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Slope stability risk management in open pit mines

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Slope stability risk management in open pit mines

Karam, K.S.

1,2; He, M.C.

3 and Sousa, L.R.

3,4

1Masdar Institute of Science and Technology,

2Sarooj Construction Company, Abu Dhabi, United Arab Emirates.

kkaram@masdar.ac.ae. 3State Key Laboratory for Geomechanics and Deep Underground Engineering, University of

Mining & Technology, Beijing, China; 4University of Porto, Portugal

Abstract

The stability of slopes in open pit mines is an issue of great concern because of the significant detrimental

consequences instabilities can have. To ensure the safe and continuous economic operation of these mines, it is

necessary to systematically assess and manage slope stability risk. This however has not been traditionally easy due

to the fact that measuring the parameters needed to assess the stability of slopes can be laborious, expensive, and

cause disruption to mining operations. This paper presents a framework based on decision theory by which risk can

be systematically assessed and managed, and proposes a combination of traditional, and remote sensing techniques,

both earth and satellite based, to measure certain parameters. This combination allows one to assess and update risk

in a more efficient and cost effective way than is traditionally done particularly where satellite observation data is

already available. The application of such a system at the Nanfen iron open pit mine in China is presented, where a

novel technique for monitoring sliding forces on pre-stressed rock bolts was developed and successfully applied.

This is the first step in building an automated risk management system, which in the future will include smart

sensors for warning systems and stabilization methods based on materials that can self-adjust their properties such as

strength, and stiffness in response to potential instabilities.

Keywords: Risk Management, Decision Analysis, Slope Stability, Open Pit Mines, Remote Sensing

1. Introduction

Open pit mines are among the largest geotechnical structures in the world, and are located necessarily where ore can

be extracted economically. These are frequently in inconvenient locations for the geotechnical engineer because

processes such as seepage concentrate the ore along a fault, which then passes through the pit. It is not uncommon to

find strata on opposite sides of the fault dipping in different directions and having different geotechnical properties.

Excavation usually takes place in a series of benches, each of which may be many meters high, so the geotechnical

engineer must evaluate the stability of individual benches as well as the overall slope. Since excavating and

disposing of material is a major cost in operating the mine, the simplest way to hold down the cost of excavation and

disposal is to reduce the volume that needs to be excavated. This implies, on the one hand that the slopes of the pit

be as steep as possible, but on the other hand, the steeper the slopes, the greater the danger of slope failures. Slope

instabilities can have detrimental consequences, both in terms of economic damage, and sometimes even loss of life.

To ensure the safe and economic operation of these mines, it is necessary to systematically assess and manage slope

stability risk. This paper presents a framework based on decision theory by which risk can be systematically

assessed and managed. The risk assessment involves estimating the properties of the materials in the slopes,

calculating the stability of various slope geometries, and monitoring the performance of the slopes as the pit is

developed. The risk management involves making decisions on the actions to mitigate these risks. Warning systems

are described with emphasis placed on monitoring systems based on traditional and remote sensed data. The

application of a warning system in the Nanfen iron open pit mine in China is presented where a novel technique for

monitoring sliding forces on pre-stressed rock bolts was developed and successfully applied. In the future, risk

management systems will become automated and include smart sensors and materials that have self-adjusting

properties.

2. Decision Analytical Approach to Slope Stability Risk Assessment and Management

2.1. Definitions

Risk can be expressed in many different ways. The definitions used in this paper are based on the ISSMGE

recommended Glossary of risk assessment terms (TC32).

Danger (Threat): Phenomenon, natural or manmade, that could lead to damage

Hazard: Probability that a danger (threat) occurs within a given period of time

Consequence (Damage): Result of a hazard being realized

Vulnerability: Degree of loss to a given element or set of elements within the area affected by a hazard

Risk: Measure of the probability and severity of an adverse effect to life, health, property, or the environment

Following these definitions, risk can be expressed as:

i

ii CuTCPTPR ]|[][ (1)

where:

