| Literature DB >> 35329174 |
Yu Chen1, Mengke Zhu2.
Abstract
In order to explore the spatiotemporal evolution of land use function and its driving factors in China, taking both sides of the Hu Line as an example, we used Exploratory Spatial Data Analysis and Geographically Weighted Regression methods to reveal dynamic evolution law, spatial characteristics and influencing factors of the "Production-Living-Ecology" functions of 288 prefecture-level cities on both sides of the Hu Line. The results show that: (1) In the temporal dimension, the coordination of "Production-Living-Ecology" functions of land use in China has been improved, and the Hu Line can be roughly used as the boundary of China's territorial space use. (2) In the spatial dimension, there is a significant positive spatial correlation between "Production-Living-Ecology" functions of land use in China, and the coordination gap between "Production-Living-Ecology" functions of land use on both sides of the Hu Line is gradually narrowing. (3) In terms of influencing mechanism, the coordination of "Production-Living-Ecology" functions is mainly driven by internal factors and is supplemented by external ones. The influence pattern of most driving factors is consistent with the layout characteristics of "strong east and weak west" of the Hu Line.Entities:
Keywords: China; ESDA-GWR; Hu Line of land; spatial heterogeneity; “production-living-ecology” coordination
Mesh:
Year: 2022 PMID: 35329174 PMCID: PMC8953988 DOI: 10.3390/ijerph19063488
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Figure 1Population size and economic level on both sides of the Hu Line.
Functional coordination evaluation index system of “production-living-ecology”.
| Criteria Layer | Elements Layer | Basic Indicators |
|---|---|---|
| Production function | Agricultural production | Proportion of agricultural land |
| Proportion of agricultural output value | ||
| Per unit area yield of grain | ||
| Non-agricultural production | Proportion of construction land | |
| Average gross industrial output value of land | ||
| Average industrial output value | ||
| Freight volume | ||
| Economic development | Per capita GDP | |
| Amount of foreign capital used | ||
| Fixed asset investment per land | ||
| The industrial structure | ||
| Living function | Living standard | Proportion of residential land area |
| Density of road network | ||
| Material life | The employment rate | |
| Per capita savings balance | ||
| Spiritual life | Proportion of science and education expenditure | |
| Number of books in public libraries per 10,000 people | ||
| Number of college students per 10,000 persons | ||
| Ecological function | Ecological foundation | Green coverage rate of built-up area |
| Per capita green garden area | ||
| Ecological carrying | Average industrial wastewater discharge | |
| Average industrial sulfur dioxide emissions | ||
| Average industrial smoke and dust emission | ||
| Ecological governance | Comprehensive utilization rate general solid waste | |
| Sewage treatment rate | ||
| Harmless treatment rate of domestic garbage |
Functional coordination of “production-living-ecology” in China from 2008 to 2017.
| 2008 | 2011 | 2014 | 2017 | |
|---|---|---|---|---|
| Total | 0.1223 | 0.1732 | 0.1320 | 0.1366 |
| The Southeastern | 0.1069 | 0.1701 | 0.1385 | 0.1341 |
| The Northwest | 0.1207 | 0.1729 | 0.1327 | 0.1364 |
Figure 2Distribution of “production-living-ecology” functional coordination in China from 2008 to 2017.
Figure 3Spatial pattern of “production-living-ecology” functional coordination in China from 2008 to 2017.
Selection of driving factors for “production-living-ecology” functional coordination.
| Driving Factors | Variables | Definition |
|---|---|---|
| Internal driving force | Production-Living function | / |
| Production-Ecological function | / | |
| Living-Ecological function | / | |
| External driving force | Population density | population/total area |
| Financial density | general budget expenditure/total area of local finance | |
| Economic density | regional GDP/ total area | |
| Water resource density | total water resources/total area of the region |
Calculation results of the GWR model.
| Minimum | Lower Quartile | Mean | Upper Quartile | Maximum | |
|---|---|---|---|---|---|
| P-L | −0.3195 | 0.1447 | 0.1765 | 0.2098 | 0.3271 |
| P-E | −0.1798 | 0.0722 | 0.0703 | 0.1111 | 0.1214 |
| L-E | 0.3190 | 0.3864 | 0.4041 | 0.4033 | 1.3531 |
| ED | −0.1690 | 0.0563 | 0.0565 | 0.0584 | 0.0889 |
| FD | 0.0484 | 0.0494 | 0.0537 | 0.0530 | 0.3024 |
| PD | 0.0028 | 0.0261 | 0.0345 | 0.0433 | 0.0815 |
| WD | −0.0782 | −0.0041 | −0.0026 | 0.0014 | 0.0026 |
Figure 4The spatial coefficient distribution of internal driving force (a) production-living function, (b)production-ecological function, (c) living-ecological function.
Figure 5The spatial coefficient distribution of external driving force (a) economic density, (b) financial density, (c) population density, (d) water resource density.