后降低,說明城市年氣候舒適度隨緯度的降低先升高后降低,長(zhǎng)江流域城市年綜合氣候舒適指數(shù)隨海拔高度的降低呈一下降趨勢(shì),城市年氣候舒適度隨海拔高度的降低呈下降趨勢(shì)。隨著緯度的降低,1-2月和12月氣候舒適度升高,3-5月和10-11月氣候舒適度先升高后降低,6-9月氣候舒適度降低。依據(jù)城市綜合氣候舒適指數(shù)的年內(nèi)變化,可以將46個(gè)城市劃分為倒“V”形、倒“U”形、“M”形和寬“U”形4種類型。依據(jù)城市旅游氣候舒適期的年內(nèi)分布,可以將46個(gè)城市劃分為夏適型、冬適型、春秋適型和四季型4種類型。 (3)氣候舒適度是影響游客網(wǎng)絡(luò)關(guān)注度時(shí)空變化的重要因素。收集30個(gè)旅游城市游客網(wǎng)絡(luò)關(guān)注度,分析其年內(nèi)時(shí)空變化狀況,按游客網(wǎng)絡(luò)關(guān)注度年內(nèi)變化,將30個(gè)城市劃分為13種類型。在游客網(wǎng)絡(luò)關(guān)注度月指數(shù)與氣候舒適度指數(shù)比較的基礎(chǔ)上,采用虛擬變量的回歸分析方法,建立相關(guān)模型,分析氣候舒適度與游客網(wǎng)絡(luò)關(guān)注度的相關(guān)關(guān)系,長(zhǎng)春、北京、西寧和�？谟慰途W(wǎng)絡(luò)關(guān)注度月指數(shù)的氣候彈性系數(shù)分別為0.542、0.46、1.182和0.8,長(zhǎng)白山、八達(dá)嶺長(zhǎng)城、周莊古鎮(zhèn)、張家界武陵源游客網(wǎng)絡(luò)關(guān)注度月指數(shù)的氣候彈性系數(shù)分別為0.333、0.632、0.438、0.324。氣候舒適度是影響游客網(wǎng)絡(luò)關(guān)注度空間分布的重要因素,綜合氣候舒適指數(shù)每變化1個(gè)單位,游客網(wǎng)絡(luò)關(guān)注度將增加(或減少)0.641萬次。 (4)氣候舒適度是影響客流量時(shí)空變化的重要因素。收集2005-2007年26個(gè)城市各月入境客流量,分析其年內(nèi)時(shí)空變化狀況,將其年內(nèi)變化分為4種類型。在客流量月指數(shù)與氣候舒適度指數(shù)比較的基礎(chǔ)上,采用虛擬變量的回歸分析方法,建立了4個(gè)城市入境旅游客流量月指數(shù)模擬模型,哈爾濱、大連、北京、海口入境游客月指數(shù)氣候彈性系數(shù)分別為0.666、0.372、0.625、1.227。同時(shí)收集了4個(gè)城市2005-2007年各月國(guó)內(nèi)客流量以及4個(gè)景區(qū)的客流量數(shù)據(jù),對(duì)國(guó)內(nèi)客流量與氣候舒適度年內(nèi)變化的相關(guān)關(guān)系進(jìn)行了分析,北京、海口、張家界和昆明國(guó)內(nèi)游客月指數(shù)氣候彈性系數(shù)分別為0.1221、1.069、0.401、0.763,九寨溝、青城山、都江堰和廣漢三星堆游客月指數(shù)氣候彈性系數(shù)分別為2.337、0.831、0.421、0.816。利用旅游資源豐度、經(jīng)濟(jì)發(fā)展水平、綜合氣候舒適指數(shù)3個(gè)因素,建立其與入境及國(guó)內(nèi)客流量地域分布的統(tǒng)計(jì)關(guān)系,綜合氣候舒適度指數(shù)每變化1個(gè)單位,入境客流量將增加(或減少)2.17萬人,國(guó)內(nèi)客流量將增加(或減少)30.72萬人。 (5)全球氣候變化使城市氣候舒適度發(fā)生了改變。30年來旅游氣候舒適度的變化主要受地理緯度的影響,重慶以北絕大部分城市年綜合氣候舒適指數(shù)上升,旅游氣候舒適度升高,重慶以南絕大部分城市年綜合氣候舒適指數(shù)下降,旅游氣候舒適度降低。緯度較高的城市溫濕指數(shù)、風(fēng)寒指數(shù)和綜合氣候舒適指數(shù)變化幅度相對(duì)較大,緯度較低的城市變化幅度相對(duì)較小。春季緯度較高的城市氣候舒適度上升,緯度較低的城市氣候舒適度有所下降；夏季絕大多數(shù)城市氣候舒適度降低,且隨緯度的降低城市氣候舒適度下降幅度有所減��；秋季絕大部分城市氣候舒適度下降,且隨緯度的降低氣候舒適度的下降幅度在增大；冬季除濟(jì)南外,南昌及其以北城市氣候舒適度均上升,且隨緯度的降低氣候舒適度上升的幅度在減小。30年來45個(gè)城市年綜合氣候舒適指數(shù)共上升了26.8,促進(jìn)了我國(guó)旅游業(yè)的發(fā)展,但隨著全球的進(jìn)一步升溫,年綜合氣候舒適指數(shù)下降的城市將進(jìn)一步增多,下降的幅度將進(jìn)一步增大,對(duì)旅游業(yè)的促進(jìn)將逐漸轉(zhuǎn)變?yōu)橐种�。極端天氣氣候?qū)β糜螛I(yè)有重大的影響,2008年雪災(zāi)對(duì)旅游業(yè)的影響,其游客損失量與客流量基數(shù)(本底值)成正比,游客損失率與2008年本底值(基數(shù))成反比,損失量和損失率兩者均與受災(zāi)程度存在一定的成正比關(guān)系。 (6)氣候舒適度變化對(duì)目的地客流量接待產(chǎn)生了影響。利用綜合氣候舒適指數(shù)及40個(gè)城市的相關(guān)氣候和旅游客流量數(shù)據(jù),構(gòu)建國(guó)內(nèi)外旅游氣候模型,分析氣候舒適度變化對(duì)旅游業(yè)的影響。