R is Risk

][TP is the hazard, defined as the probability that a particular threat occurs within a given period of time

i

i TCP ]|[ is the vulnerability, defined as the conditional probability that consequences iC occur given the threat

iC are consequences which can include for example economic damage, as well as those that affect human lives,

such as injuries and fatalities

iCu is the utility of consequences iC , defined as a function that describes a decision maker’s relative preferences

between attributes

2.2. Framework

Decision analysis provides a framework by which complex decision problems can be simplified, allowing one to

more clearly make decisions based on alternatives (Hammond et al. (2015).; Howard and Abbas (2015)). Figure 1 is

a graphical representation of decision making under uncertainty as proposed by Raiffa and Schlaifer (1964), Pratt et

al. (1965) and Stael von Holstein (1974). This process is actually also the standard decision making process used in

engineering in which one determines parameters, includes them in models and makes decisions based on the model

results. The updating cycles can, amongst other things, represent the observational method in geotechnical

engineering (Terzaghi (1961), Peck (1969), Einstein (1988)).

Figure 1. The Decision Analysis Cycle (after Einstein (1988))

Figure 2. Decision Analytical Approach to Natural Threat Risk Assessment and Management (after Einstein (1997))

The steps or levels in the decision analytical approach (Figure 2) are described in the following. Since this paper is

related to risk management, emphasis is placed on this level whereas the other levels are briefly described.

Level 1: Assess the State of Nature

In decision analytical terms, this level forms part of the information collection. This information pertains to the

factors that affect the stability of slopes in open pit mines. Slope instability initiation is complex and depends on a

great number of factors and the interaction between them. Some of these factors are shown in Figure 3.

Figure 3. Some Factors Affecting Slope Instability in Open Pit Mines

The geology of a mine site is usually well known because the investigations that led to the establishment of the mine

in the first place should provide a reasonable geological description of the site. In contrast, engineering properties of

soils and rocks that affect the stability of slopes are often less well known. Gravitational loads are the most

important loads affecting the stability of a slope in a mine, and the major resistance to failure is the shear strength of

the ground. This is a major concern of geotechnical engineers, since the strength parameters can vary significantly

even in small areas. The strength of a rock mass is affected by not only the intrinsic rock strength but also the

existence, and persistence of fractures and joint sets, patterns and networks. Furthermore, the percolation of pore

fluids have major effects on the stability, and subsurface flow regimes can be complex. In addition, natural events,

such as rainfall and earthquakes, and manmade factors, such as blasting, can serve as triggers to slope instabilities

(Karam (2005), Huang et al. (2012)).

Collecting information on the parameters that affect slope stability, or site characterization, is usually done through

exploration schemes. Exploration is defined as information collection that involves processes of induction based on

interpretations of regional geology and geologic history, as well as deduction based on site investigations and

measurements. Typically, information may comprise traditional techniques such as maps, photographs, boring logs,

topographical data, weather data and visual observations. Site characterization, however, requires the allocation of

resources, effort and money, both of which are usually scarce, and therefore a tradeoff is usually made between the

value of exploration and economics based on a cost benefit analysis. Since this forms part of the cost of a mine

operation, frequently not enough resources are allocated to site characterization as one would desire.

Level 2: Identify and Describe Threat

This involves both information collection and deterministic modeling. There are various techniques to assess slope

stability that range in complexity from simple heuristic models to statistical models based on historical data, to more

complex mechanical models which attempt to represent reality. A typical mode of slope failure in open pit mines

involves a block of material sliding on two or three planes of discontinuity, known as rock wedges. The stability

analysis of wedges in rock slopes involves resolution of forces in two or three dimensional space. The problem has

been extensively treated in, for example, Goodman and Taylor (1967), John (1968), Londe et al. (1969), Hendron et

al. (1971), Jaeger (1971), Hoek et al. (1973), Goodman (1976, 1989, 1995), Hoek and Bray (1977, 1981), Wittke

(1990), and Wyllie and Mah (2004). The methods used include stereographic projection technique, engineering

graphics, and vector analysis.

Level 3: Determine Probabilities and Combine with Threat to Determine Hazards

Uncertainties are inherent to geology and geotechnical engineering since they deal with the underground and thus

cannot be seen. Several categorizations of uncertainties have been proposed over the years that include Baecher

(1972, 1978), Einstein and Baecher (1982), Christian et al. (1994), and Lacasse and Nadim (1996). Einstein and

Karam (2001) discuss uncertainties in the context of slope stability risk assessment. It should also be noted that

when formally assessing uncertainties, this can be done both by the relative frequentist or the subjective approach.

