A Multi-Objective Scenario Study of County Land Use in Loess Hilly Areas: Taking Lintao County as an Example
Abstract
:1. Introduction
2. Study Area and Materials
2.1. Overview of the Study Area
2.2. Data Sources and Pre-Processing
3. Research Methodology
3.1. Land Use Dynamic Degree
3.2. FLUS Model
3.2.1. ANN-Based Suitability Probability Estimation
3.2.2. Self-Adaptive Inertia and Competition Mechanism CA
3.2.3. Precision Validation
3.3. The InVEST Model
3.4. Scenarios and Parameter Settings
3.4.1. Modeling Scenario Settings
- Cropland protection scenario (CPS). China, as a populous country, attaches great importance to the protection of food and cropland, has formulated strict cropland protection measures and put forward the slogan of “Strictly abide by the red line of 1.8 billion mu of cropland”. Under this scenario, permanent prime cropland in Lintao County is used as a restricted conversion area, strictly limiting the conversion of cropland within the study area, allowing only general cropland to be converted to urban land and other construction land, and permitting sloping cropland to be “returned to forests and grasses”.
- Ecological protection scenario (EPS). “Green mountains are golden mountains”. China attaches great importance to the construction of ecological civilization and strengthening the protection of the ecological environment. In recent years, Lintao County vigorously implemented the “ecological county” strategy and successively implemented a number of key ecological protection projects. In the EPS, the ecological protection red line in Lintao County was added as a restricted conversion zone, strictly controlling the conversion of ecological land (forest land, grassland, water area) outside the red line into other land types; it allows other land types to be converted to ecological land.
- Economic development scenario (EDS). Lintao County is included in the Lanzhou-Xining City Cluster Development Plan, and its economic development is bound to enter a fast lane. Regional economic development is inevitably accompanied by urbanization, which leads to the outward expansion of construction land. In this scenario, the expansion of urban land, rural settlement area, and other construction land will be prioritized, regardless of the constraints of land use planning and government policies in Lintao County. At the same time, regional economic development cannot be achieved without the support of primary industries, thus raising the priority of croplands.
- Comprehensive development scenario (CDS). The above three scenarios are ideal and only consider a single demand. Therefore, a comprehensive development scenario is set to consider the demands of the above three scenarios and simulate a more realistic development situation. In this scenario, prime cropland is protected, the ecological red line is strictly abided by permanent prime cropland, and the ecological protection red line is used as the restricted conversion area. The priority of ecological protection is set higher than that of cropland protection according to the research of Guo [55]. Considering the needs of regional development, the conversion of cropland, forest land, grassland, and water area to construction land is controlled according to the actual situation.
3.4.2. Neighborhood Weighting Factors
3.4.3. Cost Matrix
4. Results and Analyses
4.1. Analysis of Land Use Change 2000–2020
4.2. Analyses of Land-Use Scenario Modeling
4.2.1. Multi-Scenario Modeling Results
- Multi-scenario land use time change
- 2.
- Multi-scenario land use spatial change
4.2.2. Analysis of Carbon Stock Changes under Multiple Scenarios
5. Discussion
- Exploring Land Use and Multi-Objective Coordination Pathways in Lintao County under Multi-Scenario Simulation
- 2.
- Land sustainable development strategy in Lintao County under multi-objective coordination
- 3.
- Deficiency and prospect
6. Conclusions
- From 2000 to 2020, the transformation of land use in Lintao County will show the strongest motivation for the growth of construction land, with the scale of urban land and other construction land continuing to grow rapidly. The growth of land for rural settlement areas is relatively slow, while cropland and water areas continue to decrease, and forest land grows slowly. The increase in construction land is dominated by an increase in urban land and other construction land, whereas the increase in rural settlement area is slow and is also shifting to urban land and other construction land. The primary encroachment of construction land expansion is on cropland; among them, encroachment on general cropland is the main one, and the change in general cropland is more significant than that in sloping cropland. Spatially, except for other construction land, the intensity of change in other land-use types was greater in river townships than in mountain townships. River townships are dominated by an increase in forest land, urban land, rural settlement area, and unused land and a decrease in general cropland and grassland, while mountain townships are dominated by an increase in rural settlement area and other construction land and a decrease in general cropland. The intensity of land use change was greater in river townships than in mountain townships.
- This study sets four different development scenarios, namely, CPS, EPS, EDS, and CDS, which can comprehensively simulate the land-use pattern under the multi-objective development needs of Lintao County. Among them, the CDS is more in line with the coordination of multiple objectives. Under the CDS, forest land, urban land, and other construction land show an increasing trend. The decrease in general cropland, grassland, and rural settlement areas slows, which can make up for the single-objective nature of the single-demand scenario and meet the multi-objective coordination needs of new urbanization, food security, and ecological civilization construction. Regarding temporal and spatial variations, the overall intensity of land use changes in river townships was greater than that in mountain townships under each scenario. The magnitudes of changes in general cropland, urban land, rural settlement areas, and unused land in river townships were greater than those in mountain townships, and the magnitudes of changes in grassland and other construction land in mountain townships were greater than those in river townships. By 2035, urban land and other construction land will still be strong land, with stronger expansion capacity, while general cropland and rural settlement areas will be weak land, sacrificing the expansion of strong land. General cropland is more susceptible to external environmental impacts, and its changes will be more pronounced than those of sloping cropland.
