The Application of a Proposed Risk Assessment Approach on Rock Failure Hazard on Manshiet

Rock failure is one of the most geomorphological hazards that cause considerable damages in different regions every year. To effectively mitigate this hazard, new methodologies are needed to develop a better understanding of rock failure assessment and management. In recent years, risk analysis and assessment have become an important tool in addressing uncertainty. However, the all-embracing perspective of the notion of risk is not an easy task to undertake since it requires data availability at different scales and a multidisciplinary point of view. The research aims to analyse the factors causing the occurrence of rock failure by analysing hazard and vulnerability factors using a proposed risk assessment approach to be applied on Mansheit Nasser district. The research uses a quantitative analytical risk assessment methodology. The methodology used to assess the risk of rock failure in Mansheit Nasser district is to estimate the hazard (H) and the vulnerability (V). The risk is calculated by using equations mentioned in the research and the arc GIS programme to prepare maps. The equation is used to standardise the value of risk factors and unify their weights. The research concludes that the rock failure risk index (RFRI) determines the most vulnerable areas to rock failure in Manshiet Nasser to estimate the elements at risk (E).


Introduction
The research aims to analyse the factors that cause the occurrence of rock failure. It helps to estimate the severity of risks and analyse the vulnerability factors for identifying risk elements of rock failure. The proposed methodology is drawn from the review of several previous researches, to help solve the deficiencies in the previous risk assessment methodologies, which omitted the input identification of rock failure risk assessment. This methodology will be applied on Mansheit Nasser District using the GIS programme to extract and prepare maps and equations.
Risk is the probability and the amount of harmful consequences or expected losses resulting from interactions between natural or human induced hazards and vulnerable conditions (UN/ISDR, 2004). Rock failure hazards include rockfall and landslide. Landslide is a natural hazard that may produce deaths, injuries, and direct and indirect economic losses, so it is important to take them into account in town and country planning aiming to reduce these consequences (Guillard and Zezere, 2012). Rockfall means falling blocks of rocks sequentially. Figure 1 shows the difference between landslide and rockfall. tal Planning Department, Faculty of Urban and Regional Planning, Cairo University, Teaching iro University Campus, Gamaa Street, Giza, Egypt, tal Planning Department, Faculty of Urban and Regional Planning, Cairo University, Lecturer, sity Campus, Gamaa Street, Giza, Egypt. .fa5ri@yahoo.com. //dx.doi.org/10.5755/j01.erem.76.2.25490 failure is one of the most geomorphological hazards that cause considerable damages in nt regions every year. To effectively mitigate this hazard, new methodologies are needed to p a better understanding of rock failure assessment and management. In recent years, risk is and assessment have become an important tool in addressing uncertainty. However, the bracing perspective of the notion of risk is not an easy task to undertake since it requires vailability at different scales and a multidisciplinary point of view. The research aims to e the factors causing the occurrence of rock failure by analysing hazard and vulnerability using a proposed risk assessment approach to be applied on Mansheit Nasser district. The ch uses a quantitative analytical risk assessment methodology. The methodology used to the risk of rock failure in Mansheit Nasser district is to estimate the hazard (H) and the ability (V). The risk is calculated by using equations mentioned in the research and the arc rogramme to prepare maps. The equation is used to standardise the value of risk factors and their weights. The research concludes that the rock failure risk index (RFRI) determines the ulnerable areas to rock failure in Manshiet Nasser to estimate the elements at risk (E).
arch aims to analyse the factors that cause the occurrence of rock failure. It helps to estimate the sks and analyse the vulnerability factors for identifying risk elements of rock failure. The proposed is drawn from the review of several previous researches, to help solve the deficiencies in the assessment methodologies, which omitted the input identification of rock failure risk assessment. logy will be applied on Mansheit Nasser District using the GIS programme to extract and prepare ations. the probability and the amount of harmful consequences or expected losses resulting from etween natural or human induced hazards and vulnerable conditions (UN/ISDR, 2004). Rock s include rockfall and landslide. Landslide is a natural hazard that may produce deaths, injuries, d indirect economic losses, so it is important to take them into account in town and country ing to reduce these consequences (Guillard and Zezere, 2012). Rockfall means falling blocks of tially. Figure 1 shows the difference between landslide and rockfall.
e difference between landslide and rockfall assessment process is the decision making process. It detects whether the existing risks are t, and whether the measures to address such risks are adequate or not. If the answer is negative, the easures have to be implemented (Fell et al., 2005). The rock failure risk assessment has a great n decision-making processes, where risk management process depends basically on critical rom risk assessment. The urban areas in Egypt are affected mostly by the occurrence of rock result of the imbalance between land use and geo-environmental hazards, there is a relative neglect of geo-environmental risks on urban areas in Egypt. The applied methodologies for assessing the The risk assessment process is the decision making process. It detects whether the existing risks are possible or not, and whether the measures to address such risks are adequate or not. If the answer is negative, the alternative measures have to be implemented (Fell et al., 2005). The rock failure risk assessment has a great importance in decision-making processes, where risk management process depends basically on critical information from risk assessment. The urban areas in Egypt are affected mostly by the occurrence of rock failure. As a result of the imbalance between land use and geo-environmental hazards, there is a relative neglect of the impact of geo-environmental risks on urban areas in Egypt. The applied methodologies for assessing the risk of rock failure for urban areas in Egypt are not appropriate, because these risks are met in limited spatial conditions and technical engineering methods.
Some studies tackle the field of rock collapse risk assessment. Roslee et al. (2017) suggested a methodology for calculating and estimating the hazard only, but it neglected the vulnerability assessment that makes the evaluation of results inaccurate. Another research tackled the assessment of risk by proposing an approach to determine hazard assessment of inputs and outputs, but it did not specify the vulnerability assessment of inputs and outputs (Effat and Hegazy, 2014). Mrozek et al. (2016) proposed that the future rock failure will have causal factors such as rock failure in the past, so it is hard to apply this approach because the selected region has not had previous rock failure. Papathoma et al. (2007) suggested a methodology for assessing the risk of rock failure by focusing on calculating the vulnerability of population and urban areas, but this approach did not consider the specificity of the inputs of risk assessment and omit the severity of hazard. According to the indicators, criteria and stages resulting from the analysis of previous researches are combined in one proposed approach to solve the defects.

