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With the development of the economy, people’s living standards are getting higher and higher. People will look for ways to relax after busy work, and rural tourism is a slow-paced life. The purpose of this paper is to analyse the evaluation system of rural sustainable tourism land based on ecosystem service value. In this paper, an evaluation model based on AHP and association rules is proposed, and the two methods are described in detail. The experimental results of this paper show that the number of tourists has increased from 12 % in 2014 to 24.9 % in 2020, and the growth rate of tourism revenue has increased from 24 % in 2014 to 30 % in 2020. Rural tourism is an important part of tourism and an important force to implement the strategy of rural revitalisation. It plays an important role in accelerating the modernisation of agriculture and rural areas, the integrated development of urban and rural areas, and poverty alleviation in poor areas. The number of farm stays has increased from 1.9 million in 2014 to 3.25 million in 2020. It can be seen that with the growth of time, the rapid development of the economy, and increasing people who love to travel, this has led to changes in the utilisation rate of rural land. Therefore, the research on the evaluation system of rural sustainable tourism land based on ecosystem service value is very meaningful.
Czasopismo
Rocznik
Tom
Strony
347--363
Opis fizyczny
Bibliogr. 19 poz., rys., tab., wykr.
Twórcy
autor
- School of Tourism and Geography, Hulunbuir University, Hailar 021008, Inner Mongolia, China
autor
- School of Tourism and Geography, Hulunbuir University, Hailar 021008, Inner Mongolia, China
Bibliografia
- [1] Zang Z, Zou X, Zuo P, Song Q, Wang C, Wang J. Impact of landscape patterns on ecological vulnerability and ecosystem service values: An empirical analysis of Yancheng Nature Reserve in China. Ecol Indicators. 2017;72:142-52. DOI: 10.1016/j.ecolind.2016.08.019.
- [2] Yang Y, Song G, Lu S. Study on the ecological protection redline (EPR) demarcation process and the ecosystem service value (ESV) of the EPR zone: A case study on the city of Qiqihaer in China. Ecol Indicators. 2020;109:105754.1-105754.13. DOI: 10.1016/j.ecolind.2019.105754.
- [3] Lloyd-Smith P. A note on the robustness of aggregate ecosystem service values. Ecol Economics. 2017;146:778-80. DOI: 10.1016/j.ecolecon.2017.12.008.
- [4] Song XP. Global estimates of ecosystem service value and change: taking into account uncertainties in satellite-based land cover data. Ecol Economics. 2018;143:227-35. DOI: 10.1016/j.ecolecon.2017.07.019.
- [5] Makwinja R, Kaunda E, Mengistou S, Alamirew T. Impact of land use/land cover dynamics on ecosystem service value-a case from Lake Malombe, Southern Malawi. Environ Monitoring Assess. 2021;193(8):1-23. DOI: 10.1007/s10661-021-09241-5.
- [6] Negash E, Getachew T, Birhane E, Gebrewahed H. Ecosystem service value distribution along the agroecological gradient in north-central Ethiopia. Earth Systems Environ. 2020;4(1):107-16. DOI: 10.1007/s41748-020-00149-7.
- [7] Hou L, Wu F, Xie X. The spatial characteristics and relationships between landscape pattern and ecosystem service value along an urban-rural gradient in Xi'an city, China. Ecol Indicators. 2020;108:105720.1-105720.10. DOI: 10.1016/j.ecolind.2019.105720.
- [8] Watson-Gandy JAC. A disaggregate travel demand model. J Operational Res Soc. 2017;27(2):521-2. DOI: 10.1057/jors.1976.103.
- [9] Backer E, Morrison AM. Vfr travel: Is it still underestimated? Int J Tourism Res. 2017;19(4):395-9. DOI: 10.1002/jtr.2145.
- [10] Bongkoo L, Agarwal S, Hyunji K. Influences of travel constraints on the people with disabilities' intention to travel: An application of Seligman's helplessness theory. Tourism Manage. 2017;33(3):569-79. DOI: 10.1016/j.tourman.2011.06.011.
- [11] Ding C, Wang D, Liu C, Zhang Y, Yang J. Exploring the influence of built environment on travel mode choice considering the mediating effects of car ownership and travel distance. Transportation Res Part A Policy Practice. 2017;100:65-80. DOI: 10.1016/j.tra.2017.04.008.
- [12] Woerther PL, Andremont A, Kantele A. Travel-acquired ESBL-producing Enterobacteriaceae: impact of colonization at individual and community level. J Travel Medicine. 2017;24:S29-34. DOI: 10.1093/jtm/taw101.
- [13] Boyce D, O'Neill CR, Scherr W. Solving the sequential travel forecasting procedure with feedback. Transportation Res Record. 2018;2077(1):129-35. DOI: 10.3141/2077-17.
- [14] Ilić P, Ilić S, Nesković-Markić D, Stojanović-Bjelić L, Farooqi ZUR, Sole B, et al. Source identification and ecological risk of polycyclic aromatic hydrocarbons in soils and groundwater. Ecol Chem Eng S. 2021;28(3):355-63. DOI: 10.2478/eces-2021-0024.
- [15] Woodard D, Nogin G, Koch P, Goldszmidt M, Horvitz E. Predicting travel time reliability using mobile phone GPS data. Transportation Res Part C. Emerging Technol. 2017;75:30-44. DOI: 10.1016/j.trc.2016.10.011.
- [16] Rashidi TH, Abbasi A, Maghrebi M, Hasan S, Waller TS. Exploring the capacity of social media data for modelling travel behaviour: Opportunities and challenges. Transportation Res Part C. Emerging Technol. 2017;75:197-211. DOI: 10.1016/j.trc.2016.12.008.
- [17] Travelletti J, Malet JP, Samyn K, Grandjean G, Jaboyedoff M. Control of landslide retrogression by discontinuities: evidences by the integration of airborne-and ground-based geophysical information control of landslide retrogression by. Landslides. 2018;10(1):37-54. DOI: 10.1007/s10346-011-0310-8.
- [18] Hagenauer J, Helbich M. A comparative study of machine learning classifiers for modeling travel mode choice. Expert Systems Applications. 2017;78:273-282. DOI: 10.1016/j.eswa.2017.01.057.
- [19] Lin WP. Monitoring and protection of forest ecological tourism resources by dynamic monitoring system. Ecol Chem Eng S. 2019;26(1):189-97. DOI: 10.1515/eces-2019-0018.
Typ dokumentu
Bibliografia
Identyfikator YADDA
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