Inventory of Landslides Triggered by Heavy Rainfall in Fuling District, Chongqing, China, June 2019

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Authors: Xue Zhiwen, Chong Xu, Yawei Xie, Xuning Nie, Xin Li, Zikang Xiao, Xiwei Xu, Zhiqiang Zhang, Dengjie Zhu, Bo Gong, Hourong Zhang
Cited by: 0
References: 109

Abstract

ABSTRACT In this study, a landslide triggered by a rainfall event in Fuling District of Chongqing was comprehensively investigated. Based on the high‐resolution remote sensing satellite image data and DEM data provided by GIS and Google Earth platform, and by comparing the image differences before and after the event, the landslide database triggered by this rainfall in Fuling District was constructed. Fuling District in Chongqing covers an area of about 2944 km 2 , and the total number of landslides is 791, with a total area of 818,418.1 m 2 , the smallest landslide area of 69 m 2 , the largest landslide area of 12,044.8 m 2 and the average landslide area of 1034.7 m 2 . Most landslides were categorised as small to medium‐sized, with those less than 1000 m 2 comprising over 70% of the total count. The landslides predominantly occurred in the northern and northeastern mountainous areas of Fuling District. This database not only provides detailed information on the location, size and distribution characteristics of landslides but also offers crucial data support for future research on rainfall‐induced landslide hazards. Researchers can utilise this data to further analyse patterns of landslide occurrence, identify influencing factors, and assess disaster risks, thereby providing a scientific basis for disaster prevention and mitigation strategies. Moreover, the collection and analysis of this data can serve as a significant reference for urban planning, land use management, and disaster risk management, fostering regional sustainable development and safe construction practices.

Fields of Study & Subjects

Landslides and related hazards Soil erosion and sediment transport Tree Root and Stability Studies

Publication details

Journal / source
Geoscience Data Journal
Volume
13
Issue
2
Publication date
10 March 2026
Language
EN