- From the viewpoint of carbon stock change, the carbon stock of Lintao County under all four scenarios in 2035 shows an increasing trend, among which the carbon stock change under the CDS is more reasonable. The CDS takes into account the needs of CPS, EPS, and CDS, and the increase in carbon stock is maintained at a high level, with the increase in carbon stock in construction land and ecological land as the major part and the decrease in carbon stock in cropland slows down compared with other scenarios. The change in carbon stock in various land uses is more moderate, and the development of construction land has been taken into account, while the protection of cropland and ecological land has been taken into account.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Data Type | Data Sources | Data Description |
---|---|---|
Administrative boundaries | RESDC (http://www.resdc.cn (accessed on 6 March 2023)) | County and township administrative boundary data for 2020 |
Land use data | 2000–2020 data, 30 × 30 m | |
Elevation/m | Geospatial data cloud (http://www.gscloud.cn/ (accessed on 10 March 2023)) | 30 × 30 m |
population density | China County Statistical Yearbook (Township Volume) | Persons/km2 |
Gross industrial output | Ten thousand yuan | |
County government | Lintao County Department of Natural Resources | 2020 data |
Formed town halls | 2020 data | |
River vector data | RESDC (http://www.resdc.cn (accessed on 10 March 2023)) | Data on the spatial distribution of tertiary river basins in China in 2020 |
Road data | National Centre for Basic Geographic Information (http://www.ngcc.cn/ (accessed on 10 March 2023)) | 2020 data |
Permanent basic farmland | Lintao County Department of Natural Resources | Vector data |
Ecological conservation red line |
Typology | Above-Ground Carbon Density | Subsurface Carbon Density | Soil Carbon Density | Dead Organic Carbon Density |
---|---|---|---|---|
General cropland | 1.10 | 15.30 | 53.51 | 1.90 |
Sloping cropland | 1.10 | 15.30 | 53.51 | 1.90 |
Forest land | 24.56 | 5.88 | 92.36 | 0.84 |
Grassland | 0.59 | 0.82 | 79.00 | 0.04 |
Water area | 0.60 | 0.00 | 0.00 | 0.00 |
unused land | 0.44 | 0.54 | 21.60 | 0.00 |
Typology | Carbon Pool Composition | Carbon Density |
---|---|---|
Urban land | Building carbon pool, Furniture and book carbon pool, Human carbon pool | 66.67 |
Rural settlement area | Buildings carbon pool, Furniture and books carbon pool, Human and animals carbon pool | 13.21 |
Other construction land | Building carbon pool | 40.10 |
Land Type | GC | SC | FL | GL | WA | UL | RS | OC | UN |
---|---|---|---|---|---|---|---|---|---|
Ratio | 0.2 | 0.01 | 0.1 | 0.3 | 0.4 | 1 | 0.5 | 1 | 0.5 |
GC | SC | FL | GL | WA | UL | RS | OC | UN | ||
---|---|---|---|---|---|---|---|---|---|---|
GC | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | |
SC | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | |
FL | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | |
GL | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | |
CPS | WA | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
UL | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | |
RS | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | |
OC | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | |
UN | 1 | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | |
GC | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | |
SC | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | |
FL | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | |
GL | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | |
EPS | WA | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
UL | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | |
RS | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | |
OC | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | |
UN | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | |
GC | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | |
SC | 0 | 1 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | |
FL | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | |
EDS | GL | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 0 |
WA | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | |
UL | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | |
RS | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | |
