Geospatial Analysis of Mass-Wasting Susceptibility of Four Small Catchments in Mountainous Area of Miyun County, Beijing
Abstract
:1. Introduction
2. Study area and Inventory Maps
2.1. Identifying Locations of Mass-Wasting Inventory
2.2. Influence Factors
3. Methodology
3.1. Frequency Ratio
3.2. Information Value Model
4. Results
4.1. Mass-Wasting Susceptibility Mapping Using the FR Model
4.2. Mass-Wasting Susceptibility Mapping Using the IV Model
4.3. Validation of Mass-Wasting Susceptibility Mapping
5. Discussion
6. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Influence Factors | Data Sources |
---|---|
Elevation | Generated using GIS from a digital elevation model with a resolution of 5 m |
Slope angle | |
Curvature | |
Stream power index | |
Topographic wetness index Flow accumulation | |
Lithology | Obtained from a geological map with a scale of 1:10,000 |
Land use | Google Earth image on May 3, 2014, and field survey |
Soil type | Distribution of soil type map in Miyun County with a scale of 1:10,000 |
Parameter | Subclass | Mass-Wasting did not Occur | Mass-Wasting Occurred | Total Count | FR | IVM | ||
---|---|---|---|---|---|---|---|---|
Count | Ratio (%) | Count | Ratio (%) | |||||
Elevation (m) | 610–691 | 36,676 | 9.00 | 3 | 6 | 36,679 | 0.667 | −0.405 |
691–749 | 60,610 | 14.87 | 16 | 32 | 60,626 | 2.152 | 0.766 | |
749–799 | 69,605 | 17.08 | 11 | 22 | 69,616 | 1.288 | 0.253 | |
799–846 | 69,408 | 17.03 | 11 | 22 | 69,419 | 1.292 | 0.256 | |
846–891 | 56,444 | 13.85 | 5 | 10 | 56,449 | 0.722 | −0.325 | |
891–935 | 45,554 | 11.17 | 3 | 6 | 45,557 | 0.537 | −0.622 | |
935–980 | 34,307 | 8.41 | 0 | 0 | 34,307 | 0.000 | −1.000 | |
980–1030 | 20,916 | 5.13 | 0 | 0 | 20,916 | 0.000 | −1.000 | |
1030–1103 | 10,049 | 2.47 | 1 | 2 | 10,050 | 0.811 | −0.209 | |
1103–1280 | 4070 | 1.00 | 0 | 0 | 4070 | 0.000 | −1.000 | |
Slope angle (°) | 0–6 | 192,418 | 7.64 | 6 | 12 | 31,160 | 1.570 | 0.451 |
6–14 | 28,252 | 8.43 | 7 | 14 | 34,386 | 1.660 | 0.507 | |
14–21 | 186,969 | 9.16 | 12 | 24 | 37,324 | 2.622 | 0.964 | |
21–27 | 192,418 | 12.55 | 7 | 14 | 51,185 | 1.115 | 0.109 | |
27–31 | 28,252 | 16.58 | 9 | 18 | 67,590 | 1.086 | 0.082 | |
31–35 | 186,969 | 17.15 | 4 | 8 | 69,915 | 0.467 | −0.763 | |
35–39 | 192,418 | 14.19 | 3 | 6 | 57,838 | 0.423 | −0.861 | |
39–44 | 28,252 | 9.16 | 1 | 2 | 37,329 | 0.218 | −1.521 | |
44–50 | 186,969 | 4.19 | 1 | 2 | 17,075 | 0.478 | −0.739 | |
50–73 | 192,418 | 0.95 | 0 | 0 | 3887 | 0.000 | −1.000 | |
Curvature | Concave | 192,418 | 47.21 | 32 | 64 | 192,450 | 1.356 | 0.304 |
Flat | 28,252 | 6.93 | 6 | 12 | 28,258 | 1.731 | 0.549 | |
Convex | 186,969 | 45.86 | 12 | 24 | 186,981 | 0.523 | −0.648 | |
SPI | 0–2.57 | 65,867 | 16.16 | 3 | 6 | 65,870 | 0.371 | −0.991 |
2.57–6.21 | 169,540 | 41.59 | 12 | 24 | 169,552 | 0.577 | −0.550 | |
6.21–8.99 | 90,167 | 22.12 | 15 | 30 | 90,182 | 1.356 | 0.305 | |
8.99–11.12 | 35,453 | 8.70 | 13 | 26 | 35,466 | 2.989 | 1.095 | |
11.12–13.05 | 17,690 | 4.34 | 2 | 4 | 17,692 | 0.922 | −0.082 | |
13.05–15.19 | 6509 | 1.60 | 1 | 2 | 6510 | 1.253 | 0.225 | |
15.19–17.97 | 3284 | 0.81 | 1 | 2 | 3285 | 2.482 | 0.909 | |
17.97–22.04 | 1300 | 0.32 | 0 | 0 | 1300 | 0.000 | −1.000 | |
22.04–29.52 | 265 | 0.07 | 0 | 0 | 265 | 0.000 | −1.000 | |
29.52–54.55 | 17,564 | 4.31 | 3 | 6 | 17,567 | 1.393 | 0.331 | |