These approaches and their applicability have been discussed by Baecher (1972), Einstein and Baecher (1982), and

Einstein (1995). The formal incorporation of uncertainties into the slope stability problem results in probabilities of

slope instabilities or hazards. These can range in from first and second order reliability analyses (Hasofer and Lind

(1974), Veneziano (1974), Ditlevesen (1981), Ditlevesen and Madsen (1995)), to full distribution probabilistic

analyses based on numerical techniques (Vanmarcke (1977), Low (1979), Low and Tang (1997), Griffiths and

Fenton (2004)). Examples of such studies for the stability of slopes in open pit mines include for example Riela et

al. (1999), Harr (1996), Duncan (2000), El-Ramly et al. (2002, 2006), Nadim (2007) as well as others.

Level 4: Risk Assessment

In Section 2.1, risk was defined as a measure of the probability and severity of an adverse effect to life, health,

property, or the environment or the product of the hazard and the potential worth of loss. Risk is therefore obtained

as combination of the quantified hazard with the quantification of consequences conditional on the hazard (eq. (1)).

It is worth noting that a particular hazard can have different consequences. The quantification of consequences

requires the identification of consequences, and associating an expression of loss with them. This expression is

usually in the form of a utility function (Ang and Tang (1975, 1984)), which is a dimensionless transformation that

describes the relative preferences of the decision maker towards different outcomes, as well as the decision maker’s

attitude towards risk, i.e. risk neutral versus risk averse. For a detailed discussion on utility, reference is made to for

example Keeney and Raiffa (1976) and Howard and Matheson (1984), and Howard and Abbas (2015).

Level 5: Risk Management (Decisions)

A decision is an irrevocable allocation of resources. Decisions in the slope instability problem concern measures that

can be taken to mitigate risk. These decisions, or actions, can range from construction countermeasures to

administrative procedures. Typical actions include:

(a) Passive countermeasures

Passive countermeasures reduce the vulnerability, resulting in a reduced risk 'R , where:

pasi

ii CuCuTCPTPR ]|['][' (2)

where:

]|[' TCP i is the reduced vulnerability

pasCu is the utility associated with the cost of the passive countermeasure

Other terms as defined for eq. (1).

Examples of passive countermeasures include galleries and nets.

(b) Active countermeasures

Active countermeasures reduce the hazard, resulting in a reduced risk 'R , where:

acti

ii CuCuTCPTPR ]|[]['' (3)

where:

][' TP is the reduced probability of threat

actCu is the utility associated with the cost of the active countermeasure

Other terms as defined for eq. (1).

Examples of active countermeasures include rock bolts, anchors, tie-backs and retaining structures.

(c) Warning systems

Warning systems mitigate risk by reducing consequences. They consist of devices capturing relevant signals, models

for relating the signal to potential threats, people and procedures interpreting the modeled results, evaluating

consequences and issuing warnings. Such warnings have then to be communicated to potentially affected areas and

lead to passive or active countermeasures.

Warning systems include the following components:

(i) Monitoring systems (data acquisition) that track a threat such as slope instability.

(ii) Communication systems (data transmission) that continually transit measurements to experts.

(iii) Models that predict (data analysis and interpretation) the threat in the short and long terms.

(iv) Alarm systems that transmit the warning signal(s) to the potentially affected parties efficiently and effectively

when a predefined alarm threshold is exceeded.

(v) Specific actions (procedures) that are implemented during the warning (evacuations routes, assembly points,

others), as well as those after the warning.

Figure 4 shows a flow chart for a warning system with the typical components involved.

Given the uncertainties involved in each of the components above, warning systems have a reliability associated to

them. That is to say that warning systems can on the one hand, fail to issue an alarm before a threat materializes, and

on the other hand issue false alarms. Well-designed warning systems attempt, to the extent possible, to reduce these

events so as not to lose credibility, and hence effectiveness. It is also important for warning systems to be flexible

and updatable both during an event/threat and as experience and technical capabilities increase.

Figure 4. Block Diagram for Warning System (after DiBiagio and Kjekstad (2007))

Monitoring is the key to slope instability assessment, management and mitigation. The objective of a landslide

monitoring program is to systematically collect, record and analyze qualitative and quantitative information. Designing

a monitoring program includes the following steps:

(a) Define the objectives of the monitoring program and select the type of measurements to be included, assigning

priorities to measurements.

(b) Decide on the measurement methods to be used, usually on a cost benefit basis, and select the appropriate

instruments.

