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Land Mw 6 Dslides T 6.2 Eart Trigger Thquake Journal of Earth Science, Vol. 31, No. 4, p. 853–866, August 2020 ISSN1674-487X Printed in China https://doi.org/10.1007/s12583-020-1297-7 Landslides Triggered by the 3 August 2014 Ludian (China) Mw 6.2 Earthquake: An Updated Inventory and Analysis of Their Spatial Distribution Weiying Wu1, Chong Xu *2, 3, Xiaoqing Wang1, Yingying Tian3, Fei Deng1 1. Institute of Earthquake Forecasting, China Earthquake Administration, Beijing 100036, China 2. Institute of Crustal Dynamics, China Earthquake Administration, Beijing 100085, China 3. Key Laboratory of Active Tectonics and Volcano, Institute of Geology, China Earthquake Administration, Beijing 100029, China Chong Xu: https://orcid.org/0000-0002-3956-4925 ABSTRACT: The 3 August 2014 Ludian, Yunnan, China Mw 6.2 (Ms 6.5) earthquake triggered a large number of coseismic landslides. Based on pre- and post-quake high-resolution optical satellite images, this study established a new, complete and objective database of these landsslides with field investigations. The updated inventory shows that this earthquake triggered at least 12 817 landslides with a total occupation area of 16.33 km2, covering a nearly circular area about 600 km2, which all exceed those in our previous work and other relevant studies. In addition, we used this database to examine the correlations of the landslides with topographic, geologic, and seismic factors. Results show that the landslides occurred mostly at places with slope gradients 10º–40º, showing an increase tendency with steeper slopes. Affected by the propagation direction of the earthquake rupture, the eastward-facing slopes are more prone to landsliding. The differences between the landslide suscep- tibility in different strata indicate that lithology is also an important controlling factor. The landslide density of the places with peak ground acceleration (PGA) greater than 0.16g is obviously larger than those with PGA less than 0.16g. Meanwhile, the greater the distance from the epicenter, the lower the susceptibility of landslides is. This study suggests that when using satellite images to create coseismic landslide inventories, it should meet certain conditions, including high resolution, whole coverage, and timely data collection. The correct criteria of coseismic landslide inventorying also should be followed. Such inventories can provide a reliable basis for hazard assessment of earthquake-triggered landslides and other quantitative studies. KEY WORDS: 2014 Ludian earthquake, coseismic landslides, landslide inventory, spatial distribu- tion. 0 INTRODUCTION groups (Xu, 2015). Landslides triggered by large earthquakes Major earthquakes in mountainous areas can induce mas- are usually characterized by large scope, large number, and sive landslides, leading to serious disasters (Shao et al., 2019a; complex morphology. Therefore, it is impossible to complete a Tian et al., 2019a; Lei, 2012; Xu et al., 2010; Yin et al., 2009; high-quality landslide inventory related to a large earthquake Keefer, 1984; Seed, 1968). A detailed and accurate inventory immediately solely based on field investigations, especially in of earthquake-triggered landslides is an important basis for affected areas with complicated tterrain. Currently, a common research on this issue (Ma and Xu, 2019a, b; Tian et al., 2019b; method of coseismic landslide inventorying is to delineate Xu et al., 2015, 2014a; Guzzetti et al., 2012; Harp et al., 2011). landslides based on visual interpretation of optical satellite A high-quality landslide inventory should cover the whole images with the aid of other higher-resolution images, such as earthquake area, spanning all scales of coseismic landslides that aerial photographs, and in combination with field verifications. can be detected, mapping accurate locations and boundaries, The quality of landslide inventories depends on the image qual- providing polygon-based descriptions of the landslides, and ity, coverage, and methods of interpretation, which determines separating individual landslides from contiguous landslides if the final landslide inventory is complete and accurate. In recent years, quite a few achievements about coseismic land- *Corresponding author: [email protected] slide inventories have been reported, such as the 1994 North- © China University of Geosciences (Wuhan) and Springer-Verlag ridge, California (USA) Mw 6.7 (Harp and Jibson, 1996, 1995), GmbH Germany, Part of Springer Nature 2020 the 1999 Chi-chi, Taiwan (China) Mw 7.6 (Wang et al., 2002; Liao and Lee, 2000), the 2008 Wenchuan (China) Mw 7.9 (Li Manuscript received September 22, 2019. et al., 2014; Xu et al., 2014a; Gorum et al., 2011), the 2010 Manuscript accepted January 20, 2020. Port-au-Prince (Haiti) Mw 7.0 (Harp et al., 2016; Xu et al., Wu, W. Y., Xu, C., Wang, X. Q., et al., 2020. Landslides Triggered by the 3 August 2014 Ludian (China) Mw 6.2 Earthquake: An Updated Inventory and Analysis of Their Spatial