Dynamic development of landslide susceptibility based on slope unit and deep neural networks

The Three Gorges Reservoir is one of the areas with the most serious landslide hazards in China. Landslide susceptibility indicates where landslides are prone to occur in the future under the influences of certain geoenvironmental and triggering conditions and is an important way for landslide preve...

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Published inLandslides Vol. 18; no. 1; pp. 281 - 302
Main Authors Hua, Ye, Wang, Xianmin, Li, Yongwei, Xu, Peiyun, Xia, Wenxiang
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2021
Springer Nature B.V
Subjects
Agriculture
Algorithms
Annual rainfall
Artificial neural networks
Canyons
Civil Engineering
Construction
Dynamic response
Earth and Environmental Science
Earth Sciences
Geography
Geological hazards
Geology
Highway construction
Hydrology
Land use
Landslides
Landslides & mudslides
Monitoring
Mountain regions
Mountainous areas
Natural Hazards
Neural networks
Normalized difference vegetative index
Original Paper
Prevention
Rain
Rainfall
Remote sensing
Reservoir water
Reservoirs
Rivers
Road construction
Roads & highways
Segmentation
Slopes
Soil
Soil moisture
Soil water
Susceptibility
Vegetation index
Water levels
Yangtze River
The Three Gorges Reservoir
Deep neural networks
Landslide susceptibility
Slope unit
Online AccessGet full text
ISSN1612-510X
1612-5118
DOI10.1007/s10346-020-01444-0

