Study on the Spatial–Temporal Pattern and Driving Mechanism of Tourism Eco-Security in the Yellow River Basin
Abstract
:1. Introduction
2. Materials and Methods
2.1. Research Region
2.2. Data Collection
2.3. Index System Building
2.4. Research Method
2.4.1. Entropy–TOPSIS Method
2.4.2. Spatial Autocorrelation Analysis and Spatial Econometric Model
2.4.3. Geo-Detector
3. Results
3.1. Temporal Evolutionary Characteristics of Tourism Eco-Security
3.2. Spatial Pattern and Variation Characteristics of Tourism Eco-Security
3.3. The Driving Factors of Tourism Eco-Security
4. Discussion
4.1. Attribution Analysis of the Spatial and Temporal Variation Patterns of Tourism Eco-Security
4.2. Key Factor Identification of the Spatial Spillover Effect of Tourism Eco-Security
4.3. Limitations and Prospects of This Study
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Target Layer | Criterion Layer | Factor Layer | Index Layer | Unit | Weight | The Meaning and Description of Indicators |
---|---|---|---|---|---|---|
Tourism ecological security | Driver | Economy | D1_Per capita GDP | yuan | 0.026 | Reflects the overall state of the regional economy. |
D2_Per capita disposal income | yuan | 0.018 | Reflects the living standard of local residents. | |||
Society | D3_Natural population growth rate | ‰ | 0.001 | Reflects the population growth trend. | ||
Tourism | D4_Growth rate of tourism revenue | % | 0.003 | Reflects the impact of tourism development and increasing tourists on the ecological environment of the tourism destination. | ||
D5_Growth rate of tourists | % | 0.002 | ||||
Pressure | Ecology | P1_Total wastewater discharge | 10,000 tons | 0.056 | Reflects the potential damage caused by regional pollutant discharge. | |
P2_Sulfur dioxide total emissions | 10,000 tons | 0.026 | ||||
P3_Life garbage clearance volume | 10,000 tons | 0.047 | ||||
P4_Solid waste production | 10,000 tons | 0.048 | ||||
Traffic | P5_Tourism traffic pressure | % | 0.062 | Reflects the impact of the flow and influx of tourists on the transportation facilities of the tourist destination; the ratio of the number of tourists to the traffic passenger volume is used to represent it. | ||
Tourism | P6_Tourism spatial index | person/km2 | 0.063 | Reflects the occupation of tourist space by tourists. | ||
P7_Population density | person/km2 | 0.033 | Reflects the occupation of tourist space by local residents. | |||
P8_Visitor density index | % | 0.038 | Reflects the degree of disturbance from tourists to the life of local residents. | |||
State | Ecology | S1_Per capita park green area | m2 | 0.043 | Reflects the quality of tourism resources. | |
S2_ Normalized Vegetation Index | 0.048 | |||||
S3_The number of days with air quality above level 2 | day | 0.006 | ||||
Economy | S4_Proportion of total tourism revenue in GDP | % | 0.032 | Reflects the development intensity of the tourism economy. | ||
Tourism | S5_Total number of tourists | 10,000 person | 0.054 | Reflects the impact intensity of tourists on the tourist destination. | ||
Impact | Economy | I1_ Per capita tourism income | yuan | 0.053 | Reflects the degree of compensation from tourists to local residents. | |
I2_Total tourism revenue | 100_million yuan | 0.060 | Reflects the influence of system operation on the development level of the regional tourism economy. | |||
Society | I3_Proportion of tertiary industry in GDP | % | 0.008 | Reflects the influence of system state change on the industrial structure level of the tourism destination. | ||
I4_Number of employees in the tertiary industry | 10,000 person | 0.038 | ||||
Tourism | I5_Tourism economic density | 10,000 yuan/km2 | 0.071 | Reflects the intensity of tourism development. | ||
Response | Economy | R1_Proportion of environmental protection investment in GDP | % | 0.052 | Reflects the degree of investment in the ecological security of the tourism destination. | |
R2_Proportion of education expenditure in GDP | % | 0.024 | ||||
Ecology | R3_Comprehensive utilization rate of solid waste | % | 0.006 | Reflects the technical level of environmental protection and pollution prevention in the tourist destination. | ||
R4_Sewage treatment rate | % | 0.005 | ||||
R5_Life garbage treatment rate | % | 0.003 | ||||
Society | R6_The number of students in ordinary high schools | 10,000 person | 0.073 | Reflects the quality of the population in the tourist destination. |