Factors causing and triggering the occurrence of rock failure
The assessment process is affected by several factors. These factors are the causal and motivational factors of rock failure occurrence, the size of available data, the size of the study area, and the type of ancient and modern rock failure occurring in the area in question. The factors of rock failure include: _ Environmental factors: geology, geomorphology, soil, topography, hydrological study and land cover; _ Topographic attributes have been identified as the most important factor in controlling the initiation and distribution of landslides and rock failure (Zhang et al., 2012); _ Causing and motivating factors: earthquakes, volcanoes and rain; _ Elements at risk: buildings, urbanisation, road network and basic facilities; _ Urban characteristics: construction materials, age of building, number of floors and number of households in each building; _ Hazard characteristics: historical record, types of constituents, and pattern of movement and repetition; _ Socio-economic factors, like increasing population and concentrations of settlements on endangered areas (Azzam et al., 2010); and _ Anthropogenic activities and land use: the explosives, used for quarry activities, cause cracks, fractures and faults activation, which in turn increase the rate of block movement, and the rock excavation process in these quarries that creates unstable vertical cliffs (Khaled et al., 2008).

Materials and Methods
The maps, aerial photographs and reports of the study area, such as topographic and geological maps, are collected and analysed to identify the most important characteristics of rock failure and land use. The ArcGIS programme is used for this process because of its high accuracy in doing analysis. The research focuses on spatial analysis to ensure saving time and effort. It proposes many ways to assess the risk of rock failure depending on the study area, research methods, study objective and physical possibilities.
SRTM satellite data is used to derive elevation, slope angles and flow network using the ArcGIS software.
The analysis was performed in the study area (approximately 4.52 km 2 ). The study area was divided into cells (10 m x 10 m) (a total of 45,723 pixels).

