Analysis of Landscape Patterns of Arid Valleys in China, Based on Grain Size Effect
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Methods
2.2.1. Sample Selection
2.2.2. Choice of Landscape Metrics and Grain Size
3. Results
3.1. Impact of Landscape Metrics
3.1.1. Landscape Level
Grain Size Response Curve
Curve Fitting
3.1.2. Class Level
Grain-Size Response Curve
Curve Fitting
3.2. Landscape Pattern
3.2.1. Landscape Level
3.2.2. Class Level
4. Discussion
4.1. Impact of Grain Size on Landscape Metrics
4.2. Landscape Pattern
5. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Basin Attributes | Area (km2) | The Length of River (km) | The Length of Boundary (km) | Mean DEM (m) | Mean Slope (°) |
---|---|---|---|---|---|
Dadu River | 1202.11 | 229.23 | 2845.23 | 2387.66 | 29.31 |
Yuanjiang | 1378.76 | 187.50 | 1357.49 | 807.456 | 19.41 |
Minjiang | 1489.17 | 404.41 | 3330.44 | 2377.56 | 30.46 |
Anning River | 2693.62 | 677.71 | 2781.95 | 1649.52 | 15.10 |
Yalong River | 3347.99 | 340.33 | 5734.65 | 2177.29 | 27.89 |
Lancang River | 3457.13 | 586.16 | 4197.94 | 2572.87 | 29.68 |
Nujiang | 4100.81 | 730.54 | 3312.10 | 2264.63 | 29.13 |
Jinsha River | 15,390.53 | 2438.28 | 15,844.28 | 1927.06 | 25.58 |
Metrics | Name | Description |
---|---|---|
Area and Edge metrics | Total Area (TA) | The area of the landscape |
Largest Patch Index (LPI) | The proportion of the largest patch area | |
Shape metrics | Perimeter-Area Fractal Dimension (PAFRAC) | Non-randomness or degree of aggregation for different patches |
Fractal Index Distribution (FRAC_MN) | The shape complexity of patches, which approaches 1 for shapes with simple perimeters and 2 for complex shapes | |
Aggregation metrics | Number of Patches (NP) | The number of patches |
Patch Density (PD) | Number of patches per unit area | |
Splitting Index (SPLIT) | The number of patches of a landscape divided into equal sizes keeping landscape division constant, express the separation degree of individual distribution in different | |
Interspersion and Juxtaposition Index (IJI) | The measurement of evenness of patch adjacencies and the degree of intermixing of patch types | |
Aggregation Index (AI) | The degree of aggregation of similar patches | |
Landscape Shape Index (LSI) | The continuity and complex of landscape shape and the measurement of the perimeter-to-area ratio for the landscape as a whole. | |
Diversity metrics | Shannon’s Diversity Index (SHDI) | Uncertainties and landscape heterogeneity of patches |
Shannon’s Evenness Index (SHEI) | The degree of evenness of each patch in the area, which only consider the evenness of patch sizes, not the number of patches |
Metrics | js2 | mj | yj | |||
---|---|---|---|---|---|---|
Curve Fitting | R2 | Curve Fitting | R2 | Curve Fitting | R2 | |
TA | ||||||
LPI | S function | 0.870 | S function | 0.790 | Cubic function | 0.746 |
PAFRAC | Log function | 0.994 | Log function | 0.991 | Log function | 0.972 |
FRAC_MN | Cubic function | 0.987 | Cubic function | 0.991 | Cubic function | 0.988 |
NP | Exp function | 0.989 | Exp function | 0.987 | Exp function | 0.990 |
PD | Exp function | 0.989 | Exp function | 0.987 | Exp function | 0.990 |
SPLIT | S FUNCTION | 0.894 | S FUNCTION | 0.827 | S FUNCTION | 0.683 |
IJI | Cubic function | 0.933 | Cubic function | 0.751 | Cubic function | 0.897 |
AI | Cubic function | 0.999 | Cubic function | 0.998 | Cubic function | 0.998 |
LSI | Cubic function | 0.999 | Cubic function | 0.998 | Cubic function | 0.998 |
SHDI | ||||||
SHEI |
Metrics | First Scale Domain | The Appropriate Grain Size |
---|---|---|
TA | The smaller, the better | |
LPI | 30–90 m | 45–75 m |
PAFRAC | 30–210 m | 45–195 m |
NP | 60–105 m | 75–90 m |
PD | 60–105 m | 75–90 m |
SPLIT | 30–90 m | 45–75 m |
IJI | 60–180 m | 75–125 m |
AI | 45–240 m | 60–210 m |
LSI | 45–105 m | 60–135 m |
SHDI | <195 m | |
SHEI | <195 m | |
All | 60–90 m | 75 m |
Metrics | js2 | mj | yj | ||||
---|---|---|---|---|---|---|---|
Patch | Curve Fitting | R2 | Curve Fitting | R2 | Curve Fitting | R2 | |
PLAND | Forest | ||||||
Shrub | |||||||
Grass | |||||||
Water | |||||||
Farmland | |||||||
Settlement | |||||||
Unused land | |||||||
NP | Forest | Cubic function | 0.995 | Cubic function | 0.997 | Cubic function | 0.992 |
Shrub | Cubic function | 0.995 | Cubic function | 0.984 | Cubic function | 0.995 | |
