Topographic Analysis of Landslide Distribution Using AW3D30 Data
Abstract
1. Introduction
2. Study Area
3. DEM and Landslide Datasets
4. Ridgeline Extraction
5. Landslide Distributions Relative to Ridgelines
6. Discussion
7. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Xu, Q.; Fan, X.; Huang, R.; Westen, C. Landslide dams triggered by the Wenchuan Earthquake, Sichuan Province, southwest China. Bull. Eng. Geol. Environ. 2009, 68, 373–386. [Google Scholar] [CrossRef]
- Lacroix, P. Landslides triggered by the Gorkha earthquake in the Langtang valley, volumes and initiation processes. Earth Planets Space 2016, 68, 46. [Google Scholar] [CrossRef]
- Dai, F.C.; Lee, F.C.; Ngai, Y.Y. Landslide risk assessment and management: An overview. Eng. Geol. 2002, 64, 65–87. [Google Scholar] [CrossRef]
- Kirschbaum, D.B.; Stanley, T.; Simmons, J. A dynamic landslide hazard assessment system for Central America and Hispaniola. Nat. Hazards Earth Syst. Sci. 2015, 15, 2257–2272. [Google Scholar] [CrossRef]
- Froude, M.J.; Petley, D.V. Global fatal landslide occurrence from 2004 to 2016. Nat. Hazards Earth Syst. Sci. 2018, 18, 2161–2181. [Google Scholar] [CrossRef]
- Fan, X.; Zhan, W.; Dong, X.; Westen, C.; Xu, Q.; Dai, L.; Yang, Q.; Huang, R.; Havenith, H. Analyzing successive landslide dam formation by different triggering mechanisms: The case of the Tangjiawan landslide, Sichuan, China. Eng. Geol. 2018, 243, 128–144. [Google Scholar] [CrossRef]
- Chang, K.; Chan, Y.; Chen, R.; Hsieh, Y. Geomorphological evolution of landslides near an active normal fault in northern Taiwan, as revealed by lidar and unmanned aircraft system data. Nat. Hazards Earth Syst. Sci. 2018, 18, 709–727. [Google Scholar] [CrossRef]
- Wang, Y.; Ma, C.; Wang, Z. Prediction of landslide position of loose rock mass at mountain tunnel exit. Adv. Civ. Eng. 2019, 2019, 1–9. [Google Scholar] [CrossRef]
- Guzzetti, F.; Mondini, A.; Cardinali, M.; Fiorucci, F.; Santangelo, M.; Chang, K. Landslide inventory maps: New tools for an old problem. Earth-Sci. Rev. 2012, 112, 42–66. [Google Scholar] [CrossRef]
- Varnes, D. Slope Movement Types and Processes. In Landslides: Analysis and Control; Schuster, R., Krizek, R., Eds.; National Research Council; Transportation Research Board; Special Report 176; National Academy of Science: Washington, DC, USA, 1978; pp. 11–33. [Google Scholar]
- International Association for Engineering Geology and the Environment (IAEG) Commission. Suggested nomenclature for landslides. Bull. Int. Assoc. Eng. Geol. 1990, 41, 13–16. [Google Scholar] [CrossRef]
- Tarolli, P.; Tarboton, D. A new method for determination of most likely landslide initiation points and the evaluation of digital terrain model scale in terrain stability mapping. Hydrol. Earth Sys. Sci. 2006, 10, 663–677. [Google Scholar] [CrossRef]
- Booth, A.; Roering, J.; Perron, J. Automated landslide mapping using spectral analysis and high-resolution topographic data: Puget Sound lowlands, Washington, and Portland Hills, Oregon. Geomorphology 2009, 109, 132–147. [Google Scholar] [CrossRef]
- Hölbling, D.; Betts, H.; Spiekermann, R.; Phillips, C. Identifying Spatio-Temporal Landslide Hotspots on North Island, New Zealand, by Analyzing Historical and Recent Aerial Photography. Geosciences 2016, 6, 48. [Google Scholar] [CrossRef]
- Pawluszek, K. Landslide features identification and morphology investigation using high-resolution DEM derivatives. Nat. Hazards 2019, 96, 311–330. [Google Scholar] [CrossRef]
- Keefer, D. The Loma Prieta, California, Earthquake of October 17, 1989—Landslides; USGS Professional Paper 1551–C; US Government Printing Office: Washington, DC, USA, 1998.
