Research on Urban Resilience from the Perspective of Land Intensive Use: Indicator Measurement, Impact and Policy Implications
Abstract
:1. Introduction
2. Theoretical Analysis
2.1. Concept Connotation of Urban Resilience
2.2. Theoretical Analysis of the Impact of Land Intensification on Urban Resilience
3. Research Design
3.1. Study Sample and Data Description
3.1.1. Research Sample
3.1.2. Data Sources
3.2. Core Index Measurement
3.2.1. Land Intensive Use Index
3.2.2. Urban Resilience Index
- ①
- Economic resilience:
- ②
- Social resilience:
- ③
- Ecological resilience:
Destination Layer | System Layer | Evaluation Metrics | Indicator Meaning |
---|---|---|---|
Land intensive use | Land input intensity | Fixed asset investment of unit land (10,000 yuan/km2) | Capital factor input |
Employment of unit land (person/km2) | Labor factor input | ||
Land use intensity | Per capita urban construction land area (m2/person) | Land conservation level | |
Population density (people/km2) | Population carrying level | ||
Land use efficiency | GDP of unit land (10,000 yuan/km2) | Land output benefit | |
Fiscal revenue of unit land (10,000 yuan/km2) | |||
Urban resilience | Economic resilience | Total GDP (billion yuan) | Economic development strength |
Per capita GDP (yuan) | |||
Per capita deposit balance of financial institutions (yuan) | Economic reserve capacity | ||
Per capita retail sales of consumer goods (yuan) | Economic operation vitality | ||
Electricity consumption per 10,000 yuan GDP (kW) | Economic transformation potential | ||
Water consumption per 10,000 yuan GDP (tons) | |||
Social resilience | Per capita disposable income of urban residents (yuan) | Residents’ risk resistance | |
Engel coefficient for urban residents | |||
Number of hospital beds per 10,000 people (zhang) | Social assistance ability | ||
Number of unemployed per 10,000 people (people) | Social stability | ||
Number of patents granted per 10,000 people (pieces) | Social transformation potential | ||
Ecological resilience | Green land rate of built-up area (%) | Ecological stability | |
Per capita green space (m2) | |||
Urban domestic sewage treatment rate (%) | Ecological response capacity | ||
Harmless treatment rate of household waste (%) | |||
Industrial wastewater discharge of per 10,000 yuan GDP (kg) | Ecological environment pressure | ||
Industrial SO2 emissions per 10,000 yuan GDP (kg) | |||
Industrial fumes emission per 10,000 yuan GDP (kg) |
3.3. Measurement Model Setting and Description
3.3.1. Measurement Model Setting
3.3.2. Variables and Explanation
4. Empirical Results and Analysis
4.1. Spatiotemporal Evolution Characteristics of Land Intensive Use and Urban Resilience
4.1.1. Spatiotemporal Evolution Characteristics of Land Intensive Use
4.1.2. Spatiotemporal Evolution Characteristics of Urban Resilience
4.2. Effects of Land Intensive Use on Urban Resilience
4.2.1. Analysis of Baseline Regression Results
4.2.2. Robustness Test
4.2.3. Quantile Regression Analysis
4.3. Effects of Different Dimensions of Land Intensive Use on Urban Resilience
Variable | Model (1) | Model (2) | Model (3) |
---|---|---|---|
ULIU- Land input intensity | 0.246 *** | ||
(16.69) | |||
ULIU- Land use intensity | −0.009 | ||
(−0.33) | |||