Distribution. Journal of Earth Science, 31(4): 853–866. https://doi.org/10.1007/s12583-020-1297-7. http://en.earth-science.net 854 Weiying Wu, Chong Xu, Xiaoqing Wang, Yingying Tian and Fei Deng 2014b; Gorum et al., 2013), the 2013 Minxian (China) Mw 5.9 1 REGIONAL SETTING (Tian et al., 2017a, 2016; Xu et al., 2014c), the 2013 Lushan The 2014 Ludian Mw 6.2 earthquake took place on the (China) Mw 6.6 (Xu et al., 2015), the 2015 Gorkha (Nepal) Mw east edge of the Sichuan-Yunnan rhomboidal block, the south- 7.8 (Xu et al., 2018a, 2016a; Gnyawali and Adhikari, 2017; east margin of the Tibet Plateau, and mid-south of the north- Martha et al., 2017; Tiwari et al., 2017), the 2016 Kumamoto south seismic belt of Central China Mainland (Wang et al., 2010). (Japan) Mw 7.0 (Xu et al., 2018b), the 2016 Kaikōura (New This region is characterized by many active faults, intense tec- Zealand) Mw 7.8 (Massey et al., 2018; Sotiris et al., 2016), the tonic deformation, and frequent major earthquake (Xu X W et al., 2017 Jiuzhaigou (China) Mw 6.5 (Tian et al., 2019a), and the 2015; Xu X et al., 2003; Zhang et al., 2003). The Zemuhe fault 2018 Tomakomai (Japan) Mw 6.6 (Shao et al., 2019a) and Xiaojiang fault, which trend NNW with left-lateral strike-slip earthquakes. These data can facilitate studies of the spatial movement are the primary active structures in this area. North- distribution of coseismic landslides, the subsequent susceptibil- east of them, a series of nearly parallel NE-trending right-lateral ity and hazard assessment, and the impact on geomorphic evo- strike-slip faults of relatively smaller scales are present (Fig. 1), lution in the earthquake-affected area. Therefore, it is the most where the epicenter of the Ludian earthquake is located be- important task to prepare a detailed and complete inventory of tween Lianfeng fault (LFF) and Zhaotong-Ludian fault (ZLF). coseismic landslides and analyze their spatial distribution after In field investigations, Xu X W et al. (2015) found a 2-km-long, a large mountainous earthquake occurs. NNW trending surface rupture and a 6-km-long deformation At 16:30 on August 3, 2014 (Beijing time), an Mw 6.2 belt associated with the earthquake. Combining aftershock (Ms 6.5) earthquake occurred in Ludian County, Zhaotong City, distribution, they suggested that the NNW-trending Baogunao- Yunnan Province, China. Its epicenter is located at 27.099 4ºN, Xiaohe fault (BXF) between the LFF and ZLF is the seis- 103.34ºE with a focal depth of 12 km. As of 15 August 2014, mogenic structure of this earthquake. It is a left-lateral strike- 617 people were killed, 112 were missing, 3 143 were injured, slip fault with a direction of 330º that is composed of several 229 700 were relocated and 80 900 houses collapsed (Xu et al., secondary, discontinuous faults (Xu X W et al., 2015; Chang et 2014d). Because of the steep terrain, high topographic relief, al., 2014; Xu X et al., 2014). Due to strong tectonic uplift and fragile geological conditions, and strong ground shaking in the stream incision, this area hosts steep slopes and deep valleys affected area, the earthquake triggered a large number of land- with maximum terrain relief over 1 500 m. slides (Xu et al., 2014d), including quite a few large-scale rock falls and avalanches (Shi et al., 2017; Chang et al., 2016; Zhou 2 DATA AND METHODS J W et al., 2016). Very soon after the earthquake, some re- 2.1 Data searchers made investigations into its geologic effects and sev- The pre- and post-quake, ultrahigh-resolution satellite im- eral inventories of coseismic landslides were released (Wu and ages used in this study come from the Google Earth platform. Xu, 2018; Tian et al., 2017b; Zhou S H et al., 2016; Chen et al., 2015; Xu et al., 2014d), which provides general information on these landslides and facilitates further research. However, be- cause of the limited resolution and quality of satellite images available then and other reasons, such as professional levels and experience of interpreters, all the released landslide inven- tories are incomplete and unsatisfactory. Most of them contain significant commission and omission errors, for instance, de- lineating quite a few medium- and small-scale landslides into a large individual one. Considering the importance of the basic data, this study attempts to establish a new and more objective landslide inventory related to the Ludian earthquake based on artificial visual interpretation of pre- and post-quake ultra- high-resolution satellite images covering the whole affected area in combination with selected field investigations. Results show that this earthquake triggered at least 12 817 landslides in a suborbicular area about 600 km2. This number is much larger than previous studies (Zhou S H et al., 2016; Chen et al., 2015; Xu et al., 2014d). The reasons for this discrepancy may involve some aspects, such as the selection of remote sensing images, the coverage, and resolution of available post-quake satellite Figure 1.
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