- AIST. GeomapNavi, Geological Map Display System of Geological Survey of Japan; AIST: Warrendale, PA, USA, 2014. [Google Scholar]
- Hasegawa, S.; Tamura, E.; Kanbara, D. Georisks along active faults of Median Tectonic Line in Shikoku, Southwest Japan. In Proceedings of the 10th Asian Regional Conference of IAEG, Kyoto, Japan, 26–29 September 2015; pp. 1–8. [Google Scholar]
- Alganci, U.; Besol, B.; Sertel, E. Accuracy assessment of different digital surface models. ISPRS Int. J. Geo-Inf. 2018, 7, 114. [Google Scholar] [CrossRef]
- Tadono, T.; Ishida, H.; Oda, F.; Naito, S.; Minakawa, K.; Iwamoto, H. Precise Global DEM Generation by ALOS PRISM. ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci. 2014, 4, 71–76. [Google Scholar] [CrossRef]
- Tadono, T.; Nagai, H.; Ishida, H.; Oda, F.; Naito, S.; Minakawa, K.; Iwamoto, H. Initial Validation of the 30 m-mesh Global Digital Surface Model Generated by ALOS PRISM. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. ISPRS 2016, 157–162. [Google Scholar] [CrossRef]
- National Research Institute for Earth Science and Disaster Prevention. Digital Archive for Landslide Distribution Maps. Available online: http://dil-opac.bosai.go.jp/publication/nied_tech_note/landslidemap/gis.html (accessed on 10 February 2020).
- Dou, J.; Bui, D.; Yunus, A.; Jia, K.; Song, X.; Revhaug, I.; Xia, H.; Zhu, Z. Optimization of causative factors for landslide susceptibility evaluation using remote sensing and GIS data in parts of Niigata, Japan. PLoS ONE 2015, 10, e0133262. [Google Scholar] [CrossRef]
- Schmidt, J.; Evans, I.; Brinkmann, J. Comparison of polynomial models for land surface curvature calculation. Int. J. Geogr. Inf. Sci. 2003, 17, 797–814. [Google Scholar] [CrossRef]
- Shary, P.; Sharaya, L.; Mitusov, A. Fundamental quantitative methods of land surface analysis. Geoderma 2002, 107, 1–32. [Google Scholar] [CrossRef]
- Bergonse, R.; Reis, E. Controlling factors of the size and location of large gully systems: A regression-based exploration using reconstructed pre-erosion topography. Catena 2016, 147, 621–631. [Google Scholar] [CrossRef]
- Conoscenti, C.; Angileri, S.; Cappadonia, C.; Rotigliano, E.; Agnesi, V.; Märker, M. Gully erosion susceptibility assessment by means of GIS-based logistic regression: A case of Sicily (Italy). Geomorphology 2014, 204, 399–411. [Google Scholar] [CrossRef]
- Dewitte, O.; Daoudi, M.; Bosco, C.; Eeckhaut, M. Predicting the susceptibility to gully initiation in data-poor regions. Geomorphology 2015, 228, 101–115. [Google Scholar] [CrossRef]
- Gutiérrez, Á.; Schnabel, S.; Felicísimo, Á. Modelling the occurrence of gullies in rangelands of southwest Spain. Earth Surf. Proc. Landf. 2009, 34, 1894–1902. [Google Scholar] [CrossRef]
- Nonomura, A.; Hasegawa, S.; Matsumoto, H.; Takahashi, M.; Masumoto, M.; Fujisawa, K. Curvature derived from LiDAR digital elevation models as simple indicators of debris-flow susceptibility. J. Mt. Sci. 2015, 16, 95–107. [Google Scholar] [CrossRef]
- Yokoyama, R.; Shirasawa, M.; Pike, R. Visualizing topography by openness: A new application of image processing to Digital Elevation Models. Photogramm. Eng. Remote Sens. 2002, 68, 257–265. [Google Scholar]
- Kaihara, S.; Arakawa, M.; Tetsuga, H.; Sato, T.; Maeda, M.; Nakayama, H.; Furukawa, K. A study on the method of critical line in the each slope using data envelopment analysis. J. Jpn. Soc. Eros. Control Eng. 2015, 16, 95–107. [Google Scholar]
- Charnes, A.; Cooper, W.; Rhodes, E. Measuring the efficiency of decision making units. Eur. J. Oper. Res. 1978, 2, 429–444. [Google Scholar] [CrossRef]
- Cooper, W.; Seiford, L.; Zhu, J. Data envelopment analysis, History, Models, and Interpretations. In Handbook on Data Envelopment Analysis; Springer: Boston, MA, USA, 2011; pp. 1–39. [Google Scholar]
- CRAN. Available online: https://cran.r-project.org/web/packages/rDEA/rDEA.pdf (accessed on 12 June 2016).