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Abstract The Three Gorges Reservoir is one of the areas with the most serious landslide hazards in China. Landslide susceptibility indicates where landslides are prone to occur in the future under the influences of certain geoenvironmental and triggering conditions and is an important way for landslide prevention. This work employs multi-source and three-temporal landslide monitoring data (geology, terrain, hydrology, and remote sensing data) to reveal the dynamic change of landslide susceptibility with time in the Badong-Zigui section in the Three Gorges area. Nine influence factors for landslides (land use, aspect, engineering rock group (ERG), slope, distance to river (DTR), relative relief, normalized difference water index (NDWI), normalized difference vegetation index (NDVI) and annual cumulative rainfall (ACR)) are generated from the monitoring data. The algorithms of slope unit segmentation and deep neural networks are adopted to conduct landslide susceptibility evaluations in the 3 years of 2002, 2007, and 2017 and to investigate the dynamic change of landslide susceptibility. Moreover, this work also reveals the dynamic response of landslide susceptibility to the changing factors of rainfall, reservoir water fluctuation, soil moisture, and land use. Some new viewpoints are suggested as follows. (1) The main factors affecting landslide occurrence are DTR, NDWI, relative relief, and ERG. Among them, DTR contributes most in all the 3 years; thus, reservoir water fluctuation has the most important impact on landslide occurrence in the study area. (2) From 2002 to 2007, the new high-susceptibility areas mainly appeared along the Yangtze River and also distributed around the roads. From 2007 to 2017, more than half of the new high-susceptibility areas were distributed around the roads, and susceptibility increases also occurred in the mountainous areas far from the Yangtze River. (3) The development of landslide susceptibility from 2002 to 2007 was mainly caused by the rising of reservoir water level as well as road construction. The change of landslide susceptibility from 2007 to 2017 was mainly caused by rainfall and road construction. This work may provide some clues on landslide prevention and control according to the dynamic development of landslide susceptibility and the causes of the susceptibility changes.
AbstractList The Three Gorges Reservoir is one of the areas with the most serious landslide hazards in China. Landslide susceptibility indicates where landslides are prone to occur in the future under the influences of certain geoenvironmental and triggering conditions and is an important way for landslide prevention. This work employs multi-source and three-temporal landslide monitoring data (geology, terrain, hydrology, and remote sensing data) to reveal the dynamic change of landslide susceptibility with time in the Badong-Zigui section in the Three Gorges area. Nine influence factors for landslides (land use, aspect, engineering rock group (ERG), slope, distance to river (DTR), relative relief, normalized difference water index (NDWI), normalized difference vegetation index (NDVI) and annual cumulative rainfall (ACR)) are generated from the monitoring data. The algorithms of slope unit segmentation and deep neural networks are adopted to conduct landslide susceptibility evaluations in the 3 years of 2002, 2007, and 2017 and to investigate the dynamic change of landslide susceptibility. Moreover, this work also reveals the dynamic response of landslide susceptibility to the changing factors of rainfall, reservoir water fluctuation, soil moisture, and land use. Some new viewpoints are suggested as follows. (1) The main factors affecting landslide occurrence are DTR, NDWI, relative relief, and ERG. Among them, DTR contributes most in all the 3 years; thus, reservoir water fluctuation has the most important impact on landslide occurrence in the study area. (2) From 2002 to 2007, the new high-susceptibility areas mainly appeared along the Yangtze River and also distributed around the roads. From 2007 to 2017, more than half of the new high-susceptibility areas were distributed around the roads, and susceptibility increases also occurred in the mountainous areas far from the Yangtze River. (3) The development of landslide susceptibility from 2002 to 2007 was mainly caused by the rising of reservoir water level as well as road construction. The change of landslide susceptibility from 2007 to 2017 was mainly caused by rainfall and road construction. This work may provide some clues on landslide prevention and control according to the dynamic development of landslide susceptibility and the causes of the susceptibility changes.
The Three Gorges Reservoir is one of the areas with the most serious landslide hazards in China. Landslide susceptibility indicates where landslides are prone to occur in the future under the influences of certain geoenvironmental and triggering conditions and is an important way for landslide prevention. This work employs multi-source and three-temporal landslide monitoring data (geology, terrain, hydrology, and remote sensing data) to reveal the dynamic change of landslide susceptibility with time in the Badong-Zigui section in the Three Gorges area. Nine influence factors for landslides (land use, aspect, engineering rock group (ERG), slope, distance to river (DTR), relative relief, normalized difference water index (NDWI), normalized difference vegetation index (NDVI) and annual cumulative rainfall (ACR)) are generated from the monitoring data. The algorithms of slope unit segmentation and deep neural networks are adopted to conduct landslide susceptibility evaluations in the 3 years of 2002, 2007, and 2017 and to investigate the dynamic change of landslide susceptibility. Moreover, this work also reveals the dynamic response of landslide susceptibility to the changing factors of rainfall, reservoir water fluctuation, soil moisture, and land use. Some new viewpoints are suggested as follows. (1) The main factors affecting landslide occurrence are DTR, NDWI, relative relief, and ERG. Among them, DTR contributes most in all the 3 years; thus, reservoir water fluctuation has the most important impact on landslide occurrence in the study area. (2) From 2002 to 2007, the new high-susceptibility areas mainly appeared along the Yangtze River and also distributed around the roads. From 2007 to 2017, more than half of the new high-susceptibility areas were distributed around the roads, and susceptibility increases also occurred in the mountainous areas far from the Yangtze River. (3) The development of landslide susceptibility from 2002 to 2007 was mainly caused by the rising of reservoir water level as well as road construction. The change of landslide susceptibility from 2007 to 2017 was mainly caused by rainfall and road construction. This work may provide some clues on landslide prevention and control according to the dynamic development of landslide susceptibility and the causes of the susceptibility changes.
Author Wang, Xianmin
Xu, Peiyun
Li, Yongwei
Xia, Wenxiang
Hua, Ye
Author_xml – sequence: 1
  givenname: Ye
  surname: Hua
  fullname: Hua, Ye
  organization: Hubei Subsurface Multi-scale Imaging Key Laboratory, Institute of Geophysics and Geomatics, China University of Geosciences
– sequence: 2
  givenname: Xianmin
  surname: Wang
  fullname: Wang, Xianmin
  email: xianminwang@163.com
  organization: Hubei Subsurface Multi-scale Imaging Key Laboratory, Institute of Geophysics and Geomatics, China University of Geosciences
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  givenname: Yongwei
  surname: Li
  fullname: Li, Yongwei
  organization: Hubei Subsurface Multi-scale Imaging Key Laboratory, Institute of Geophysics and Geomatics, China University of Geosciences
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  givenname: Peiyun
  surname: Xu
  fullname: Xu, Peiyun
  organization: School of Geography and Information Engineering, China University of Geosciences
– sequence: 5
  givenname: Wenxiang
  surname: Xia
  fullname: Xia, Wenxiang
  organization: Hubei Subsurface Multi-scale Imaging Key Laboratory, Institute of Geophysics and Geomatics, China University of Geosciences
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IEDL.DBID BENPR
ISSN 1612-510X
IngestDate Fri Jul 25 09:45:20 EDT 2025
Wed Oct 01 02:50:02 EDT 2025
Thu Apr 24 23:04:03 EDT 2025
Fri Feb 21 02:49:08 EST 2025
IsPeerReviewed true
IsScholarly true
Issue 1
Keywords The Three Gorges Reservoir
Deep neural networks
Landslide susceptibility
Slope unit
Language English
LinkModel DirectLink
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crossref_citationtrail_10_1007_s10346_020_01444_0
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  year: 2021
  text: 20210100
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PublicationPlace Berlin/Heidelberg
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PublicationSubtitle Journal of the International Consortium on Landslides
PublicationTitle Landslides
PublicationTitleAbbrev Landslides
PublicationYear 2021
Publisher Springer Berlin Heidelberg
Springer Nature B.V
Publisher_xml – name: Springer Berlin Heidelberg
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Snippet The Three Gorges Reservoir is one of the areas with the most serious landslide hazards in China. Landslide susceptibility indicates where landslides are prone...
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SubjectTerms Agriculture
Algorithms
Annual rainfall
Artificial neural networks
Canyons
Civil Engineering
Construction
Dynamic response
Earth and Environmental Science
Earth Sciences
Geography
Geological hazards
Geology
Highway construction
Hydrology
Land use
Landslides
Landslides & mudslides
Monitoring
Mountain regions
Mountainous areas
Natural Hazards
Neural networks
Normalized difference vegetative index
Original Paper
Prevention
Rain
Rainfall
Remote sensing
Reservoir water
Reservoirs
Rivers
Road construction
Roads & highways
Segmentation
Slopes
Soil
Soil moisture
Soil water
Susceptibility
Vegetation index
Water levels
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Title Dynamic development of landslide susceptibility based on slope unit and deep neural networks
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