GIS-based landslide hazard assessment: an overview

2005 ◽  
Vol 29 (4) ◽  
pp. 548-567 ◽  
Author(s):  
Wang Huabin ◽  
Liu Gangjun ◽  
Xu Weiya ◽  
Wang Gonghui
Keyword(s):  
Hazard Assessment ◽  
Landslide Hazard ◽  
Integrated System ◽  
Process Models ◽  
Land Utilization ◽  
Property A ◽  
Landslide Hazard Assessment ◽  
Landslide Hazards ◽  
Digital Elevation ◽  
Slope Management

In recent years, landslide hazard assessment has played an important role in developing land utilization regulations aimed at minimizing the loss of lives and damage to property. A variety of approaches has been used in landslide assessment and these can be classified into qualitative factor overlay, statistical models, geotechnical process models, etc. However, there is little work on the satisfactory integration of these models with geographic information systems (GIS) to support slope management and landslide hazard mitigation. This paper deals with several aspects of landslide hazard assessment by presenting a focused review of GIS-based landslide hazard assessment: it starts with a framework for GIS-based assessment of landslide hazard; continues with a critical review of the state of the art in using GIS and digital elevation models (DEM) for mapping and modelling landslide hazards; and concludes with a description of an integrated system for effective landslide hazard assessment and zonation incorporating artificial intelligence and data mining technology in a GIS-based framework of knowledge discovery.

scholarly journals A study on the use of planarity for quick identification of potential landslide hazard

2015 ◽  
Vol 15 (5) ◽  
pp. 997-1009 ◽  
Author(s):  
M. H. Baek ◽  
T. H. Kim
Keyword(s):  
Hazard Assessment ◽  
Ground Surface ◽  
Landslide Hazard ◽  
Axial Orientation ◽  
Orientation Data ◽  
Landslide Hazard Assessment ◽  
Geotechnical Monitoring ◽  
Digital Elevation ◽  
Elevation Model ◽  
Geomorphological Features

Abstract. In this study we focused on identifying a geomorphological feature that controls the location of landslides. The representation of the feature is based on a high-resolution digital elevation model derived from the airborne laser altimetry (LiDAR) and evaluated by the statistical analysis of axial orientation data. The main principle of this analysis is generating eigenvalues from axial orientation data and comparing them. The planarity, a ratio of eigenvalues, would tell the degree of irregularity on the ground surface based on their ratios. Results are compared to the recent landslide case in Korea in order to evaluate the feasibility of the proposed methodology in identifying the potential landslide hazard. The preliminary landslide hazard assessment based on the planarity analysis discriminates features between stable and unstable domain in the study area well, especially in the landslide initiation zones. Results also show it is beneficial to build the landslide hazard inventory mapping, especially where no information on historical records of landslides exists. By combining other physical procedures such as geotechnical monitoring, the landslide hazard assessment using geomorphological features promises a better understanding of landslides and their mechanisms and provides an enhanced methodology to evaluate their hazards and appropriate actions.

Landslide hazard assessment using digital elevation models

2013 ◽  
Vol 50 (6) ◽  
pp. 620-631 ◽  
Author(s):  
Gordon A. Fenton ◽  
Amanda McLean ◽  
Farrokh Nadim ◽  
D.V. Griffiths
Keyword(s):  
Hazard Assessment ◽  
Slope Failure ◽  
Digital Elevation Models ◽  
Landslide Hazard ◽  
Mitigation Strategies ◽  
Human Beings ◽  
Maximum Slope ◽  
Vast Number ◽  
Landslide Hazard Assessment ◽  
Digital Elevation

Human beings are, in general, risk-averse and willing to go to great lengths to reduce failure consequences. However, if the underlying issues are not understood, effective action cannot properly be taken. A landslide hazard assessment framework capable of estimating regional probabilities of slope failure can be used to aid a vast number of communities currently living in landslide “danger zones”. Such a framework would provide a tool with which community resources can be optimized and ensure that appropriate preparedness and mitigation strategies are in place. Maximum slope angles, as estimated using digital elevation models (DEMs), are one of the most important indicators for landslide hazard assessment. This paper uses local averaging theory to determine how the resolution of DEMs affects regional landslide probability estimates. Emphasis is on a regional landslide hazard assessment, measured by the probability that one or more slopes of at least a critical minimum scale will fail within the region.

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