結(jié)果顯示綜合氣候舒適指數(shù)每變化1個(gè)單位我國(guó)入境及國(guó)內(nèi)旅游客流量將增加或減少1.852萬人次和35.263萬人次,重慶以北絕大部分城市年接待客流量增加,重慶以南絕大部分城市年接待客流量減少,30年來40城市國(guó)內(nèi)及入境旅游客流量分別增加540.7萬人次和28.4萬人次。 本文的主要?jiǎng)?chuàng)新點(diǎn)有： (1)以溫濕指數(shù)、風(fēng)寒指數(shù)和著衣指數(shù)為基礎(chǔ),采用專家打分和層次分析法確定各分指數(shù)的權(quán)重,建立了一個(gè)新的旅游氣候舒適性綜合評(píng)價(jià)模型,該模型不僅能直接反映客流量的年內(nèi)月變化,而且還有可加和等特征。 (2)構(gòu)建氣候舒適度與客流量及游客網(wǎng)絡(luò)關(guān)注度時(shí)空相關(guān)模型,揭示旅游氣候舒適度彈性。傳統(tǒng)的研究多以氣候論“氣候”,較少將氣候舒適度與客流量年內(nèi)變化聯(lián)系起來,探討氣候舒適度與客流量年內(nèi)變化的關(guān)系；本文系統(tǒng)收集城市客流量及游客網(wǎng)絡(luò)關(guān)注度數(shù)據(jù),分析其時(shí)空變化規(guī)律,并將其與氣候舒適度時(shí)空變化規(guī)律相對(duì)比,構(gòu)建氣候舒適度與客流量及游客網(wǎng)絡(luò)關(guān)注度時(shí)空相關(guān)模型,揭示旅游氣候舒適度彈性。 (3)本文揭示了極端天氣氣候?qū)β糜螛I(yè)影響的動(dòng)力機(jī)制,并借助本底趨勢(shì)線理論,分析了2008年雪災(zāi)對(duì)旅游業(yè)的影響,發(fā)現(xiàn)2008年雪災(zāi)對(duì)旅游業(yè)的影響,其游客損失量與客流量基數(shù)(本底值)成正比,游客損失率與2008年本底值(基數(shù))成反比,損失量和損失率兩者均與受災(zāi)程度存在一定的成正比關(guān)系。 (4)構(gòu)建旅游氣候模型,估算氣候變化對(duì)旅游業(yè)的影響。國(guó)內(nèi)外有關(guān)氣候變化對(duì)游客旅游需求和目的地客流量接待影響的研究多以其中一種或幾種氣候要素為變量,通過建立相關(guān)模型定量分析氣候變化對(duì)旅游業(yè)的影響,這種研究方法存在較大的缺陷,因?yàn)榇蠖鄶?shù)氣候要素對(duì)旅游業(yè)的影響均存在“過猶不及”的現(xiàn)象。本文以綜合氣候舒適指數(shù)為變量,構(gòu)建旅游氣候模型,從氣候舒適度視角定量分析了氣候變化對(duì)旅游業(yè)的影響。
[Abstract]:Climate and tourism are a hot issue of tourism research at home and abroad in recent years. The evaluation and development of tourism climate resources, the impact of climate change on tourism resources, the impact of climate change on tourism demand, the impact of climate change on tourist flow and the impact of tourist flow are deeply studied. The comfort degree of tourism climate is an important content of climate and tourism research. However, the related research is mostly the analysis and evaluation of the present situation. It does not examine the changes and laws of climate comfort from a long time scale, and the climate theory is "climate", and the climate comfort is associated with the changes in the annual passenger flow, and the climate comfort is discussed. In this paper, based on the collection of relevant data, this paper mainly completed the assessment of the status of urban climate comfort and the analysis of the changes in the climate comfort of urban tourism in the past 30 years, and the research on the perception of climate change and its impact on travel behavior on the basis of the system collection of relevant data. The main conclusions are as follows: the climate comfort and the passenger flow, the spatio-temporal correlation analysis of the tourist network attention, the impact analysis of the climate comfort change on the passenger flow, and so on.