Security State | Deteriorated | Risky | Sensitive | Critically Safe | Generally Safe | Relatively Safe | Very Safe |
---|---|---|---|---|---|---|---|
Security level | I | II | III | IV | V | VI | VII |
Security index | (0, 0.2] | (0.2, 0.3] | (0.3, 0.4] | (0.4, 0.5] | (0.5, 0.6] | (0.6, 0.7] | (0.7, 1] |
Year | Moran’s Index | Z-Score | p-Value | Spatial Pattern |
---|---|---|---|---|
2003 | 0.0667 | 1.2475 | 0.2122 | Random distribution |
2004 | 0.0261 | 0.6455 | 0.5186 | Random distribution |
2005 | 0.0439 | 0.9223 | 0.3564 | Random distribution |
2006 | 0.0964 | 1.7156 | 0.0862 | Random distribution |
2007 | 0.1042 | 1.9007 | 0.0737 | Random distribution |
2008 | 0.0861 | 1.5775 | 0.1147 | Random distribution |
2009 | 0.0587 | 1.1644 | 0.2443 | Random distribution |
2010 | 0.0585 | 1.1621 | 0.2452 | Random distribution |
2011 | 0.0658 | 1.2597 | 0.2078 | Random distribution |
2012 | 0.1010 | 1.7956 | 0.0726 | Random distribution |
2013 | 0.0905 | 1.6335 | 0.1024 | Random distribution |
2014 | 0.1020 | 1.8095 | 0.0704 | Random distribution |
2015 | 0.1218 | 2.1132 | 0.0346 | Concentration distribution |
2016 | 0.1301 | 2.2195 | 0.0265 | Concentration distribution |
2017 | 0.1597 | 2.6626 | 0.0078 | Concentration distribution |
2018 | 0.2011 | 3.2872 | 0.0010 | Concentration distribution |
2019 | 0.2138 | 3.4612 | 0.0005 | Concentration distribution |
2020 | 0.1257 | 2.2055 | 0.0274 | Concentration distribution |
Variable | All the Cities | Upstream Cities | Midstream Cities | Downstream Cities | ||||
---|---|---|---|---|---|---|---|---|
qv | sig | qv | sig | qv | sig | qv | sig | |
D1 | 0.999 | 0.000 | 0.998 | 0.000 | 1.000 | 0.000 | 1.000 | 0.000 |
D2 | 0.997 | 0.000 | 1.000 | 0.000 | 1.000 | 0.000 | 0.997 | 0.000 |
D3 | 0.576 | 1.000 | 0.796 | 1.000 | 0.840 | 0.898 | 0.849 | 1.000 |
D4 | 0.596 | 1.000 | 0.896 | 0.270 | 0.823 | 0.923 | 0.663 | 0.986 |
D5 | 0.692 | 1.000 | 0.928 | 0.014 | 0.814 | 0.863 | 0.886 | 0.029 |
P1 | 0.918 | 0.004 | 0.735 | 1.000 | 0.896 | 0.170 | 0.990 | 0.053 |
P2 | 0.901 | 0.000 | 0.797 | 1.000 | 0.956 | 0.760 | 0.877 | 0.000 |
P3 | 0.948 | 0.000 | 0.928 | 0.000 | 0.962 | 0.000 | 0.964 | 0.007 |
P4 | 0.933 | 0.000 | 0.979 | 0.000 | 0.896 | 0.404 | 0.944 | 0.000 |
P5 | 0.999 | 0.000 | 0.994 | 0.000 | 1.000 | 0.000 | 1.000 | 0.000 |
P6 | 0.997 | 0.000 | 0.999 | 0.000 | 0.999 | 0.000 | 0.991 | 0.000 |
P7 | 0.980 | 0.375 | 0.986 | 0.774 | 0.959 | 0.514 | 0.999 | 0.000 |
P8 | 0.999 | 0.000 | 1.000 | 0.000 | 1.000 | 0.000 | 0.999 | 0.000 |
S1 | 0.978 | 0.243 | 0.816 | 1.000 | 1.000 | 0.000 | 1.000 | 0.000 |
S2 | 0.998 | 0.000 | 1.000 | 0.000 | 1.000 | 0.000 | 0.999 | 0.000 |
S3 | 0.377 | 0.234 | 0.462 | 0.954 | 0.551 | 0.726 | 0.539 | 0.752 |
S4 | 1.000 | 0.000 | 1.000 | 0.000 | 1.000 | 0.000 | 1.000 | 0.000 |
S5 | 0.992 | 0.000 | 0.987 | 0.006 | 0.996 | 0.000 | 0.996 | 0.000 |
I1 | 1.000 | 0.000 | 1.000 | 0.000 | 1.000 | 0.000 | 1.000 | 0.000 |
I2 | 0.992 | 0.000 | 0.990 | 0.000 | 0.999 | 0.000 | 0.998 | 0.000 |
I3 | 0.975 | 0.137 | 0.816 | 1.000 | 1.000 | 0.000 | 0.989 | 0.078 |
I4 | 0.762 | 0.925 | 0.699 | 1.000 | 0.889 | 0.200 | 0.593 | 0.997 |
I5 | 0.996 | 0.000 | 0.997 | 0.000 | 1.000 | 0.000 | 0.992 | 0.000 |
R1 | 1.000 | 0.000 | 1.000 | 0.000 | 1.000 | 0.000 | 1.000 | 0.000 |
R2 | 0.973 | 0.676 | 0.768 | 1.000 | 1.000 | 0.000 | 1.000 | 0.000 |
R3 | 0.421 | 0.967 | 0.645 | 0.260 | 0.616 | 0.798 | 0.383 | 0.906 |
R4 | 0.403 | 0.742 | 0.462 | 0.998 | 0.599 | 0.339 | 0.513 | 0.992 |
R5 | 0.475 | 1.000 | 0.512 | 1.000 | 0.684 | 0.992 | 0.371 | 1.000 |
R6 | 0.910 | 0.000 | 0.898 | 0.129 | 0.931 | 0.000 | 0.985 | 0.000 |
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Zhao, J.; Wang, S.; Li, J. Study on the Spatial–Temporal Pattern and Driving Mechanism of Tourism Eco-Security in the Yellow River Basin. Int. J. Environ. Res. Public Health 2023, 20, 3562. https://doi.org/10.3390/ijerph20043562
Zhao J, Wang S, Li J. Study on the Spatial–Temporal Pattern and Driving Mechanism of Tourism Eco-Security in the Yellow River Basin. International Journal of Environmental Research and Public Health. 2023; 20(4):3562. https://doi.org/10.3390/ijerph20043562
Chicago/Turabian StyleZhao, Junyuan, Shengjie Wang, and Jiayue Li. 2023. "Study on the Spatial–Temporal Pattern and Driving Mechanism of Tourism Eco-Security in the Yellow River Basin" International Journal of Environmental Research and Public Health 20, no. 4: 3562. https://doi.org/10.3390/ijerph20043562