(c) Determine the optimum instrumentation scheme by using, where possible, theoretical or empirical methods to

optimize the number and placement of instruments.

(d) Decide on the preferred method of data acquisition, e.g. manual or automatic recordings.

(e) Arrange for the proper installation, protection and marking of instruments and reference points in the field.

(f) Plan for the data flow, data management and analysis.

(g) Plan for the adequate maintenance of the monitoring system.

Traditionally, monitoring systems have been based on information collection using visual observations to look for

evidence of instability, coupled with surface and subsurface measurements to detect movements. While these

techniques still play an important role in monitoring instabilities they suffer from various drawbacks mostly related

to the fact that they can be localized. The use of remote sensed measurements is becoming more widespread with

technological advancements, and as these methods become more cost effective. The integration of Synthetic

Aperture Radar (SAR) and optical images, along with interferometric SAR (InSAR) techniques, are currently being

used to characterize instabilities. New techniques such as differential Synthetic Aperture Radar (DInSAR) and high

resolution image processing are also increasingly being used in risk assessment studies. Ground-based radar devices

such as Linear SAR (LISA) are capable of assessing the deformation field of an unstable slope in the areas

characterized by a high radar reflectivity. Near surface geophysical methods such as seismic, gravimetric, magnetic,

electric and electromagnetic, can be used to monitor hydrogeological phenomena, and electric and electromagnetic

survey techniques can be applied to areas with complex geology. These remote sensing tools are practical and for

many of them, affordable, particularly in open pit mines where consequences can be very detrimental. Table 1

shows some of the techniques, as well as their strengths and limitations.

Table 1. Remote sensing technologies: strength and limitations, after Hutchinson (2008), Lacasse (2008), and Lacasse and Nadim (2012)

System Applications Resolution Limitations Strengths

(DEM from all) Future

Photogrammetry

Terrestrial

Joint survey, scarp

and change

detection cm to m,

depending

on scale

Field of view, image

resolution, requirement for

surveyed positions, vegetation

obscuring

Rapid, cheap, long term

record, stereoscopic; build

DEMs and see terrain

conditions

Digital imagery,

high resolution

scanners and

video Airborne

Landslide

inventory and time

series analysis

LiDAR

Ground based

(Static) Landslide

monitoring,

landslide mapping,

topography

extraction, joint

surveys, moisture

detection

mm to cm

Humidity, distance limitations,

angular limitations,

reflectivity, vegetation

obscuring, Field of view

Multi-return LiDAR allows

earth model, very high

accuracy, high rate of

acquisition, perspective

views possible

Cost effective,

signal

processing

improvements,

possible

automated

feature

extraction

Ground based

(Mobile)

Airborne

(Fixed Wing)

Airborne

(Helicopter)

InSAR

Standard

Movement

detection and

monitoring, time

series

displacement, HR

movement

detection (ground

based)

mm

Visibility and shadowing,

need reflectance, doesn't

penetrate vegetation, limited

to slow movements

Large area survey, long term

monitoring, return frequency

affects use, comparison or

combination of ascending

and descending paths,

movement measurement,

rapid mapping of targeted More frequent

satellite Passes,

monitoring of

faster slope

instabilities PS

As above but only works with

stable reflectors, very

expensive

As above with mm accuracy

movement detection

Ground based

As above, but can monitor

faster movements, semi-

permanent installation and

view point is required

As above, and can pick up

larger movements

Table 1 (continued). Remote sensing technologies: strength and limitations, after Hutchinson (2008), Lacasse (2008), and Lacasse and Nadim (2012)

System Applications Resolution Limitations Strengths

(DEM from all) Future

Optical Satellite Images

Landslide

inventory and time

series analysis

10's cm to

10's m

Expensive, image quality can

be poor due to cloud cover

Landslide surveys, large area

coverage, historical record

since 1990's, change

detection, rapid mapping of

targeted areas

Higher

resolution

satellites to be

deployed, more

satellites will

increase

coverage and

frequency

Weather Radar

Precipitation

intensity, early

warning from

rainfall intensity

and accumulation

Depending

on

calibration

km

Calibration is required Helps map spatial

distribution of weather

Enhanced

mapping of

weather

systems,

cheaper systems

Others (Thermal IR, etc)

Low

Resolution

Vegetation Classification,

Water Content, Change

Detection

It is important to note that monitoring slope instabilities have to be coupled with continuous, and if possible real

time measurements on triggering events, such as rainfall, and induced vibrations. One also needs to consider the

different models of failure in interpreting the data and modes of failure in data interpretation and the setting of

threshold values to issue alarms.

