Dynamic Simulation of Land Use and Habitat Quality Assessment in Baiyangdian Basin Using the SD-PLUS Coupled Model
Abstract
:1. Introduction
2. Data and Methods
2.1. Study Area
2.2. Data Sources
2.3. Models and Methods
2.3.1. LUCC Future Scenario Demand Prediction Based on SD Model
2.3.2. Introduction of InVEST Model
3. Results
3.1. Spatial and Temporal Changes of Land Use from 2000 to 2020
3.2. Spatial and Temporal Characteristics of Habitat Quality from 2000 to 2020
3.3. LUCC Prediction under SSPs Scenario Based on SD-PLUS Coupling Model
3.4. Habitat Quality Prediction Based on SSPs Scenarios
4. Discussion
4.1. Land Use Change Driving Mechanisms
4.2. Causes Analysis of Habitat Quality
4.3. Uncertainties and Implications
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Data Type | Name | Time | Attribute | Sources |
---|---|---|---|---|
Scenario | SSPs | 2010–2050. | Cell point/0.5° | Jiang Tong et al. [24] |
Land Use | CLCD | 2000–2020. | Raster/30 m | Yang and Huang [29] |
Socio-Economic | GDP | 2019 | Grid/1 km | Resources and Environmental Science and Data Center (https://www.resdc.cn) |
Population density | 2020 | Grid/1 km | ||
Statistical Yearbook | 2000–2020. | Statistics | China City Statistical Yearbook, Annual Bulletin of Baoding City | |
Climatic Environmental | Average annual temperature | 2000–2015. | Grid/1 km | Resources and Environmental Science and Data Center (https://www.resdc.cn) |
Average annual precipitation | 2000–2015. | Grid/1 km | ||
Soil type | 1995 | Grid/1 km | ||
Water Level | 2006–2019. | Statistics | Yearbook of Haihe River Basin Hydrological Data | |
Elevation | / | Grid/30 m | Geospatial data Cloud platform (https://www.gscloud.cn) | |
Slope | / | Raster/30 m | Extracted from elevation data | |
Road, Water System | Road network | 2016 | Vector | National Center for Basic Geographic Information (https://www.webmap.cn) |
Water System | 2015 | Vector |
Landscape Type | Actual Area in 2020/km2 | Simulated Area in 2020/km2 | Relative Error/% |
---|---|---|---|
Farmland | 12,675.08 | 12,428.31 | −1.95 |
Woodland | 8484.29 | 8456.03 | −0.33 |
Grassland | 5574.27 | 5786.59 | 3.81 |
Water | 169.67 | 171.00 | 0.78 |
Construction land | 4322.14 | 4378.33 | 1.30 |
Variables | 2020–2030. | 2030–2040. | 2040–2050. | ||||||
---|---|---|---|---|---|---|---|---|---|
SSP1 | SSP2 | SSP5 | SSP1 | SSP2 | SSP5 | SSP1 | SSP2 | SSP5 | |
GDP change rate/% | 4.64 | 4.67 | 4.59 | 2.36 | 2.38 | 2.61 | 1.36 | 1.10 | 1.81 |
Population change rate/‰ | 0.91 | 2.24 | 1.59 | −0.49 | 0.53 | 0.31 | −2.25 | −0.52 | −1.41 |
Threat Factor | Maximum Impact Distance/km | Weights | Type of Decline |
---|---|---|---|
Farmland | 4 | 0.7 | Linear |
Construction land | 8 | 1 | Index |
Railways | 5 | 0.6 | Linear |
Expressways | 3 | 0.6 | Linear |
National highways | 3 | 0.6 | Linear |
Provincial roads | 2 | 0.5 | Linear |
Landscape Types | Habitat Suitability | Susceptibility | |||||
---|---|---|---|---|---|---|---|
Farmland | Construction Land | Railway | Expressways | National Highways | Provincial Roads | ||
Farmland | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Woodland | 1 | 0.5 | 0.7 | 0.75 | 0.7 | 0.7 | 0.6 |
Grassland | 0.7 | 0.6 | 0.65 | 0.5 | 0.3 | 0.3 | 0.2 |
Water | 1 | 0.75 | 0.7 | 0.75 | 0.7 | 0.7 | 0.6 |
Construction land | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Unutilized land | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
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Han, Z.; Li, B.; Han, Z.; Wang, S.; Peng, W.; Liu, X.; Benson, D. Dynamic Simulation of Land Use and Habitat Quality Assessment in Baiyangdian Basin Using the SD-PLUS Coupled Model. Water 2024, 16, 678. https://doi.org/10.3390/w16050678
Han Z, Li B, Han Z, Wang S, Peng W, Liu X, Benson D. Dynamic Simulation of Land Use and Habitat Quality Assessment in Baiyangdian Basin Using the SD-PLUS Coupled Model. Water. 2024; 16(5):678. https://doi.org/10.3390/w16050678
Chicago/Turabian StyleHan, Zhen, Budong Li, Zepeng Han, Shiyan Wang, Wenqi Peng, Xiaobo Liu, and David Benson. 2024. "Dynamic Simulation of Land Use and Habitat Quality Assessment in Baiyangdian Basin Using the SD-PLUS Coupled Model" Water 16, no. 5: 678. https://doi.org/10.3390/w16050678