- Ministry of Land, Infrastructure, Transport and Tourism, Government of Japan. Shikoku Regional Development Bureau. Available online: https://www.skr.mlit.go.jp/kokai/project_evaluation/h23/2nd/pdf/6.pdf (accessed on 12 October 2011).
- Yanagida, M.; Hasegawa, S. Morphological dating and dissection process of landslide topography. In Landslide, Proceedings of the 7th International Conference and Field Workshop on Landslides, 28 August–15 September 1993, Czech and Slovakia; Novosad, S., Wagner, P., Eds.; A.A. Balkema: Rotterdam, The Netherlands; Brookfield: Toronto, ON, Canada, 1993; pp. 117–122. [Google Scholar]
- NASA. Landsat Science. Available online: https://www.nasa.gov/jpl/landsat-8-reveals-extent-of-quake-disaster-in-nepal-s-langtang-valley (accessed on 12 February 2020).
- Nappo, N.; Peduto, D.; Mavrouli, O.; Westen, C.; Gullà, G. Slow-moving landslides interacting with the road network: Analysis of damage using ancillary data, in situ surveys and multi-source monitoring data. Eng. Geol. 2019, 260, 105244. [Google Scholar] [CrossRef]
- Li, L.; Yao, X.; Yao, J.; Zhou, Z.; Feng, X.; Liu, X. Analysis of deformation characteristics for a reservoir landslide before and after impoundment by multiple D-InSAR observations at Jinshajiang River, China. Nat. Hazards 2019, 98, 719–733. [Google Scholar] [CrossRef]
- Hao, J.; Wu, T.; Wu, X.; Hu, G.; Zou, D.; Zhu, X.; Zhao, L.; Li, R.; Xie, C.; Ni, J.; et al. Investigation of a small landslide in the Qinghai-Tibet Plateau by InSAR and absolute deformation model. Remote Sens. 2019, 11, 2126. [Google Scholar] [CrossRef]
- Van Western, C.J.; Van Asch, T.W.J.; Soeters, R. Landslide hazard and risk zonation—Why is it sill so difficult? Bull. Eng. Geol. Environ. 2006, 65, 167–184. [Google Scholar] [CrossRef]
Site A | Site B | Site C | Average | |
---|---|---|---|---|
Average (ave) | 14.7 | 11.2 | 10.4 | - |
Standard deviation (σ) | 3.6 | 2.8 | 3.1 | - |
Ave-σ | 11.1 | 8.5 | 7.3 | 9.0 |
Ave-2σ | 7.5 | 5.7 | 4.2 | 5.8 |
Site 1 | Site 2 | Site 3 | Site 4 | Site 5 | |
---|---|---|---|---|---|
Average (m2) | 209,965 | 81,739 | 52,421 | 162,660 | 5811 |
Standard deviation (m2) | 176,874 | 132,260 | 77,824 | 131,828 | 16,406 |
The number of grids | 160 | 160 | 100 | 100 | 100 |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Nonomura, A.; Hasegawa, S.; Kanbara, D.; Tadono, T.; Chiba, T. Topographic Analysis of Landslide Distribution Using AW3D30 Data. Geosciences 2020, 10, 115. https://doi.org/10.3390/geosciences10040115
Nonomura A, Hasegawa S, Kanbara D, Tadono T, Chiba T. Topographic Analysis of Landslide Distribution Using AW3D30 Data. Geosciences. 2020; 10(4):115. https://doi.org/10.3390/geosciences10040115
Chicago/Turabian StyleNonomura, Atsuko, Shuichi Hasegawa, Daisuke Kanbara, Takeo Tadono, and Tatsuro Chiba. 2020. "Topographic Analysis of Landslide Distribution Using AW3D30 Data" Geosciences 10, no. 4: 115. https://doi.org/10.3390/geosciences10040115
APA StyleNonomura, A., Hasegawa, S., Kanbara, D., Tadono, T., & Chiba, T. (2020). Topographic Analysis of Landslide Distribution Using AW3D30 Data. Geosciences, 10(4), 115. https://doi.org/10.3390/geosciences10040115