Abstract
Earthquake-induced landslide (EQIL) inventories are essential tools to extend our knowledge of the relationship between earthquakes and the landslides they can trigger. Regrettably, such inventories are difficult to generate and therefore scarce, and the available ones differ in terms of their quality and level of completeness. Moreover, access to existing EQIL inventories is currently difficult because there is no centralized database. To address these issues, we compiled EQIL inventories from around the globe based on an extensive literature study. The database contains information on 363 landslide-triggering earthquakes and includes 66 digital landslide inventories. To make these data openly available, we created a repository to host the digital inventories that we have permission to redistribute through the U.S. Geological Survey ScienceBase platform. It can grow over time as more authors contribute their inventories. We analyze the distribution of EQIL events by time period and location, more specifically breaking down the distribution by continent, country, and mountain region. Additionally, we analyze frequency distributions of EQIL characteristics, such as the approximate area affected by landslides, total number of landslides, maximum distance from fault rupture zone, and distance from epicenter when the fault plane location is unknown. For the available digital EQIL inventories, we examine the underlying characteristics of landslide size, topographic slope, roughness, local relief, distance to streams, peak ground acceleration, peak ground velocity, and Modified Mercalli Intensity. Also, we present an evaluation system to help users assess the suitability of the available inventories for different types of EQIL studies and model development.
| Original language | English |
|---|---|
| Pages (from-to) | 1991-2015 |
| Number of pages | 25 |
| Journal | Journal of Geophysical Research: Earth Surface |
| Volume | 122 |
| Issue number | 10 |
| DOIs | |
| Publication status | Published - Oct 2017 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:©2017. The Authors.
Funding
For the sharing of their EQIL inventories, the authors are very grateful to following researchers: Brian D. Collins, Chenxiao Tang, Chong Xu, Chyi-Tyi Lee, Edwin L. Harp, F. C. Dai, Fausto Guzzetti, M. J. García-Rodríguez, Gen Li, George Papathanassiou, Geospatial Information Authority of Japan, Hiroshi Yagi, Jianqiang Zhang, John Barlow, Jose Delgado, Joseph Wartman, LI Wei-le, Masahiro Chigira, Mattia De Amicis, Muhammad Basharat, Pascal Lacroix, Saibal Ghosh, Sergio A. Sepúlveda, Shengwen Qi, Tai-Phoon Huang, Taro Uchida, Timothy P. McCrink, Tommaso Piacentini, and Tsuyoshi Wakatsuki. Thank you to Yoko Tamura (PASCO) for assistance with obtaining the data set provided by PASCO Corporation and Kokusai Kogyo Company Ltd of Japan and Sally Dellow (GNS Science) and Toko Takayama (Asia Air Survey Co., Ltd of Japan) for assistance with obtaining the data sets provided by GNS Science and National Institute for Land and Infrastructure Management of Japan. We would also like to thank Mario Reyes of the El Salvador Landslides Monitoring Center (Ministry of Environment and Natural Resources) for his assistance in providing landslide inventories from El Salvador, the Japan Landslide Society for providing the earthquake-induced landslide inventory, Kristin D. Marano for providing global records of earthquake-induced landslides, and David Wald, Michael Hamburger, and two anonymous reviewers for their comments and contributions. T. G. wishes to thank the Turkish Academy of Sciences for their support within the framework of the Distinguished Young Scientist Award Program (TÜBA-GEBIP). Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. The authors have no conflicts of interest related to the work reported in this paper. Data that we have permission to share are available through the ScienceBase Community, which is a collaborative scientific data and information management platform developed by the USGS.
| Funders | Funder number |
|---|---|
| Turkish Academy of Sciences |
Keywords
- data characteristics
- data sharing
- earthquake-induced landslides inventories
- evaluation of earthquake-induced landslide inventories
- global database
