Global patterns of loss of life from landslides

Petley, David

doi:10.1130/g33217.1

Cited by 1,212 publications

(656 citation statements)

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“…Having severe impact both on civil infrastructure and on the natural environment, landslides cause losses and damages of several billion US$ every year as well as numerous fatalities and injuries [4]. As reported by Petley [5], who has investigated fatal landslides between 2004 and 2010, during the 7-year observation period 2,620 landslides have been recorded, which have caused more than 30,000 fatalities.…”

Section: Introductionmentioning

confidence: 97%

An Internet-Enabled Wireless Multi-Sensor System for Continuous Monitoring of Landslide Processes

Smarsly¹,

Georgieva²,

König³

2014

IJET

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Abstract-Monitoring and early warning systems, although being capable of continuously collecting field data related to landslide processes, are usually unable to autonomously detect and analyze signs of landslides in real time. This paper presents the design and experimental implementation of an autonomous landslide monitoring system. Besides reliably issuing early warnings in case of detected slope anomalies, the monitoring system is primarily designed to support human individuals in assessing the risk of landslide and to improve the understanding of the slope behavior, which may help to reduce economic losses and fatalities caused by landslides. Specifically, intelligent wireless sensor nodes are distributed in the observed slope to autonomously collect, analyze and communicate relevant environmental parameters in real time. Supporting remote analyses of the collected field data, a web application, which is installed on a computer connected to the on-site sensor nodes, enables an automated dissemination of slope parameters through the Internet. Last but not least, geospatial information stemming from external sources is integrated into the monitoring system to provide a comprehensive overview of landslide-related slope conditions. Index Terms-Monitoring of slope movements, wireless sensor networks, early warning systems, artificial intelligence, smart sensors, Internet computing. I. INTRODUCTIONThe world population, which currently numbers more than 7 billion people [1], is growing continuously, and it is expected to reach 10 billion people in the year 2100 [2]. As a direct consequence of the population growth, also the density of population increases rapidly, and therefore unstable, hazardous areas and steep terrains with high risks of natural hazards such as volcanic eruptions, floods or landslides are being developed for settlement [3]. As another direct consequence of the population growth, human activities increasingly trigger natural hazards due to changes in the environmental conditions. For example, landslides are frequently initiated by human-induced factors, such as disturbed or changed drainage patterns, destabilized slopes, or removed vegetation [4]. Landslides, according to the United States Geological Survey (USGS) are defined as "downslope movement of soil, rock and organic materials under the effects of gravity" [4]. Generally, landslides occur in different terrains independently from climate conditions, and they are among the most common but also among the most dangerous natural hazards, because civil infrastructure cannot withstand the forces generated by moving masses of soil, rock, or organic material. Having severe impact both on civil infrastructure and on the natural environment, landslides cause losses and damages of several billion US$ every year as well as numerous fatalities and injuries [4]. As reported by Petley [5], who has investigated fatal landslides between 2004 and 2010, during the 7-year observation period 2,620 landslides have been recorded, which have caused more than 30,0...

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Section: Introductionmentioning

confidence: 97%

An Internet-Enabled Wireless Multi-Sensor System for Continuous Monitoring of Landslide Processes

Smarsly¹,

Georgieva²,

König³

2014

IJET

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“…There are various definitions of reliability depending of the field of study; however, it contains four basic elements: probability, adequate performance, time, and operating conditions (Billinton and Allan, 1992). One of the definitions of reliability in general terms can be introduced as: the probability that an item will perform a required function without failure under stated conditions for a stated period of time (O'Connor and Kleyner, 2012). According to Kapur and Pecht (2014), the reliability function R(t) in mathematical terms is expressed as: 25…”

Section: Probability Model By the Reliability Conceptmentioning

confidence: 99%

“…Landslide is one of the most dangerous disasters in terms of occurrence frequency and damage severity that result in loss of human life and social infrastructure (Petley, 2012;Kjekstad and Highland, 2009;Guzzetti, 2000;Salvati et al, 2010). 30 Nat.…”

