Identification of Potential Land Use Conflicts in Shandong Province: A New Framework
Abstract
:1. Introduction
2. Study Area and Data Sources
2.1. Study Area
2.2. Data Sources
3. Research Process and Methods
3.1. Conceptual Framework
3.2. Identification of Potential LUC
3.2.1. Developing Multi-Criteria Evaluation System
Evaluation of LUMS
- (1)
- Construction suitability
- (2)
- Evaluation of cultivation suitability
- (3)
- Evaluation of ecological suitability
Evaluation of LRS
Evaluation of DD
3.2.2. Indicator Grading Assignment, Weight Determination, and Multi-Objective Evaluation Model
3.2.3. Classification of Potential LUC
4. Results
4.1. Spatial Distribution Characteristics of LUMS
4.1.1. Construction Suitability
4.1.2. Cultivation Suitability
4.1.3. Ecological Suitability
4.1.4. LUMS
4.2. Spatial Distribution Characteristics of LRS
4.2.1. Construction Land Scarcity
4.2.2. Cultivated Land Scarcity
4.2.3. Ecological Land Scarcity
4.2.4. LRS
4.3. Spatial Distribution Characteristics of DD
4.3.1. Diversity of Human Demands
4.3.2. Diversity of Wildlife Demands
4.3.3. DD
4.4. Results of Potential LUC Identification
4.4.1. Spatial Distribution of Potential LUC
4.4.2. Current Land Use Types under Different Potential LUC Intensities
4.5. Governance Strategy of LUC Based on Inducement
5. Discussion
5.1. Land Use Implications
- (1)
- Pay attention to tapping potential reserves and improve the efficiency of construction land
- (2)
- Strengthen cultivated land “quantity, quality, and ecology” trinity protection
- (3)
- Adhere to “bottom line” thinking and protect ecological land
5.2. Advantages, Application Scope, and Limitations of the Proposed New Framework and Future Work
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Category | Datasets | Resolution | Data Sources |
---|---|---|---|
Geospatial data | DEM | 90 × 90 m | Geospatial data Cloud (http://www.gscloud.cn, accessed on 9 April 2022) |
Geological hazard susceptibility map | Vector | Shandong provincial geological environment monitoring station | |
Land use data of 2020 | 1000 × 1000 m | Resources and Environmental Science and Data Center (https://www.resdc.cn, accessed on 2 May 2022) | |
Rainfall of 2020 | 1000 × 1000 m | Resources and Environmental Science and Data Center (https://www.resdc.cn, accessed on 2 May 2022) | |
Surface soil texture | 1000 × 1000 m | Resources and Environmental Science and Data Center (https://www.resdc.cn, accessed on 2 May 2022) | |
Soil thickness | 1000 × 1000 m | National Earth System Science Data Center (http://www.geodata.cn/index.html, accessed on 3 May 2022) | |
NDVI of 2020 | 100 × 100 m | Resources and Environmental Science and Data Center (https://www.resdc.cn, accessed on2 May 2022) | |
NPP of 2020 | 1000 × 1000 m | Resources and Environmental Science and Data Center (https://www.resdc.cn, accessed on 2 May 2022) | |
Social and economic statistics | Total population, urban population, rural population, GDP, per capita disposable income of urban residents, and that of rural residents of each district and county in 2020 | County level | Statistical yearbook of prefecture-level cities of Shandong Province in 2021 |
Factor (Weights) | Indicator | Weights | Indicator Classification and Score | ||||
---|---|---|---|---|---|---|---|
100 | 80 | 60 | 40 | 20 | |||
Natural conditions (0.6) | DEM (m) | 0.40 | <50 | 50–70 | 70–163 | 163–291 | >291 |
Slope (°) | 0.15 | <2 | 2–6 | 6–15 | 15–25 | >25 | |
Susceptibility to geological hazards | 0.45 | None | — | Low | Medium | High | |
Location conditions (0.4) | Distance to town (km) | 0.75 | <1.5 | 1.5–3.0 | 3.0–5.0 | 5.0–8.0 | >8.0 |