ULIU- Landuse benefit | 0.259 *** | ||
(16.81) | |||
Urban | 0.001 *** | 0.000 *** | 0.001 *** |
(5.16) | (2.71) | (5.74) | |
Infrastructure | 0.007 *** | 0.006 *** | 0.007 *** |
(4.38) | (3.38) | (4.28) | |
Technology | 0.002 *** | 0.004 *** | 0.002 *** |
(3.54) | (5.63) | (3.46) | |
Information | 0.011 *** | 0.002 | 0.009 *** |
(5.45) | (1.04) | (4.25) | |
Open | 0.001 *** | 0.001 ** | 0.001 *** |
(3.92) | (2.51) | (3.09) | |
Labor | 0.003 * | 0.004 ** | 0.002 |
(1.75) | (2.29) | (1.26) | |
Cons. | 0.122 *** | 0.227 *** | 0.135 *** |
(8.41) | (14.91) | (9.54) | |
Time effect | Yes | Yes | Yes |
Individual effect | Yes | Yes | Yes |
R-squared | 0.875 | 0.865 | 0.875 |
4.4. Heterogeneity of the Impact of Land Intensive Use on Urban Resilience
4.4.1. Scale Heterogeneity
4.4.2. Locational Heterogeneity
Variable | Scale Heterogeneity | Location Heterogeneity | ||
---|---|---|---|---|
Model (1) | Model (2) | Model (3) | Model (4) | |
Megacities | Non-Megacities | Eastern Cities | Central/Western Cities | |
ULIU | 0.141 *** (6.68) | 0.555 *** (9.93) | 0.176 *** (8.48) | 0.725 *** (11.54) |
Urban | 0.000 ** (2.22) | 0.001 *** (4.76) | 0.000 ** (2.39) | 0.001 *** (4.01) |
Infrastructure | 0.011 *** (3.99) | 0.005 *** (2.94) | 0.013 *** (4.75) | 0.005 ** (2.46) |
Technology | 0.002 (1.53) | 0.001 (0.84) | 0.006 *** (5.73) | 0.001 (1.06) |
Information | 0.008 ** (2.06) | 0.016 *** (6.71) | 0.007 ** (2.07) | 0.023 *** (9.01) |
Open | 0.002 *** (3.20) | 0.001 ** (2.15) | 0.001 ** (2.16) | 0.001 *** (2.78) |
Labor | 0.020 *** (5.18) | 0.006 *** (3.63) | 0.002 (0.59) | 0.003 * (1.78) |
Cons. | 0.257 *** (9.33) | 0.036 ** (1.98) | 0.300 *** (11.74) | 0.021 (1.04) |
Sample size | 1001 | 2156 | 1254 | 1903 |
Number of cities | 91 | 196 | 114 | 173 |
Timeeffect | Yes | Yes | Yes | Yes |
Individual effect | Yes | Yes | Yes | Yes |
R-squared | 0.889 | 0.838 | 0.847 | 0.861 |
5. Research Conclusions and Policy Implications
5.1. Research Conclusions
5.2. Policy Implications
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Variable | Indicator Meaning | Min | Max | Mean | Std. Dev | |
---|---|---|---|---|---|---|
Explained variable | URES | Urban resilience | 0.163 | 0.556 | 0.315 | 0.053 |
Explanatory variable | ULIU | Land intensive use | 0.107 | 0.995 | 0.151 | 0.052 |
Control variable | Urban | Level of urbanization | 19.700 | 100.000 | 55.474 | 15.006 |
Infrastructure | Level of infrastructure | 0.298 | 2.953 | 1.866 | 0.338 | |
Technology | Level of scientific research investment | 0.151 | 9.389 | 1.618 | 1.205 | |
Information | Level of information development | 5.178 | 7.807 | 6.817 | 0.317 | |
Open | Level of openness | 0.000 | 13.164 | 1.633 | 1.648 | |
Labor | Level of human capital | 0.000 | 4.709 | 2.488 | 0.875 |
Variable | Model (1) | Model (2) | Model (3) | Model (4) | Model (5) | Model (6) | Model (7) |
---|---|---|---|---|---|---|---|
ULIU | 0.237 *** | 0.250 *** | 0.254 *** | 0.247 *** | 0.272 *** | 0.276 *** | 0.276 *** |
(13.61) | (14.04) | (14.30) | (13.72) | (14.71) | (14.93) | (14.92) | |
Urban | 0.000 *** | 0.000 *** | 0.000 *** | 0.000 *** | 0.000 *** | 0.000 *** | |
(3.40) | (3.57) | (3.67) | (2.78) | (3.39) | (3.38) | ||
Infrastructure | 0.007 *** | 0.007 *** | 0.007 *** | 0.007 *** | 0.007 *** | ||