Section: Introduction 25mentioning

confidence: 99%

Risk-based analysis of monitoring time intervals for landslide prevention

Lee

Kil

et al. 2017

Preprint

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Abstract.Landslide is one of the most dangerous disasters in terms of occurrence frequency and damage severity that result in loss of human life and social infrastructure. Monitoring methods based on low temporal resolution instruments such as an inclinometer or piezometer can be an effective and cost-efficient solution. The objective of this research is to analyse monitoring time 15 intervals for low temporal resolution methods based on a risk study and to propose a plan for periodic landslide monitoring along with the different landslide hazard areas by considering the risk reduction effect. For this purpose, an equation for the probability of landslide occurrence was denoted by the concept of reliability, and the monitoring time interval was analysed quantitatively by calculating the average probability of landslide occurrence. To identity the frequency of landslide occurrence, a unit of relative temporal frequencies was adopted, and it was estimated by establishing rainfall threshold. As a case study 20 site, Pyeongchang County was selected, where landslide inventory data are available and an increase in population and infrastructure has been observed since Pyeongchang became the host city of the 2018 winter Olympic games. The result demonstrates that the appropriate monitoring intervals can be determined by calculating the average probability of landslide occurrence, and resources can then be allocated efficiently for landslide prevention.

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“…Another constraint to study the mortality caused by landslides is the relatively short time span of the existing databases and the lack of field validation (Petley 2012).…”

Section: Introductionmentioning

confidence: 99%

“…Landslides activity usually causes direct human impacts (fatalities, injuries), but the quantitative assessment of landslide societal risk has been developed in a limited number of studies performed at global (Petley 2012), European (Haque et al 2016) and national scales (Guzzetti 2000;Salvati et al 2010;Pereira et al 2016). …”

Section: Introductionmentioning

confidence: 99%

Landslide Societal Risk in Portugal in the Period 1865–2015

Pereira

Zêzere

Quaresma

2017

Advancing Culture of Living With Landslides

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In Portugal, social impacts caused by landslides occurred in the period 1865-2015 are gathered in the DISASTER database. This database includes social consequences (fatalities, injuries, missing people, evacuated people and homeless people) caused by landslides documented in newspapers. The DISASTER database contains 291 damaging landslides that caused 238 fatalities. In this work we aim to: (i) analyse the spatio-temporal analysis of damaging landslides occurred in the last 150 years; (ii) analyse the frequency and the temporal evolution of fatal landslides; (iii) analyse the spatio-temporal distribution of landslide fatalities; (iv) identify the most deadly landside types; (v) verify gender tendencies in landslide mortality; and (vi) evaluate the individual and societal risk. Individual risk is evaluated computing mortality rates for landslides, which are calculated based on the annual average population and the annual average of fatalities. The societal risk is evaluated by plotting the annual frequency of landslide cases that generated fatalities. The results demonstrate the absence of any exponential growth in time of both landslide cases and landslide mortality in Portugal. The highest number of landslide cases and related mortalities occurred in the period of 1935-1969 in relation to very wet years. Most of landslide fatalities mainly occurred in the north of the Tagus valley where the geologic and geomorphologic conditions are more prone to landslides. The Lisbon area registered a mortality hotspot, which is explained by natural conditions combined with the high exposure of population to landslide risk. Falls and flows were responsible for the highest number of fatalities associated with landslides. Males were found to have the highest frequency of fatalities. In conclusion, the spatial patterns of landslide mortality can be related to the unequal distribution of predisposing conditions to landslides, changes in the land use and exposure and social vulnerability to landslide hazards.

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Global patterns of loss of life from landslides

Cited by 1,212 publications

References 18 publications

An Internet-Enabled Wireless Multi-Sensor System for Continuous Monitoring of Landslide Processes

An Internet-Enabled Wireless Multi-Sensor System for Continuous Monitoring of Landslide Processes

Risk-based analysis of monitoring time intervals for landslide prevention

Landslide Societal Risk in Portugal in the Period 1865–2015

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