Submitted:
19 August 2024
Posted:
21 August 2024
You are already at the latest version
Abstract
Keywords:
Introduction
1. Study Area and Data Sources
1.1. Description of the Study Area
1.2. Data Source and Processing
2. Research Methods
2.1. Land Use Transfer Matrix
2.2. Simulation of Future Mangrove Land Use Using the PLUS Model
3. Results and Analysis
3.1. Land Use Characterization
3.2. Analysis of Land Use Change
3.3. Contribution of Drivers of Land Use Expansion by Land Use Type
3.4. Multi-Scenario Projections of Mangrove Distribution Patterns
3.4.1. Natural Development Scenario
3.4.2. Urban Development Scenario
3.4.3. Ecological Protection Scenario
4. Conclusions
- (1)
- The study area is located in Yalong Bay, Sanya City, and its land use changes are more closely related to regional development and construction. Before 2015, development and construction in the area developed on a large scale, with rapid growth in building and transportation land, and a significant decrease in cropland, parkland, and arbor forest land, etc. After 2015, the intensity of development and construction was significantly reduced, and the changes in land types, such as building land, transportation land, cropland, and parkland, were slowed down significantly. During this period, the area of mangrove land continued to increase, indicating that the protection and restoration of mangrove land during this period was mainly influenced by wetland protection policies, and that progress was made in the protection of mangrove wetland resources.
- (2)
- The analysis of land use expansion drivers from 2009-2022 using the PLUS model shows that the main influencing factor for expansion of each category is elevation, especially in the mangrove land, river and lagoon of the natural land category of the main driving factor, in addition, the distance from the building is also an important factor affecting the expansion of the area of artificial land such as unutilized land, building land, cropland, parkland, and grassland, etc.
- (3)
- The PLUS model was used to simulate and predict the land use types under the three scenarios of Qingmei Harbor in 2035, and the results showed that there was no significant increase in the mangrove area under all three scenarios, with the highest percentage of area under the urban development scenario. The largest increase in area was in the urban development scenario for building land, unutilized land, and parkland. The ecological protection scenario shows a significant increase in the area of natural land categories such as arbor forest land and river and lagoon.
- (4)
- The growth of mangrove area in Qingmei Harbor is mainly due to the government's policy of protecting and restoring mangrove wetland resources in recent years, and at present, this area has basically completed the “returning ponds to wetlands”, subject to the influence of the natural environmental conditions, it is difficult to expand the mangrove area in Qingmei Harbor in the future, and the focus of the subsequent work should be shifted to improving and transforming the quality and function of the mangrove ecosystem.
5. Discussion
Funding
References
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| cropland | parkland | aquaculture pond, | pit pond | river and lagoon | building land | Unutilized land | grassland | mangrove land | transportation land | Arbor forest land | ||
| natural development scenario | cropland | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 |
| parkland | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | |
| aquaculture pond | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | |
| pit pond | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| river and lagoon | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | |
| building land | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | |
| Unutilized land | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | |
| grassland | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | |
| mangrove land | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | |
| transportation land | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | |
| Arbor forest land | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | |
| urban development scenario | cropland | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| parkland | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | |
| aquaculture pond | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | |
| pit pond | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| river and lagoon | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | |
| building land | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | |
| Unutilized land | 0 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 0 | |
| grassland | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | |
| mangrove land | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | |
| transportation land | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | |
| Arbor forest land | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | |
| ecological protection scenario | cropland | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 1 | 1 |
| parkland | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 1 | |
| aquaculture pond | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | |
| pit pond | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | |
| river and lagoon | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | |
| building land | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | |
| Unutilized land | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | |
| grassland | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | |
| mangrove land | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | |
| transportation land | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | |
| arbor forest land | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 |
| Landscape Types | 2009 | 2015 | 2022 | |||
| area(ha) | Proportion(%) | area(ha) | Proportion(%) | area(ha) | Proportion(%) | |
| Cropland |
26.89 | 3.40 | 7.00 | 0.88 | 0.40 | 0.05 |
| Parkland |
92.55 | 11.69 | 56.25 | 7.11 | 59.47 | 7.51 |
| Aquaculture pond |
1.19 | 0.15 | 0.40 | 0.05 | 0.00 | 0.00 |
| Pit pond |
6.49 | 0.82 | 11.05 | 1.40 | 10.92 | 1.38 |
| River and lagoon |
27.83 | 3.52 | 24.67 | 3.12 | 34.82 | 4.40 |
| Building land |
104.83 | 13.25 | 186.93 | 23.62 | 184.20 | 23.27 |
| Unutilized land |
58.80 | 7.43 | 42.41 | 5.36 | 28.11 | 3.55 |
| Grassland |
52.36 | 6.62 | 51.94 | 6.56 | 52.63 | 6.65 |
| Mangrove land |
45.49 | 5.75 | 54.51 | 6.89 | 65.26 | 8.25 |
| Transportation land |
27.30 | 3.45 | 32.42 | 4.10 | 32.42 | 4.10 |
| Arbor forest land |
347.72 | 43.93 | 323.86 | 40.92 | 323.60 | 40.89 |
| Landscape Types | 2009-2015 | 2015-2022 | 2009-2022 | |||
| Change area(ha) | Dynamic Degree(%) |
Change area(ha) | Dynamic Degree(%) |
Change area(ha) | Dynamic Degree(%) |
|
| Cropland |
-15.54 | -73.97 | -5.16 | -94.33 | -20.70 | -98.52 |
| Parkland |
-28.36 | -39.22 | 2.51 | 5.72 | -25.85 | -35.75 |
| Aquaculture pond |
-0.62 | -66.40 | -0.31 | -100.00 | -0.93 | -100.00 |
| Pit pond |
3.56 | 70.25 | -0.11 | -1.22 | 3.46 | 68.17 |
| River and lagoon |
-2.47 | -11.34 | 7.93 | 41.14 | 5.46 | 25.13 |
| Building land |
64.14 | 78.32 | -2.13 | -1.46 | 62.01 | 75.71 |
| Unutilized land |
-12.81 | -27.88 | -11.17 | -33.72 | -23.98 | -52.20 |
| Grassland |
-0.33 | -0.80 | 0.53 | 1.32 | 0.21 | 0.51 |
| Mangrove land |
7.04 | 19.82 | 8.40 | 19.74 | 15.45 | 43.47 |
| Transportation land |
4.01 | 18.78 | 0.00 | 0.00 | 4.01 | 18.78 |
| Arbor forest land |
-18.63 | -6.86 | -0.21 | -0.08 | -18.84 | -6.94 |
| Land use type | Natural development scenario | Urban development scenario | Ecological protection scenario | |||
| percentage (%) | area (ha) | percentage (%) | area (ha) | percentage (%) | area (ha) | |
| Cropland | 3.04 | 30.22 | 0.70 | 6.97 | 3.03 | 30.10 |
| Parkland | 11.20 | 111.35 | 9.74 | 96.79 | 16.45 | 163.56 |
| Aquaculture pond | 0.02 | 0.25 | 0.02 | 0.25 | 0.11 | 1.06 |
| Pit pond | 0.79 | 7.83 | 0.84 | 8.34 | 0.72 | 7.16 |
| River and lagoon | 2.66 | 26.47 | 2.66 | 26.47 | 3.05 | 30.30 |
| Building land | 16.81 | 167.07 | 21.52 | 213.90 | 11.88 | 118.11 |
| Unutilized land | 10.04 | 99.78 | 11.69 | 116.20 | 9.42 | 93.69 |
| Grassland | 6.05 | 60.14 | 6.39 | 63.50 | 5.81 | 57.72 |
| Mangrove land | 5.77 | 57.35 | 6.27 | 62.33 | 5.23 | 51.95 |
| Transportation land | 2.68 | 26.62 | 1.44 | 14.27 | 2.26 | 22.49 |
| Arbor forest land | 40.95 | 407.09 | 38.74 | 385.16 | 42.05 | 418.04 |
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