Traditional landslide monitoring systems have been based on measuring movements. These techniques cannot

easily predict brittle slope failures or failure that change from ductile to brittle. Where a slope failure is brittle, an

observation of no movement could give a false sense of security. In Section 3, a case study is presented where a

warning system was successfully implemented in the Nanfen Open Pit Iron Mine in China. The warning system is

based on a monitoring system that uses a novel technique to measure forces to complement displacement, as well

as other, measurements.

Level 6: Information Model

Slope stability risk assessments, as well as standard geotechnical engineering practice involve the gathering of

additional information. This involves updating prior probabilities to result in posterior probabilities that reflect the

new information. This is usually done using Bayesian updating. It is possible and often desirable to check whether it

is worthwhile to collect additional information through the information modeling prior to actually going out and

obtaining the information. This is done through the process of pre-posterior or virtual exploration. This process has

been applied in the context of tunnel exploration planning in Karam et al. (2007a, 2007b), and for landslides in

Einstein et al. (2008).

3. Early Warning System: The Nanfen Open Pit Iron mine

Traditional landslide monitoring systems have often been based on displacements measurements because these are

easy to do, and the necessary equipment is widely available. The issue with measuring displacements is that for

brittle failures, early detection of movements comes too late. Monitoring forces, or stresses, is more desirable since

these reflect the kinematic characteristic of a slope. Force and stress measurements are however not very easy

because they form part of a natural system and are not easy to measure often requiring sophisticated methods.

A system to measure forces was developed at the China University of Mining and Technology, Beijing (SKLGDUE)

and first applied to the Three Gorges Project in China (He et al. (1999), He et al. (2014)). The basic principles of the

monitoring system are shown in Figure 5. A set of high-resolution sensors are installed at pre-selected measurement

locations, which are then connected to a data acquisition and transmission system, as shown in Figure 6. With small

radio antennas mounted at the measurement locations, they are connected through a base station to a wireless

receiver. The data received is transferred via satellite to a control station where data from all measurement locations

is analyzed, and the stability of the entire slope system is updated based on these measurements (He et al. (2009)).

Figure 5. The Remote Sliding Force Monitoring System

Figure 6. High Resolution Sensor and Data Acquisition and Transmission

The monitoring system was applied to the Nanfen Open Pit Iron mine in Liaoning Province, China. It is the largest

open pit iron mine in Asia, covering an area of approximately 3 km long by 2 km in wide. In 2008, the mine

underwent a series of expansions and the current production capacity is about 10 million tons of iron ore per year

(Lie et al. (2001), Shuangwei and Ketong (2001), Yang et al. (2012)). The mine consists of benches, each about 24

m high with an average slope angle of 46° on the western side (Figure 7). The total height of the slope is about 756

m.

Figure 7. Aerial View of Nanfen Open Pit Iron Mine

The Nanfen open pit iron mine is located in the south wing of Heibei mountain inversed anticline, and geology is

composed mainly of the Archean Anshan Group, Algonkian Liaohe Group, Sinian and Quaternary systems. The

slopes are typically intercepted by 5 to 6 joint sets, two of which have potential impact on stability on the heading

side: (1) Major Join Systems: these joints have an average attitude of 295/48, and the value of the roughness of the

joints is about 2-4 according to the Barton and Choubey (1977) classification system. These joints form the main

potential sliding surfaces on the heading side; (2) Secondary Joints Systems: these joints have an average attitude of

291/13, spreading extensively, and are characterized by small dip angles.

Twenty eight sets of remote monitoring systems were installed at various re-selected locations in the mine as shown

in Figure 8.

Figure 8. Outline of Nanfen open pit iron mine: sliding force monitoring points on the slope

With continuous monitoring, the system was continually field calibrated and refined, which led to the development

of a strong predictive tool. In October 2010, at monitoring location No. 334-4 (see Figure 8), large variations

(increase) in sliding force were measured, and on October 5, 2011, a large slope failure occurred. The spatial

distribution of monitoring points where the instability took place is shown in Figure 9.