(1) the climate change perception of the residents in Xi'an is basically the same as that in the actual year. The climate change perception of the residents in Xi'an has a strong consistency with the travel season preference. The most comfortable season in the climate is the most likely season for the residents to travel, and the most discomfort season is the most reluctant season for the residents to travel. Climate is an important factor affecting the choice of tourists' travel time. Climate is an important factor affecting the choice of tourist destinations. Under the same conditions, the residents prefer the comfortable tourist destinations. Climate is an important factor affecting the selection of residents' tourism projects, and the preference of residents in different seasons is different. In spring and autumn, the preference of residents in spring and autumn is more consistent, with the same trend of change, and the difference of preference degree is small. The preference of residents in summer and winter on different tourism items fluctuates greatly.
(2) latitude and altitude are the important factors that affect the comfort of urban tourism climate. The urban annual comprehensive climate comfort index rises first and then decreases with the decrease of latitude. It indicates that the annual climate comfort of the city increases first and then decreases with the decrease of latitude, and the urban annual climate comfort index of the Yangtze River Basin decreases with the decrease of altitude. The climate comfort of the city decreased with the decrease of altitude. As the latitude decreased, the climate comfort increased in 1-2 and December, the climate comfort increased first and then decreased in the 3-5 and 10-11 months, and the Climate Comfortableness decreased in 6-9 months. According to the annual change of the urban comprehensive climate comfort index, the 46 cities could be divided into "inverted" "V" shape. There are 4 types of "U" shape, "M" shape and wide "U" form. According to the annual distribution of urban tourism climate comfort period, 46 cities can be divided into 4 types of summer adaptation, winter adaptation, spring and autumn adaptation and four seasons.
(3) the climate comfort is an important factor affecting the spatial and temporal changes of tourists' network attention. To collect the network attention of 30 tourist cities, analyze the changes in time and space during the year, and divide the 30 cities into 13 types according to the changes of the visitors' network attention in the year. The basis of the comparison between the monthly index of tourist network and the climate comfort index is based on the comparison between the tourist network and the climate comfort index. On the basis of the regression analysis of virtual variables, a correlation model is established to analyze the relationship between climate comfort and tourist network attention. The climatic elasticity coefficient of the tourist network index of Changchun, Beijing, Xining and Haikou is 0.542,0.46,1.182 and 0.8, respectively, Changbai Mountain, the Badaling Great Wall, Zhouzhuang, Zhangjiajie Wulingyuan. The climate elasticity coefficient of the network concern month index (0.333,0.632,0.438,0.324.) is an important factor affecting the spatial distribution of tourists' network attention, and 1 units of the comprehensive climate comfort index will increase (or decrease) by 6 thousand and 410 times.
(4) the climate comfort is an important factor affecting the spatio-temporal change of passenger flow. Collecting and analyzing the changes in the year and space of each month in 26 cities of 2005-2007 years, and dividing the changes into 4 types. On the basis of the comparison of the monthly volume of passenger flow index and the climate comfort index, the regression analysis method of virtual variables is adopted to establish 4. Monthly index simulation model of inbound tourist flow in a city, Harbin, Dalian, Beijing and Haikou, the monthly index of the inbound tourist index is 0.666,0.372,0.625,1.227., and the domestic passenger flow of 4 cities for 2005-2007 years and the passenger flow data of 4 scenic spots are collected at the same time, and the domestic passenger flow and climate comfort are changed in the year. The correlation relationship was analyzed. The monthly index climate elasticity coefficient of Beijing, Haikou, Zhangjiajie and Kunming was 0.1221,1.069,0.401,0.763, and the monthly index of tourist index of tourists in Jiuzhaigou, Qingchengshan, Dujiangyan and Guanghan was 2.337,0.831,0.421,0.816. using tourism resources abundance, economic development level and comprehensive gas. The 3 factors of the weather comfort index set up a statistical relationship with the regional distribution of inbound and domestic passenger flow. The integrated climate comfort index will increase (or decrease) by 21 thousand and 700 people with 1 units per change, and the domestic passenger flow will increase (or decrease) by 307 thousand and 200 people.