Standardising the measurement and determination of the weights of causal and motivating factors
Rock failure is considered a complex operation because of the lack of a complete historical record on the one hand and the difficulty of identifying the causative factors on the other hand. They are different according to the specificity of each region (Pareta and Kumar, 2012). A distinction must be made between the immediate and long-term factors of rock failure. The immediate causes include vibrations (such as those caused by the passage of trains, trucks or earthquakes) and heavy rains, while the long-term causes include gradual and slow change in slope. The common difficulty in each multi-criteria analysis is the number of factors to consider. There are many factors that cause rock failure, but the factors chosen for this approach are shown in Figure 2. The risk of rock failure is assessed by calculating a combination of non-similar factors in the measuring 5 method. The type and nature of the rock layer are qualitative or descriptive, while the slope inclination is an 6 angle measured by degrees (Effat and Hegazy, 2014). The factors were converted into a scale from 0 to 1 degree 7 of vulnerability according to the following equation (1) (Effat and Hegazy, 2014). This method was selected due 8 to its simplicity to be applied. Table 1 shows an example of relative weights using the linear transform numerical 9 calculation and setting (Effat and Hegazy, 2014 The risk of rock failure is assessed by calculating a combination of non-similar factors in the measuring 5 method. The type and nature of the rock layer are qualitative or descriptive, while the slope inclination is an 6 angle measured by degrees (Effat and Hegazy, 2014). The factors were converted into a scale from 0 to 1 degree 7 of vulnerability according to the following equation (1) (Effat and Hegazy, 2014). This method was selected due 8 to its simplicity to be applied. Table 1 shows an example of relative weights using the linear transform numerical 9 calculation and setting (Effat and Hegazy, 2014). The risk of rock failure is assessed by calculating a combination of non-similar factors in the measuring 5 method. The type and nature of the rock layer are qualitative or descriptive, while the slope inclination is an 6 angle measured by degrees (Effat and Hegazy, 2014). The factors were converted into a scale from 0 to 1 degree 7 of vulnerability according to the following equation (1) (Effat and Hegazy, 2014). This method was selected due 8 to its simplicity to be applied. Table 1 shows an example of relative weights using the linear transform numerical 9 calculation and setting (Effat and Hegazy, 2014). The risk of rock failure is assessed by calculating a combination of non-similar factors in the measuring 5 method. The type and nature of the rock layer are qualitative or descriptive, while the slope inclination is an 6 angle measured by degrees (Effat and Hegazy, 2014). The factors were converted into a scale from 0 to 1 degree 7 of vulnerability according to the following equation (1) (Effat and Hegazy, 2014). This method was selected due 8 to its simplicity to be applied. Table 1 shows an example of relative weights using the linear transform numerical 9 calculation and setting (Effat and Hegazy, 2014). 10 The risk of rock failure is assessed by calculating a combination of non-similar factors in the measuring method. The type and nature of the rock layer are qualitative or descriptive, while the slope inclination is an angle measured by degrees (Effat and Hegazy, 2014). The factors were converted into a scale from 0 to 1 degree of vulnerability according to the following equation (1) (Effat and Hegazy, 2014). This method was selected due to its simplicity to be applied. Table  1 shows an example of relative weights using the linear transform numerical calculation and setting (Effat and Hegazy, 2014). Where: W j is the normal weight of the factor; n is the number of factors taken into consideration of the total rank; r j is the order of the factor and its rank; Σ(n -r k + 1) is the total sum of weight.
The weighted linear combination (WLC) method is used to combine factors where the landslide susceptibility index (LSI) of each pixel is calculated by adding the weight of each factor multiplied by the weight of the layer as shown in equation (2) (Effat and Hegazy, 2014): (2) (Zhou et al., 2016;Kanungo and Sarkar, 2004) Where: LSI is the landslide susceptibility index of a specified pixel; W j is the weight of factor j; X ij is the classification (standard value) of class i in factor j; N is the total number of factors.

General equation for calculating and assessing risks
Equation (3) is used and applied on all types of risks, but the difference lies in the method of calculating and assessing the hazard according to its type. The risk calculations are changed according to the type, duration, start and end time, risk intensity, extension, and spatial impact (Westen, 2014). The vulnerability is expressed in a digital scale of 0:1.

R = H× V × E (3)
Where: H is hazard; V is vulnerability; E is elements at risk; R is risk assessment.
Risk refers to measuring the probability and severity of an adverse effect on life, health, property, or the environment quantitatively (Fell et al., 2005). Risk assessment is the entire process of analysing risk and evaluating results according to the risk tolerance criteria (Vinnem and Røed, 2019).
Hazard refers to the probability that a particular danger (threat) occurs within a given period of time. (Costard, 2008).
Vulnerability refers to the potential degree of loss (damage) to a given element or risk elements that result from the occurrence of a natural phenomenon of a given magnitude. Vulnerability is expressed on a numerical scale from 0 (no damage) to 1 (total damage) (Roslee et al., 2017).
Elements at risk are population, buildings and engineering works, infrastructure, environmental features, and economic activities in the area affected by a hazard (Fell et al., 2005).