(4.44) | (4.46) | (4.22) | (4.42) | (4.40) | |||
Technology | 0.002 ** | 0.002 *** | 0.002 *** | 0.002 *** | |||
(2.38) | (2.80) | (2.79) | (2.79) | ||||
Information | 0.011 *** | 0.012 *** | 0.012 *** | ||||
(5.40) | (5.84) | (5.64) | |||||
Open | 0.001 *** | 0.001 *** | |||||
(3.58) | (3.58) | ||||||
Labor | 0.000 | ||||||
(0.16) | |||||||
Cons. | 0.234 *** | 0.214 *** | 0.200 *** | 0.198 *** | 0.130 *** | 0.121 *** | 0.121 *** |
(90.30) | (32.85) | (27.61) | (27.21) | (8.94) | (8.22) | (8.22) | |
Time effect | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
Individual effect | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
R-squared | 0.842 | 0.843 | 0.844 | 0.844 | 0.846 | 0.846 | 0.846 |
Variable | Bilateral Winsorizing 1% | Bilateral Winsorizing 5% | ||
---|---|---|---|---|
Model (1) | Model (2) | Model (3) | Model (4) | |
ULIU | 0.449 *** | 0.545 *** | 0.756 *** | 0.840 *** |
(14.28) | (16.34) | (16.18) | (17.81) | |
Urban | 0.000 *** | 0.001 *** | ||
(3.75) | (7.04) | |||
Infrastructure | 0.008 *** | 0.010 *** | ||
(4.82) | (6.27) | |||
Technology | 0.001 | 0.000 | ||
(1.17) | (0.32) | |||
Information | 0.014 *** | 0.011 *** | ||
(6.37) | (5.10) | |||
Open | 0.001 *** | 0.002 *** | ||
(4.61) | (7.07) | |||
Labor | 0.003 | 0.011 *** | ||
(1.55) | (6.19) | |||
Cons. | 0.205 *** | 0.065 *** | 0.166 *** | 0.008 |
(45.29) | (4.00) | (24.99) | (0.48) | |
Time effect | Yes | Yes | Yes | Yes |
Individual effect | Yes | Yes | Yes | Yes |
R-squared | 0.848 | 0.854 | 0.840 | 0.852 |
Variable | Model (1) OLS | Model (2) Q10 | Model (3) Q25 | Model (4) Q50 | Model (5) Q75 | Model (6) Q90 |
---|---|---|---|---|---|---|
ULIU | 0.276 *** (14.93) | 0.289 ** (2.18) | 0.284 *** (2.81) | 0.277 *** (3.99) | 0.268 *** (3.06) | 0.263 ** (2.18) |
Urban | 0.000 *** (3.39) | 0.000 (1.03) | 0.000 (1.26) | 0.000 (1.61) | 0.000 (1.09) | 0.000 (0.70) |
Infrastructure | 0.007 *** (4.40) | 0.008 (1.42) | 0.008 * (1.74) | 0.007 ** (2.27) | 0.006 (1.55) | 0.006 (1.02) |
Technology | 0.002 *** (2.79) | 0.001 (0.49) | 0.001 (0.76) | 0.002 (1.35) | 0.002 (1.29) | 0.002 (1.04) |
Information | 0.012 *** (5.64) | 0.008 (0.91) | 0.009 (1.39) | 0.011 ** (2.45) | 0.014 ** (2.31) | 0.015 * (1.86) |
Open | 0.001 *** (−3.58) | 0.000 (−0.23) | 0.001 (−0.74) | 0.001 * (−1.79) | 0.001 ** (−2.04) | 0.002 * (−1.78) |
Labor | 0.000 (0.17) | 0.000 (−0.000) | 0.000 (0.02) | 0.000 (0.08) | 0.000 (0.10) | 0.001 (0.09) |
Time effect | Yes | Yes | Yes | Yes | Yes | Yes |
Individual effect | Yes | Yes | Yes | Yes | Yes | Yes |
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Pan, Y.; Liu, J.; Cheng, C. Research on Urban Resilience from the Perspective of Land Intensive Use: Indicator Measurement, Impact and Policy Implications. Buildings 2024, 14, 2564. https://doi.org/10.3390/buildings14082564
Pan Y, Liu J, Cheng C. Research on Urban Resilience from the Perspective of Land Intensive Use: Indicator Measurement, Impact and Policy Implications. Buildings. 2024; 14(8):2564. https://doi.org/10.3390/buildings14082564
Chicago/Turabian StylePan, Yue, Jie Liu, and Chao Cheng. 2024. "Research on Urban Resilience from the Perspective of Land Intensive Use: Indicator Measurement, Impact and Policy Implications" Buildings 14, no. 8: 2564. https://doi.org/10.3390/buildings14082564