OC | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | |
UN | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | |
GC | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | |
SC | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | |
FL | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | |
GL | 1 | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | |
CDS | WA | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
UL | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | |
RS | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | |
OC | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | |
UN | 0 | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 1 |
2000 | 2005 | 2010 | 2015 | 2020 | ||||||
---|---|---|---|---|---|---|---|---|---|---|
Area/ km2 | Percentage/% | Area/ km2 | Percentage/% | Area/ km2 | Percentage/% | Area/ km2 | Percentage/% | Area/ km2 | Percentage/% | |
GC | 732.51 | 25.65 | 726.66 | 25.45 | 726.14 | 25.43 | 722.28 | 25.29 | 710.52 | 24.88 |
SC | 57.57 | 2.02 | 56.39 | 1.97 | 55.99 | 1.96 | 56.09 | 1.96 | 56.59 | 1.98 |
FL | 116.09 | 4.07 | 115.68 | 4.05 | 123.71 | 4.33 | 123.59 | 4.33 | 124.44 | 4.36 |
GL | 1846.91 | 64.68 | 1850.80 | 64.81 | 1839.46 | 64.42 | 1839.35 | 64.41 | 1841.91 | 64.51 |
WA | 30.42 | 1.07 | 30.48 | 1.07 | 30.20 | 1.06 | 30.26 | 1.06 | 26.85 | 0.94 |
UL | 4.33 | 0.15 | 4.83 | 0.17 | 5.83 | 0.20 | 6.49 | 0.23 | 9.14 | 0.32 |
RS | 61.60 | 2.16 | 64.59 | 2.26 | 65.45 | 2.29 | 66.18 | 2.32 | 69.84 | 2.45 |
OC | 1.22 | 0.04 | 1.22 | 0.04 | 1.76 | 0.06 | 5.12 | 0.18 | 5.92 | 0.21 |
UN | 4.90 | 0.17 | 4.89 | 0.17 | 7.00 | 0.24 | 6.19 | 0.22 | 10.11 | 0.35 |
2020/km2 | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
GC | SC | FL | GL | WA | UL | RS | OC | UN | Total | ||
2000/km2 | GC | 669.10 | 0.14 | 3.79 | 31.57 | 1.51 | 3.71 | 17.26 | 3.65 | 1.77 | 732.51 |
SC | 0.13 | 52.07 | 0.23 | 4.85 | 0.04 | 0.00 | 0.14 | 0.05 | 0.06 | 57.57 | |
FL | 1.32 | 0.11 | 109.44 | 4.08 | 0.13 | 0.33 | 0.68 | 0.00 | 0.00 | 116.09 | |
GL | 25.98 | 3.97 | 10.07 | 1799.35 | 0.60 | 0.00 | 2.57 | 0.61 | 3.75 | 1846.91 | |
WA | 3.50 | 0.22 | 0.30 | 0.62 | 24.52 | 0.27 | 0.83 | 0.01 | 0.00 | 30.42 | |
UL | 0.01 | 0.00 | 0.01 | 0.00 | 0.00 | 4.31 | 0.00 | 0.00 | 0.00 | 4.33 | |
RS | 10.14 | 0.08 | 0.58 | 1.43 | 0.05 | 0.52 | 48.32 | 0.43 | 0.01 | 61.60 | |
OC | 0.05 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 1.17 | 0.00 | 1.22 | |
UN | 0.29 | 0.00 | 0.02 | 0.02 | 0.00 | 0.00 | 0.04 | 0.00 | 4.51 | 4.90 | |
Total/km2 | 710.52 | 56.59 | 124.44 | 1841.91 | 26.85 | 9.14 | 69.84 | 5.92 | 10.11 | 2855.32 | |
Land use dynamic degree/% | −0.15 | −0.09 | 0.36 | −0.01 | −0.59 | 5.55 | 0.67 | 19.26 | 5.32 |
GC | SC | FL | GL | WA | UL | RS | OC | UN | ||
---|---|---|---|---|---|---|---|---|---|---|
2020 | Area/km2 | 710.52 | 56.59 | 124.44 | 1841.91 | 26.85 | 9.14 | 69.84 | 5.92 | 10.11 |
CPS | 709.73 | 56.36 | 124.74 | 1840.79 | 26.98 | 10.57 | 68.98 | 7.51 | 9.68 | |
EPS | 700.22 | 56.34 | 126.36 | 1847.73 | 26.92 | 11.23 | 69.26 | 7.51 | 9.75 | |
EDS | 708.69 | 56.30 | 124.75 | 1840.19 | 25.39 | 12.94 | 69.83 | 7.51 | 9.74 | |
CDS | 707.15 | 56.32 | 126.36 | 1841.03 | 26.85 | 11.04 | 69.32 | 7.51 | 9.72 | |
CPS | Rate of change/% (2020 to 2035) | −0.11 | −0.42 | 0.24 | −0.06 | 0.49 | 15.57 | −1.24 | 26.88 | −4.23 |
EPS | −1.45 | −0.43 | 1.54 | 0.32 | 0.24 | 22.86 | −0.83 | 26.88 | −3.61 | |
EDS | −0.26 | −0.52 | 0.25 | −0.09 | −5.46 | 41.50 | −0.02 | 26.88 | −3.69 | |
CDS | −0.47 | −0.48 | 1.54 | −0.05 | 0.00 | 20.79 | −0.74 | 26.88 | −3.86 |
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Luo, Z.; Zheng, W.; Liu, J.; Wang, J.; Bai, X. A Multi-Objective Scenario Study of County Land Use in Loess Hilly Areas: Taking Lintao County as an Example. Sustainability 2024, 16, 3178. https://doi.org/10.3390/su16083178
Luo Z, Zheng W, Liu J, Wang J, Bai X. A Multi-Objective Scenario Study of County Land Use in Loess Hilly Areas: Taking Lintao County as an Example. Sustainability. 2024; 16(8):3178. https://doi.org/10.3390/su16083178
Chicago/Turabian StyleLuo, Zhanfu, Wei Zheng, Juanqin Liu, Jin Wang, and Xue Bai. 2024. "A Multi-Objective Scenario Study of County Land Use in Loess Hilly Areas: Taking Lintao County as an Example" Sustainability 16, no. 8: 3178. https://doi.org/10.3390/su16083178