Calculation of vulnerability
The calculation is formulated through the development of a database of vulnerable elements (population and urban areas), as well as the history of previous rock failure done by field surveys. The factors causing rock failure in urban areas that are identified as hazardous highly are determined, and a database is created including factors of rock failure occurrence: _ physical factors (building materials); _ social status (injuries, deaths, safety, loss of housing and public awareness); and _ effect on the environment (impact period and daily management).
Moreover, the values are generated for all vulnerability elements of rock failure ranging from 0:1, as shown in Table 2. The rock failure distribution map is used to analyse the factors to generate a vulnerability degree map, where it is produced based on field studies and satellite image interpretations in order to determine the locations of rock failure in the study area. The linear transform numerical calculation is used to reanalyse this data starting from 0.00 to 1.00 by applying equation (4) and its example in Table 3

Application of methodology on Manshiet Nasser (study area)
Manshiet Nasser is situated on the rocky slopes of the Mouktam Hills range, which forms an eastern physical boundary to Cairo city; it was the main source of limestone used in the construction of buildings in old Cairo before the use of red bricks and concrete. It was completely empty of housing except for some nests in the western part of the highway. At the end of the 1960s, the area began to witness an intensive displacement of the population to the old quarries in Manshiet Nasser, as they began to build houses indiscriminately without considering the stone quarries and leaving any safety distance to consider the geological situation. The buildings had no public sanitation and the population used to drain directly on the rocks. These factors affected the degree of cohesion and led to the occurrence of several landslides that killed several inhabitants. The most famous rock failure dated 1993 and 2008 (Mostafa et al., 2009). This area has become a home for a large community of garbage collectors (El Zabbaleen) who occupied the top of the mountain hills. It had a residential density of more than 228 persons per square kilometre and was continuing to grow in density (Slum Development Fund, 2016).
Manshiet Nasser is one of the most dangerous slums in Egypt and its area reaches 7.2 Km² (GTZ-Egypt, 2016). Figure 3 shows the location of Manshiet Nasser in Cairo Governorate that is a mega slum of 800,000 to 1 million people (Scribol, 2010).
One of the most important problems in Manshiet Nasser is the failure of huge rock blocks from the high parts of the area on the residential buildings in the lower parts, as happened in El-Duwaiqain in 2008.
Such an accident caused the death of more than one hundred people after one of the huge rocks collapsed on their homes (Slum Development Fund, 2016). Manshiet Nasser is one of the most prone to rock failure areas in Egypt, where the rocky edge of Mount Mokattam has fallen more than once, as in 1993 and 2008, when the mountain of Mokattam collapsed on the slum residential area below the mountain. This occurred due to the following factors: _ The edge of the mountain had several cracks, which increased by the earthquake of magnitude 5.6 Richter in October 1992 (Slum Development Fund, 2016). The NW trend was considered as the major active trend in Egypt. Such records showed that the area was vulnerable to seismic activity that might reach 4-5 on the Richter scale.
_ Most of stones were cut with limestone filled with caves and cracks. Their size increased when exposed to water, pressed on the edge rocks, and led to failure.
_ In 1993, the rainfall coincided with the edge of the mountain, causing the water to break into the cracks and reach the friable soil forming a viscous surface that led to rock failure.
_ There are buildings built on the edge of the mountain causing additional stresses that made the mountain's edge fall.
_ The non-technical implementation of the sewage network has led to leakage of water into the moun-

