Spatial-Temporal Characteristics of Multi-Hazard Resilience in Ecologically Fragile Areas of Southwest China: A Case Study in Aba
Abstract
:1. Introduction
2. Materials and Methods
2.1. Research Area
2.2. Data Sources
2.3. Measurement Methods
2.3.1. Resilience Calculation
2.3.2. Global Entropy Weight
2.3.3. Exploratory Spatial Data Analysis (ESDA)
2.3.4. Partial Least Squares (PLS) Regression
2.3.5. DROP Model
2.3.6. Selection of Indicators
3. Results
3.1. The Changing Trend of Disaster Resilience in Aba
3.2. Temporal Variation of Disaster Resilience in 13 Counties
3.3. Spatial Variation in Disaster Resilience in 13 Counties
3.4. Influencing Factors of Disaster Resilience
4. Discussion and Recommendations
4.1. Discussion
4.2. Policy Recommendations
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Dimension | Variable | Variable Description | Category | Weight | |
---|---|---|---|---|---|
Environment | Coverage | Forest coverage (%) | Prevention | 5.41% | |
Elevation | Average elevation (m) | Prevention | 7.01% | ||
Land area | Arable land area per capita (ha/person) | Resistance | 3.04% | ||
Economy | GDP | Local GDP per capita (CNY) | Prevention | 5.46% | |
Industry structure | The proportion of tertiary industry in total GDP (%) | Prevention | 5.57% | ||
Social consumer goods retail | Total retail sales of consumer goods per capita (CNY) | Prevention | 5.98% | ||
Finance revenue | Local public finance revenue (ten thousand CNY) | Prevention | 8.17% | ||
Savings | Residents’ savings per capita (CNY) | Prevention | 5.28% | ||
Society | Students | Number of students on campus | Prevention | 4.02% | |
Bed space | Number of beds in hospitals and health institutions per 1000 population/unit | Rescue | 6.26% | ||
The doctor | Number of physicians per 1000 population | Rescue | 6.33% | ||
Social labor | Employ labor (%) | Resistance, Rescue | 2.31% | ||
Social Security | Population with health insurance (%) | Resistance | 2.23% | ||
Infrastructure | Communication Equipment | Number of fixed phone users | Resistance, Rescue | 6.74% | |
Public transport | Road mileage (km/sq km) | Resistance, Rescue | 5.41% | ||
Electricity | Electricity consumption in society (ten thousand kwh) | Resistance | 7.43% | ||
Social investment | Amount of investment in fixed assets of the whole society (ten thousand CNY) | Prevention, Resistance | 4.55% | ||
Internet users | Number of internet users | Prevention, Resistance, Rescue | 8.79% | ||
Disaster pressure | Debris flow | Hazardous spots of debris flow disaster per 10,000 people | 18.2% | ||
Landslide | Hazardous spots of landslide disaster per 10,000 people | 28.5% | |||
The collapse of the ground | Hazardous spots of the collapse of the ground per 10,000 people | 53.3% |
Environment | Economy | Society | Infrastructure | |
---|---|---|---|---|
2010 | 50.4% | 55.7% | 27.1% | 60.0% |
2011 | 50.6% | 54.4% | 33.4% | 59.8% |
2012 | 50.6% | 53.2% | 31.5% | 58.1% |
2013 | 50.1% | 49.1% | 34.7% | 57.5% |
2014 | 50.2% | 49.5% | 31.9% | 56.7% |
2015 | 50.2% | 49.6% | 35.2% | 54.8% |
2016 | 50.2% | 45.5% | 34.9% | 52.5% |
2017 | 51.0% | 43.8% | 37.5% | 48.8% |
2018 | 51.4% | 44.4% | 39.3% | 51.9% |
Moran’s I | Mean | SD | z-Value | p-Value | |
---|---|---|---|---|---|
2010 | 0.256 | −0.0833 | 0.0941 | 3.676 | 0.001 |
2011 | 0.270 | −0.0803 | 0.0900 | 3.895 | 0.001 |
2012 | 0.291 | −0.0911 | 0.0890 | 4.298 | 0.001 |
2013 | 0.228 | −0.0873 | 0.0920 | 3.424 | 0.001 |
2014 | 0.246 | −0.0800 | 0.0942 | 3.460 | 0.001 |
2015 | 0.296 | −0.0833 | 0.0909 | 4.245 | 0.001 |
2016 | 0.292 | −0.0830 | 0.0907 | 4.131 | 0.001 |
2017 | 0.075 | −0.0808 | 0.0925 | 1.685 | 0.057 |
2018 | 0.045 | −0.0863 | 0.167 | 1.660 | 0.070 |
Dimension | Variable | Coefficient | VIP |
---|---|---|---|
Environment | Coverage | 0.222 | 0.856 |
Elevation | −0.169 | 0.894 | |
Land area | 0.059 | 0.679 | |
Economy | GDP | 0.003 | 0.918 |
Industry structure | 0.040 | 0.955 | |
Social consumer goods retail | 0.171 | 1.110 | |
Finance revenue | 0.225 | 1.041 | |
Savings | −0.127 | 1.075 | |
Society | Students | 0.023 | 1.244 |
Bed space | 0.169 | 0.657 | |
The doctor | 0.019 | 0.844 | |
Social labor | 0.211 | 0.650 | |
Social security | 0.064 | 0.628 | |
Infrastructure | Communication devices | 0.411 | 1.447 |
Public transport | 0.229 | 0.720 | |
Electricity | 0.189 | 1.080 | |
Social investment | 0.316 | 0.812 | |
Internet users | 0.123 | 1.138 | |
Disaster pressure | Debris flow | −0.539 | 1.184 |
Landslide | −0.238 | 0.973 | |
The collapse of the ground | −0.530 | 1.480 |
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Zhou, Y.; Su, Q.; Li, Y.; Li, X. Spatial-Temporal Characteristics of Multi-Hazard Resilience in Ecologically Fragile Areas of Southwest China: A Case Study in Aba. Int. J. Environ. Res. Public Health 2022, 19, 12018. https://doi.org/10.3390/ijerph191912018
Zhou Y, Su Q, Li Y, Li X. Spatial-Temporal Characteristics of Multi-Hazard Resilience in Ecologically Fragile Areas of Southwest China: A Case Study in Aba. International Journal of Environmental Research and Public Health. 2022; 19(19):12018. https://doi.org/10.3390/ijerph191912018
Chicago/Turabian StyleZhou, Ying, Qihao Su, Yulian Li, and Xingwei Li. 2022. "Spatial-Temporal Characteristics of Multi-Hazard Resilience in Ecologically Fragile Areas of Southwest China: A Case Study in Aba" International Journal of Environmental Research and Public Health 19, no. 19: 12018. https://doi.org/10.3390/ijerph191912018