Figure 9. Spatial Distribution of Landslide at Nanfen Mine

Figure 10 shows the monitoring stations and the geometry of the landslide that ultimately occurred.

Figure 11shows the continuous measurements of sliding force, the cumulative amount of mining, as well as rainfall

data in the days prior and post the landslide event. When combined, these provide an early warning system based on

which actions, such as evacuations can be taken.

(b)

i

cd e f

a

Scale

(c)

b c d e f g i j

250°

Figure 10. Monitoring Stations and the Geometry of the Landslide

Figure 11. Measurements of Sliding Force, Cumulative Mining, and Rainfall Data Prior and Post Landslide

A more detailed timeline of events prior to the occurrence of the 5 November 2011 landslide is shown in Table .

Table 2. Timeline and Observations Prior to 5 October 2011 Landslide at Nanfen Mine

Date Laboratory Observations Field Observations Actions

30

September

2011

Monitored forces at location

No. 334-4 are very small, and

monitoring curve tends to a

straight horizontal line,

indicating that the slope was

relatively stable

None None

1 October

2011

Sliding forces show a clear

upward trend.

Field investigations did not find

any surface cracks and other

signs of slippage

None

2 October

2011

Sliding forces show a

significant increase particularly

at locations No. 322-334

Micro-fissures and three cracks

appear on the surface of the

rock slope surface with a width

of 15-40 cm and a length 1.5-5

m

None

3 October

2011

Sliding forces continue to

increase

The three cracks developed to

become longer and wider, with

a width of 25-60 cm and a

length of 3-9 m.

Mining activities were stopped

and personnel and equipment

were evacuated. These

measures are reflected in

reduction of the cumulative the

mining (Figure 11).

4 October

2011

Sliding forces, particularly at

location No. 334-4 continue to

rise although at a lesser rate

Cracks continue to extend and

propagate.

The footwall at stope at 322-

334 platform was squeezed and

destroyed.

Mining activities continue to

be halted as the slope is still

deemed unstable

5 October

2011

Sliding forces at location No.

334-4 reduce abruptly from

1700kN to 1400kN indicating

slope rupture

Intense rainfall event,

(accumulated rainfall 31.8 mm

in 3 hours)

A significant landslide with

height 36m and length 50m

None

The measurement of sliding force in the rock mass served, successfully, as a timely warning system in the case of

the October landslide at the Nanfen Mine. Because of the continuous monitoring system, it was possible to take

decisive measures and prevent casualties and property losses. While it is true that there are economic opportunity

costs to the cessation of mining activities, losses from the landslide occurring during mining operations would have

been far greater, possibly including loss of lives.

The high-resolution sliding force monitoring system developed at SKLGDUE provides a rapid and accurate early

warning system for open pit mines. Monitoring sliding forces can better reflect the complex systems mines exist in

which include natural systems, such as rainfall, erosion, and others, as well as manmade systems, such as excavation

and blasting as the mine is developed.

4. Future Trends

With increasing global satellite coverage and access to open and in many occasions free data, remote sensing

techniques are bound to play a more significant role in slope stability risk assessments in the future. Technological

advancements will lead to the development of cheaper and more reliable sensors that can be deployed as part of

monitoring systems. Increasing computing power and cheap storage are also likely to play more significant roles in

the future enabling the acquisition, storage and analysis of big data. In the future, the risk assessment and

management procedure described in this paper may become fully automated. Smart sensors can issue alarms based

on the results of the risk assessment. The properties of materials used in countermeasures can also become self-

adjusting based on the risk assessment. For example, the strength and stiffness of rock bolts can vary in response to

potential instabilities.

5. Conclusions

Decisions regarding mine operation, and even which mines to open and close, are based on costs of operation,

amount of ore to be extracted, and the value of the product on world markets. The economy of scale has made large

scale open pit mines or underground large caving operations attractive for the recovery of low grade mineral

deposits. These massive operations have placed new demands on rock engineers to design slopes and underground

mines on a scale not attempted before. Modern management methods, such as the one described in this paper, can

and should be used to systematically assess and manage the risks associated with slope instabilities. Warning

systems are effective tools to mitigate slope instability risks in mines. As remote sensed data becomes more widely

available, and cheaper to collect, these techniques are bound to play a more significant role in monitoring systems of

the future. The Nanfen Iron Ore case study showed that warning systems can be successfully used to prevent

substantial economic losses, and possibly save lives.

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