5
western part of the highway. At the end of the 1960s, the area began to witness an intensive displacement of the 2 population to the old quarries in Manshiet Nasser, as they began to build houses indiscriminately without 3 considering the stone quarries and leaving any safety distance to consider the geological situation. The buildings 4 had no public sanitation and the population used to drain directly on the rocks. These factors affected the degree 5 of cohesion and led to the occurrence of several landslides that killed several inhabitants. The most famous rock 6 failure dated 1993 and 2008 (Mostafa et al., 2009). This area has become a home for a large community of 7 garbage collectors (El Zabbaleen) who occupied the top of the mountain hills. It had a residential density of more 8 than 228 persons per square kilometre and was continuing to grow in density (Slum Development Fund, 2016). 9 Manshiet Nasser is one of the most dangerous slums in Egypt and its area reaches 7.2 Km² (GTZ-Egypt, 10 2016). Figure 3 shows the location of Manshiet Nasser in Cairo Governorate that is a mega slum of 800,000 to 1 11 million people (Scribol, 2010 Manshiet Nasser is one of the most prone to rock failure areas in Egypt, where the rocky edge of Mount 21 Mokattam has fallen more than once, as in 1993 and 2008, when the mountain of Mokattam collapsed on the 22 slum residential area below the mountain. This occurred due to the following factors: 23  The edge of the mountain had several cracks, which increased by the earthquake of magnitude 5.6 24 Richter in October 1992 (Slum Development Fund, 2016). The NW trend was considered as the major 25 active trend in Egypt. Such records showed that the area was vulnerable to seismic activity that might 26 reach 4-5 on the Richter scale. 27  Most of stones were cut with limestone filled with caves and cracks. Their size increased when exposed 28 to water, pressed on the edge rocks, and led to failure. 29  In 1993, the rainfall coincided with the edge of the mountain, causing the water to break into the cracks 30 and reach the friable soil forming a viscous surface that led to rock failure. 31  There are buildings built on the edge of the mountain causing additional stresses that made the 32 mountain's edge fall. 33  The non-technical implementation of the sewage network has led to leakage of water into the mountain's 34 surface; in addition, it reached the festering soil inside the mountain. 35  The presence of quarries near the scene using explosives (dynamic loads) affected the balance of the 36 mountain as well as the use of heavy equipment in the drilling by the construction companies (Ministry 37 of Petroleum, 2009). 38 Rock failure triggers are used as independent variables to prepare a map of the probability of rockfall. A 39 digital elevation model (DEM) is created to extract variables that are being used in this study such as slope angle 40 and slope direction. 41 42 The used methodology to calculate and assess the risk of rock failure 43 44 A GIS-based (spatial) multi-criteria evaluation (SMCE) analysis was used in this study to combine the 45 information from several criteria (factors) to form a single index of evaluation. Based on the available data, the 46 landslide triggering factors were identified, so the rock failure susceptibility index (RSI) map can be produced 47 (Effat and Hegazy, 2014). 48 tain's surface; in addition, it reached the festering soil inside the mountain.
_ The presence of quarries near the scene using explosives (dynamic loads) affected the balance of the mountain as well as the use of heavy equipment in the drilling by the construction companies (Ministry of Petroleum, 2009).
Rock failure triggers are used as independent variables to prepare a map of the probability of rockfall. A digital elevation model (DEM) is created to extract variables that are being used in this study such as slope angle and slope direction.
The used methodology to calculate and assess the risk of rock failure A GIS-based (spatial) multi-criteria evaluation (SMCE) analysis was used in this study to combine the information from several criteria (factors) to form a single index of evaluation. Based on the available data, the landslide triggering factors were identified, so the rock failure susceptibility index (RSI) map can be produced (Effat and Hegazy, 2014). Figure 4 shows the proposed methodology made by the authors to calculate and assess the risk of rock failure. It was developed by reviewing previous risk assessment methodologies referred to in the following research (Fell et al., 2005;AGS, 2002;Roslee et al., 2017).  Figure 4 shows the proposed methodology made by the authors to calculate and assess the risk of rock 1 failure. It was developed by reviewing previous risk assessment methodologies referred to in the following 2 research (Fell et al., 2005;AGS, 2002;Roslee et al., 2017). 3 4 5 Fig. 4 The proposed methodology made by the authors to calculate and assess the risk of rock failure 6 7 Hazard assessment and estimation (H) 8 9 There is a common difficulty encountered in every multi-criteria analysis, which is the number of factors to 10 be considered (Ladas et al., 2007). The following factors were selected to assess and calculate the severity of 11 rock failure hazard (H) in the study area because of being a motivation and a cause for this occurrence. These 12 factors vary from region to region and from risk to another, so the measurement must be standardised. Their 13

Hazard assessment and estimation (H)
There is a common difficulty encountered in every multi-criteria analysis, which is the number of factors to be considered (Ladas et al., 2007). The following factors were selected to assess and calculate the severity of rock failure hazard (H) in the study area because of being a motivation and a cause for this occurrence. These factors vary from region to region and   It is the Holocene deposits, which are formations of gravel, sand, limestone fragments and alluvial deposits in the valleys (Abd Elhameed, 2004).

Deposits of the valleys
It is located within the formations of Oligocene, occupies 9.1% of the total surface area of the plateau, and contains gravel, coarse sand, soft coherent bright colours, predominantly red, in the areas around the faults.