(5) global climate change has changed the comfort degree of urban climate in.30 years. The changes in the comfort degree of tourism climate are mainly influenced by the geographical latitude. The comprehensive climate comfort index of most cities in the north of Chongqing rises, the comfort of tourism climates, and the annual comprehensive climate comfort index of Chongqing in the south of the south of Chongqing is reduced, and the tourism climate is reduced. The comfort degree is lower. The temperature and humidity index of the city with high latitude, the wind chill index and the comprehensive climate comfort index are relatively large, the cities with lower latitude are relatively small. The urban climate comfort of higher latitudes in spring is rising, the comfort degree of the cities with lower latitudes is reduced, and the climate comfort of most cities in summer is more comfortable. The decline in urban climate comfort decreased with the decrease of latitude, and the climate comfort decreased in most cities in autumn, and the decrease of climate comfort decreased with latitude. In addition to Ji'nan, the climate comfort of Nanchang and its north cities rose and the climate comfort increased with latitude. The overall climate comfort index of the 45 cities in the year of.30 has risen by 26.8, which has promoted the development of tourism in China. However, with the further warming of the world, the city will be further increased, the decline will be further increased, and the promotion of tourism will be gradually reduced to inhibition. The air climate has a significant impact on tourism. In 2008, the effect of snow disaster on tourism is proportional to the base value of passenger flow (the base value). The loss rate of tourists is inversely proportional to the base value of 2008 (the base), and both the loss and the loss rate are in direct proportion to the degree of disaster.
(6) the climate comfort changes have an impact on the destination passenger flow reception. Using the comprehensive climate comfort index and the related climate and tourist traffic data of 40 cities, the domestic and foreign tourism climate model is constructed, and the impact of climate comfort changes on tourism is analyzed. The results show that the comprehensive climate comfort index has 1 units per change in China. The flow of tourists and domestic tourists will increase or decrease by 18 thousand and 520 and 352 thousand and 630 passengers. The annual passenger flow of most cities in the north of Chongqing is increased, and the annual passenger flow in most cities in the south of Chongqing is reduced. In the 30 years, the domestic and inbound tourist flows in 40 cities have increased by 5 million 407 thousand and 284 thousand respectively.
The main innovations of this article are:
(1) on the basis of temperature and humidity index, wind cold index and clothing index, the weight of each index is determined by expert scoring and analytic hierarchy process. A new comprehensive evaluation model of tourism climate comfort is established. This model can not only directly reflect the monthly change of passenger flow, but also can be added and so on.
(2) to construct the spatio-temporal correlation model of climate comfort and passenger flow and tourist network attention, to reveal the elasticity of tourism climate comfort. Passenger traffic and tourist network attention data, analysis of its temporal and spatial variation law, and compare it with climate comfort time and space change law, build climate comfort and passenger flow and tourist network concern time and space correlation model, to reveal the flexibility of tourism climate comfort.
(3) this paper reveals the dynamic mechanism of the impact of extreme weather and climate on tourism, and analyses the impact of snow disaster on Tourism in 2008 with the help of the bottom trend line theory, and finds the effect of snow disaster on Tourism in 2008. The loss of tourists is inversely proportional to the Cheng Zheng ratio of passenger flow base (base value), the loss rate of tourists and the base value of 2008 (base number). Both loss and loss rate are directly proportional to the degree of disaster.
(4) to construct a tourist climate model to estimate the impact of climate change on tourism. The research on the impact of climate change on tourist demand and destination passenger flow reception at home and abroad is mainly based on one or several climatic factors as variables, and the quantitative analysis of the impact of climate change on tourism is made by establishing a related model. In this paper, the impact of climate change on tourism is quantitatively analyzed from the perspective of climate comfort.
【學(xué)位授予單位】：陜西師范大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2012
【分類號(hào)】：F592.7;P4;F224

【引證文獻(xiàn)】

相關(guān)期刊論文 前1條

1 趙小寧;胡曉黎;;商洛旅游氣候舒適度評(píng)價(jià)及氣象服務(wù)[J];商洛學(xué)院學(xué)報(bào);2013年02期

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本文編號(hào)：2078009