Spatial–Temporal Change in Paddy Field and Dryland in Different Topographic Gradients: A Case Study of China during 1990–2020
Abstract
:1. Introduction
2. Research Methods and Data Source
2.1. Data Sources
2.2. The Identification of the Topographic Conditions of Paddy field and Dryland
2.3. The Transformation between Paddy Field and Dryland
2.4. The Landscape Characteristics of Paddy Field and Dryland
2.5. Topographic Potential Index
3. Result Analysis
3.1. Changes in the Topographic Characteristics of Paddy Field and Dryland
3.2. The Land Conversion of Paddy Field, Dryland, and Other Land
3.3. Land-Type Change in Paddy Field and Dryland under Different Topographic Conditions
3.3.1. Land-Type Change in Paddy Field and Dryland at Different Elevations
3.3.2. Land-Type Change in Paddy Field and Dryland at Different Slopes
3.3.3. Land-Type Change in Paddy Field and Dryland on Different Slope Aspects
3.4. The Landscape Characteristics of Paddy Field and Dryland under Different Topographic Conditions
4. Discussion
4.1. Changes in Microterrain Factors Led to a Decrease in Paddy Field and Dryland with Good Photothermal Conditions
4.2. In Addition to the “Third Ladder”, the Changes in Paddy Field and Dryland Have Become Active on the “Second Ladder” of China
4.3. Increased Paddy Field and Dryland on Slopes Exacerbated the Erosion Risk
4.4. The Landscape Fragmentation of Paddy Field and Dryland Emphasize the Importance of Land Consolidation
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Grid Value | Implication | Grid Value | Implication |
---|---|---|---|
11 | Unchanged paddy field | 22 | Unchanged dryland |
12 | Paddy field→Dryland | 21 | Dryland→Paddy field |
13 | Paddy field→Other land | 23 | Dryland→Other land |
31 | Other land→Paddy field | 32 | Other land→Dryland |
Categories | Indexes | Title | Introduction |
---|---|---|---|
Intensity | NP | Number of patches | NP is the total number of all patches in the landscape, which can reflect the landscape spatial pattern. |
PD | Patch density | PD is the number of patches per unit area. | |
LPI | Largest patch index (%) | LPI is the proportion of the largest patch of a land-use type in the whole landscape, which is used to measure the characteristics of the dominant landscape patches. | |
Shape | LSI | Landscape shape index | LSI is the shape complexity of arable land patches, which was measured by the deviation of the shape of the land patch from a circle or a square of the same area. |
AWMSI | Area-weighted mean shape index | AWMSI is the sum of the average shape factor of each land patch multiplied by the weight (the land patch area in the total landscape area). Bigger landscape patches have a higher weight than smaller patches. | |
Vergence | AI | Aggregation index (%) | AI refers to the aggregation degree of the landscape based on the common boundary length of patches of the same type of landscape. |
DIVISION | Landscape isolation | DIVISION refers to the individual isolated distribution of different patches in the landscape types. | |
SPLIT | Splitting Index | SPLIT refers to the ratio of landscape fragmentation to the total landscape area index, which is used to describe the dispersion of the landscape pattern. |
Category | Index | 1990 | 1995 | 2000 | 2005 | 2010 | 2015 | 2020 |
---|---|---|---|---|---|---|---|---|
Intensity | NP | 63,269 | 62,748 | 63,935 | 64,902 | 65,098 | 65,753 | 64,574 |
PD | 0.1339 | 0.1331 | 0.1349 | 0.1393 | 0.14 | 0.1414 | 0.1405 | |
LPI | 12.55 | 12.23 | 13.65 | 13.80 | 13.70 | 13.46 | 14.23 | |
Shape | LSI | 334.23 | 334.05 | 337.28 | 340.51 | 342.46 | 345.18 | 337.89 |
AWMSI | 14.85 | 15.00 | 16.03 | 15.93 | 15.93 | 15.65 | 16.05 | |
Vergence | AI | 51.44 | 51.39 | 51.06 | 50.15 | 49.85 | 49.44 | 50.23 |
DIVISION | 0.9775 | 0.9789 | 0.9762 | 0.9763 | 0.977 | 0.978 | 0.9776 | |
SPLIT | 44.35 | 47.34 | 42.08 | 42.25 | 43.41 | 45.38 | 44.52 |
Category | Index | 1990 | 1995 | 2000 | 2005 | 2010 | 2015 | 2020 |
---|---|---|---|---|---|---|---|---|
Intensity | NP | 107,926 | 105,567 | 108,719 | 109,163 | 109,796 | 111,141 | 110,920 |
PD | 0.0831 | 0.0822 | 0.082 | 0.0822 | 0.083 | 0.0841 | 0.0839 | |
LPI | 30.69 | 25.04 | 28.64 | 27.98 | 27.90 | 27.02 | 25.19 | |
Shape | LSI | 455.79 | 448.42 | 459.63 | 460.44 | 462.10 | 466.72 | 464.46 |
AWMSI | 56.50 | 51.63 | 59.65 | 57.21 | 57.12 | 56.80 | 57.27 | |
Vergence | AI | 60.06 | 60.46 | 60.13 | 60.07 | 59.86 | 59.44 | 59.65 |
DIVISION | 0.8988 | 0.9256 | 0.9073 | 0.9126 | 0.9132 | 0.9166 | 0.9163 | |
SPLIT | 9.89 | 13.44 | 10.78 | 11.45 | 11.52 | 11.99 | 11.94 |
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Xie, S.; Yin, G.; Wei, W.; Sun, Q.; Zhang, Z. Spatial–Temporal Change in Paddy Field and Dryland in Different Topographic Gradients: A Case Study of China during 1990–2020. Land 2022, 11, 1851. https://doi.org/10.3390/land11101851
Xie S, Yin G, Wei W, Sun Q, Zhang Z. Spatial–Temporal Change in Paddy Field and Dryland in Different Topographic Gradients: A Case Study of China during 1990–2020. Land. 2022; 11(10):1851. https://doi.org/10.3390/land11101851
Chicago/Turabian StyleXie, Shuai, Guanyi Yin, Wei Wei, Qingzhi Sun, and Zhan Zhang. 2022. "Spatial–Temporal Change in Paddy Field and Dryland in Different Topographic Gradients: A Case Study of China during 1990–2020" Land 11, no. 10: 1851. https://doi.org/10.3390/land11101851
APA StyleXie, S., Yin, G., Wei, W., Sun, Q., & Zhang, Z. (2022). Spatial–Temporal Change in Paddy Field and Dryland in Different Topographic Gradients: A Case Study of China during 1990–2020. Land, 11(10), 1851. https://doi.org/10.3390/land11101851