Grass | Cubic function | 0.991 | Cubic function | 0.994 | Cubic function | 0.990 | |
Water | Cubic function | 0.518 | Cubic function | 0.490 | Cubic function | 0.399 | |
Farmland | Cubic function | 0.984 | Cubic function | 0.996 | Cubic function | 0.996 | |
Settlement | Cubic function | 0.950 | Cubic function | 0.985 | Cubic function | 0.977 | |
Unused land | Cubic function | 0.996 | Cubic function | 0.990 | Cubic function | 0.987 | |
PD | Forest | Cubic function | 0.995 | Cubic function | 0.997 | Cubic function | 0.992 |
Shrub | Cubic function | 0.995 | Cubic function | 0.984 | Cubic function | 0.995 | |
Grass | Cubic function | 0.991 | Cubic function | 0.994 | Cubic function | 0.990 | |
Water | Cubic function | 0.519 | Cubic function | 0.490 | Cubic function | 0.400 | |
Farmland | Cubic function | 0.984 | Cubic function | 0.996 | Cubic function | 0.996 | |
Settlement | Cubic function | 0.950 | Cubic function | 0.985 | Cubic function | 0.977 | |
Unused land | Cubic function | 0.996 | Cubic function | 0.990 | Cubic function | 0.987 | |
LPI | Forest | S FUNCTION | 0.708 | Cubic function | 0.609 | Cubic function | 0.484 |
Shrub | S FUNCTION | 0.458 | Cubic function | 0.487 | Cubic function | 0.524 | |
Grass | Exp function | 0.547 | S FUNCTION | 0.499 | S FUNCTION | 0.551 | |
Water | Power function | 0.909 | S FUNCTION | 0.408 | Exp function | 0.541 | |
Farmland | Cubic function | 0.526 | Cubic function | 0.500 | Cubic function | 0.817 | |
Settlement | Cubic function | 0.471 | Cubic function | 0.477 | Cubic function | 0.281 | |
Unused land | Cubic function | 0.585 | Cubic function | 0.484 | Cubic function | 0.773 | |
PAFRAC | Forest | Power function | 0.987 | Power function | 0.934 | Power function | 0.951 |
Shrub | Power function | 0.995 | Power function | 0.974 | Power function | 0.966 | |
Grass | Power function | 0.969 | Power function | 0.973 | Power function | 0.958 | |
Water | Cubic function | 0.830 | Cubic function | 0.346 | Cubic function | 0.503 | |
Farmland | Power function | 0.951 | Power function | 0.954 | Power function | 0.961 | |
Settlement | Cubic function | 0.376 | Cubic function | 0.562 | Cubic function | 0.937 | |
Unused land | Power function | 0.733 | Power function | 0.821 | Cubic function | 0.338 | |
AI | Forest | Exp function | 0.984 | Exp function | 0.988 | Exp function | 0.987 |
Shrub | Exp function | 0.984 | Exp function | 0.992 | Exp function | 0.988 | |
Grass | Cubic function | 0.997 | Cubic function | 0.998 | Exp function | 0.989 | |
Water | Exp function | 0.981 | Exp function | 0.963 | Exp function | 0.947 | |
Farmland | Cubic function | 0.998 | Cubic function | 0.998 | Exp function | 0.989 | |
Settlement | Exp function | 0.978 | Exp function | 0.980 | Exp function | 0.983 | |
Unused land | Exp function | 0.988 | Exp function | 0.988 | Exp function | 0.969 |
Metrics | Basin | First Scale Domain | The Appropriate Grain Size |
---|---|---|---|
PLAND | js2 | The smaller, the better | |
mj | <125 m | ||
yj | <135 m | ||
NP | js2 | 60–135 m | 75–125 m |
mj | 60–135 m | 75–125 m | |
yj | 60–135 m | 75–125 m | |
PD | js2 | 45–195 m | 60–180 m |
mj | 45–195 m | 60–180 m | |
yj | 45–195 m | 60–180 m | |
LPI | js2 | <150 m | |
mj | <150 m | ||
yj | <120 m | ||
PAFRAC | js2 | 45–135 m | 60–120 m |
mj | 45–150 m | 60–135 m | |
yj | 45–165 m | 60–150 m | |
AI | js2 | 60–120 m | 75–105 m |
mj | 45–180 m | 60–165 m | |
yj | 60–195 m | 75–180 m | |
All | 60–135 m | 75 m |
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Fang, S.; Zhao, Y.; Han, L.; Ma, C. Analysis of Landscape Patterns of Arid Valleys in China, Based on Grain Size Effect. Sustainability 2017, 9, 2263. https://doi.org/10.3390/su9122263
Fang S, Zhao Y, Han L, Ma C. Analysis of Landscape Patterns of Arid Valleys in China, Based on Grain Size Effect. Sustainability. 2017; 9(12):2263. https://doi.org/10.3390/su9122263
Chicago/Turabian StyleFang, Shu, Yonghua Zhao, Lei Han, and Chaoqun Ma. 2017. "Analysis of Landscape Patterns of Arid Valleys in China, Based on Grain Size Effect" Sustainability 9, no. 12: 2263. https://doi.org/10.3390/su9122263
APA StyleFang, S., Zhao, Y., Han, L., & Ma, C. (2017). Analysis of Landscape Patterns of Arid Valleys in China, Based on Grain Size Effect. Sustainability, 9(12), 2263. https://doi.org/10.3390/su9122263