TWI | 0–3.03 | 43,441 | 10.66 | 7 | 14 | 43,448 | 1.314 | 0.273 |
3.03–3.43 | 57,290 | 14.06 | 18 | 36 | 57,308 | 2.561 | 0.940 | |
3.43–3.97 | 78,098 | 19.16 | 10 | 20 | 78,108 | 1.044 | 0.043 | |
3.97–4.58 | 89,843 | 22.04 | 9 | 18 | 89,852 | 0.817 | −0.203 | |
4.56–5.32 | 68,776 | 16.87 | 3 | 6 | 68,779 | 0.356 | −1.034 | |
5.32–6.33 | 41,754 | 10.24 | 2 | 4 | 41,756 | 0.391 | −0.940 | |
6.37–7.56 | 19,873 | 4.87 | 0 | 0 | 19,873 | 0.000 | −1.000 | |
7.56–9.38 | 6523 | 1.60 | 1 | 2 | 6524 | 1.250 | 0.223 | |
9.38–14.44 | 1768 | 0.43 | 0 | 0 | 1768 | 0.000 | −1.000 | |
14.44–18.83 | 273 | 0.07 | 0 | 0 | 273 | 0.000 | −1.000 | |
Lithology | Gneiss | 65,480 | 16.06 | 7 | 14 | 65,493 | 1.619 | 0.482 |
Quartzite | 199,298 | 48.89 | 18 | 36 | 199,324 | 1.064 | 0.062 | |
Diorite | 91,377 | 22.42 | 10 | 20 | 91,387 | 0.892 | −0.114 | |
Acid rock | 29,299 | 7.19 | 9 | 18 | 29,300 | 0.278 | −1.279 | |
Granite | 22,143 | 5.43 | 3 | 6 | 22,143 | 0.000 | −1.000 | |
Land use | Construction | 8367 | 2.05 | 0 | 0 | 8373 | 0.000 | −1.000 |
Farmland | 26,505 | 6.50 | 6 | 12 | 26,505 | 1.846 | 0.613 | |
Forest | 372,768 | 91.45 | 44 | 88 | 372,812 | 0.962 | −0.038 | |
Soil type | Cinnamon soil | 166,659 | 40.88 | 23 | 46 | 166,682 | 1.125 | 0.118 |
Brown soil | 240,979 | 59.12 | 27 | 54 | 241,006 | 0.914 | −0.091 | |
Flow accumulation | 0–2442 | 57,465 | 14.10 | 5 | 10 | 57,470 | 0.709 | −0.343 |
2442–4884 | 46,594 | 11.43 | 3 | 6 | 46,597 | 0.525 | −0.644 | |
4884–9768 | 71,240 | 17.48 | 7 | 14 | 71,247 | 0.801 | −0.222 | |
9768–14,652 | 51,253 | 12.57 | 6 | 12 | 51,259 | 0.954 | −0.047 | |
14,652–26,862 | 51,073 | 12.53 | 3 | 6 | 51,076 | 0.479 | −0.736 | |
26,862–46,398 | 38,437 | 9.43 | 6 | 12 | 38,443 | 1.273 | 0.241 | |
46,398–117,217 | 34,695 | 8.51 | 3 | 6 | 34,698 | 0.705 | −0.350 | |
117,217–351,651 | 27,961 | 6.86 | 5 | 10 | 27,966 | 1.458 | 0.377 | |
351,651–622,719 | 28,921 | 7.10 | 12 | 24 | 28,933 | 3.382 | 1.218 |
Class | FR | IVM | ||||
---|---|---|---|---|---|---|
Number of Grids | Area (km2) | Ratio (%) | Number of Grids | Area (km2) | Ratio (%) | |
Very Low | 99,911 | 2.50 | 24.55 | 70,450 | 1.76 | 17.31 |
Low | 133,203 | 3.34 | 32.74 | 111,088 | 2.78 | 27.30 |
Moderate | 89,531 | 2.24 | 22.00 | 95,677 | 2.40 | 23.51 |
High | 56,350 | 1.41 | 13.85 | 80,126 | 2.01 | 19.69 |
Very high | 27,918 | 0.70 | 6.86 | 49,572 | 1.24 | 12.18 |
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Cao, C.; Chen, J.; Zhang, W.; Xu, P.; Zheng, L.; Zhu, C. Geospatial Analysis of Mass-Wasting Susceptibility of Four Small Catchments in Mountainous Area of Miyun County, Beijing. Int. J. Environ. Res. Public Health 2019, 16, 2801. https://doi.org/10.3390/ijerph16152801
Cao C, Chen J, Zhang W, Xu P, Zheng L, Zhu C. Geospatial Analysis of Mass-Wasting Susceptibility of Four Small Catchments in Mountainous Area of Miyun County, Beijing. International Journal of Environmental Research and Public Health. 2019; 16(15):2801. https://doi.org/10.3390/ijerph16152801
Chicago/Turabian StyleCao, Chen, Jianping Chen, Wen Zhang, Peihua Xu, Lianjing Zheng, and Chun Zhu. 2019. "Geospatial Analysis of Mass-Wasting Susceptibility of Four Small Catchments in Mountainous Area of Miyun County, Beijing" International Journal of Environmental Research and Public Health 16, no. 15: 2801. https://doi.org/10.3390/ijerph16152801