Distance to main road (km) | 0.25 | <1 | 1–2 | 2–4 | 4–6 | >6 |
Factor (Weight) | Indicator | Weight | Indicator Classification and Score | ||||
---|---|---|---|---|---|---|---|
100 | 80 | 60 | 40 | 20 | |||
Natural endowment (0.75) | DME (m) | 0.3473 | <50 | 50–70 | 70–163 | 163–291 | >291 |
Slope (°) | 0.1213 | <2 | 2–6 | 6–15 | 15–25 | >25 | |
Rainfall | 0.1285 | >679.89 | 609.75–679.89 | 535.35–609.75 | 454.57–535.35 | <454.57 | |
Surface soil texture | 0.2427 | Silt loam | Loam | Silty clay loam | Clay loam; sandy loam | Silt | |
Soil thickness | 0.1601 | >162 | 140–162 | 115–140 | 90–115 | <90 | |
Cultivation convenience (0.25) | Distance to rural settlement (km) | 0.6667 | <1 | 1–2 | 2–3 | 3–4 | >4 |
Distance to road of town and village | 0.3333 | <1 | 1–2 | 2–3 | 3–4 | >4 |
Factor (Weight) | Indicator | Weight | Indicator Classification and Score | ||||
---|---|---|---|---|---|---|---|
100 | 80 | 60 | 40 | 20 | |||
Natural endowment (0.3) | NDVI | 0.6667 | >0.76 | 0.65–0.76 | 0.49–0.65 | 0.23–0.49 | <0.23 |
Rainfall (mm) | 0.3333 | >679.89 | 609.75–679.89 | 535.35–609.75 | 454.57–535.35 | <454.57 | |
Human disturbance (0.7) | Distance to town | 0.2761 | >10 | 8–10 | 5–8 | 3–5 | <3 |
Distance to rural settlement | 0.1953 | >4 | 3–4 | 2–3 | 1–2 | <1 | |
Distance to road | 0.1381 | >5 | 3–5 | 2–3 | 1–2 | <1 | |
Land use type | 0.3905 | Water; forest; grassland; wetland | Cultivated land; unused land | Construction land |
Factor | Indicator | Indicator Classification and Score | ||||
---|---|---|---|---|---|---|
100 | 80 | 60 | 40 | 20 | ||
Construction land scarcity (0.2) | Per capita urban land area (0.6667) | <90.06 | 90.06–151.82 | 151.82–245.12 | 245.12–383.20 | >383.20 |
Per capita rural settlement area (0.3333) | <125.5 | 125.5–234.9 | 234.9–347.4 | 234.9–520 | >520 | |
Cultivated land scarcity (0.4) | Per capita cultivated land area | <333.95 | 333.95–930.24 | 930.24–1468.03 | 1468.03–2845.16 | >2845.16 |
Ecological land scarcity (0.4) | Per capita forest land area (0.3333) | <45.52 | 45.52–172.11 | 172.11–320.42 | 320.42–533.27 | >533.27 |
Per capita grassland area (0.3333) | <38.15 | 38.15–119.48 | 119.48–249.06 | 249.06–419.51 | >419.51 | |
Per capita water area (0.3333) | <41.52 | 41.52–110.19 | 110.19–296.19 | 296.19–625.94 | >625.94 |
Factor | Indicator | Indicator Classification and Score | ||||
---|---|---|---|---|---|---|
100 | 80 | 60 | 40 | 20 | ||
Human demands (0.5) | Total population (0.2310) | >111.2 | 74.00–111.2 | 58.50–74.00 | 40.40–58.50 | <40.40 |
GDP (0.4901) | >1100.89 | 640.17–1100.89 | 432.70–640.17 | 268.96–432.70 | <268.96 | |
Per capita disposable income of urban residents (0.1634) | >37,118 | 32,032–37,118 | 26,529–32,032 | 21,920–26,529 | <21,920 | |
Per capita disposable income of farmers (0.1155) | >16,447 | 14,297–16,447 | 12,209–14,297 | 10,721–12,209 | <10,721 | |
Wildlife demands (0.5) | Biodiversity index |
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Dong, G.; Sun, Z.; Li, W.; Wang, K.; Yuan, C. Identification of Potential Land Use Conflicts in Shandong Province: A New Framework. Land 2024, 13, 1203. https://doi.org/10.3390/land13081203
Dong G, Sun Z, Li W, Wang K, Yuan C. Identification of Potential Land Use Conflicts in Shandong Province: A New Framework. Land. 2024; 13(8):1203. https://doi.org/10.3390/land13081203
Chicago/Turabian StyleDong, Guanglong, Zengyu Sun, Wei Li, Keqiang Wang, and Chenzhao Yuan. 2024. "Identification of Potential Land Use Conflicts in Shandong Province: A New Framework" Land 13, no. 8: 1203. https://doi.org/10.3390/land13081203