Red Mountain geology formation
It is a composition of the Eocene era. It is characterised by the presence of brown clay that is easy to divide. The clay overlaps with limestone that is high in its content of lime and sand.

Maadi geology formation
Middle Eocene formations are known as Mouktam formations and are characterised by an increase in the proportion of gypsum in limestone rocks that raises their ability to create caves filled with clay, the layers of which may leak water when exposed.

Mouktam geology formation
There are many types of limestone in the plateau of Mouktam, in terms of type, thickness, and features. It is concentrated on the western edges east to the Citadel of Mohamed Ali along Salah Salem road and in the area of El-Duwaiqa, characterised by yellowish-white colour and divided into sand-limestone, clay-limestone, dolomitic limestone, clay-limestone-Marley, and chalky limestone (Abd Elhameed, 2004).

Analysis of hazard factors (H)
1 Slope. The slope angle is directly related to rock failure. It is frequently used in preparing susceptibility maps (Lerici et al., 2002). The higher the slope angle value, the steeper the terrain. The slope is one of the most important factors affecting the stability of slopes in the area of Manshiet Nasser, where it ranges from 3 to 45 degrees and the steepest area is El-Zarayeb and El-Masaken areas as shown in Figure 5. The slope angle values were derived from the SRTM digital elevation model using the spatial analyst Arc GIS10.1.
2 Previous Rock Failure. Figure 6 shows the locations and dates of major previous rock failure incidents and their locations, which are more susceptible to the occurrence of rock failure again.
3 Geology. Landslides are greatly controlled by the lithology properties of the land surface. Since different lithological units have different landslide susceptibility values, they are very important in providing data for susceptibility mapping (Pourghasemi, 2012). The lithology in Manshiet Nasser consists of clay, sandy clay, Nile deposits, Wadi deposits, sandstone, sand gravel siltstone, and clay stone in addition to vast zones of limestone and chalky limestone as shown in Figure 7. Table 5 shows the geology formation of Manshiet Nasser.
4 Topography. The topography is a very important factor because it is controlled by several geologic and geomorphological processes (Ayalew et al., 2004). The topography of Manshiet Nasser ranges from 11 to 220 meters as shown in Figure 8. The areas on El Mouktam Mountain, which are El-Duwaiqa and Wadi Pharaon, are the most elevated and the most vulnerable to rock failures. The SRTM digital elevation model was used in this study.
5 Distance from a drainage system. Figure 9 shows the drainage systems of the study area, where the non-technical implementation of the sewage network leads to leakage of water into the mountain's surface and thus reaches the festering soil inside the mountain.
6 Steep rock edge. Figure 10 shows the areas located below and above the mountain edges, which have not considered the application of the allowed safety distance. The safety distance is equal to the length of the rocky slope, making it one of the most dangerous areas for the population and urban areas.
According to the analysis of hazard factors, Figure 11 shows hazard severity categories, where the highest hazard severity is the highest elevation, located nearby the steep mountain edges (Mouktam Mountain) and fault zones. Most of it is mountainous terrain with a geological formation of limestone permeating with clay located on previous rock failure zones. However, these indicators should be compared with the vulnerability analysis to assess risk accurately.  Fig. 5 The slope map of the study area Fig. 6 Previous rock failure in the study area Fig. 7 The geology map of the study area Fig. 8 The topography map of the study area According to the analysis of hazard factors, Figure 11 shows hazard severity categories, where the highest 2 hazard severity is the highest elevation, located nearby the steep mountain edges (Mouktam Mountain) and fault 3 zones. Most of it is mountainous terrain with a geological formation of limestone permeating with clay located 4 on previous rock failure zones. However, these indicators should be compared with the vulnerability analysis to 5 assess risk accurately. 6 7 Fig. 5 The slope map of the study area Fig. 6 Previous rock failure in the study area Fig. 7 The geology map of the study area Fig. 8 The topography map of the study area According to the analysis of hazard factors, Figure 11 shows hazard severity categories, where the highest 2 hazard severity is the highest elevation, located nearby the steep mountain edges (Mouktam Mountain) and fault 3

Fig. 6. Previous rock failure in the study area
zones. Most of it is mountainous terrain with a geological formation of limestone permeating with clay located 4 on previous rock failure zones. However, these indicators should be compared with the vulnerability analysis to 5 assess risk accurately. 6 7 According to the analysis of hazard factors, Figure 11 shows hazard severity categories, where the highest 2 hazard severity is the highest elevation, located nearby the steep mountain edges (Mouktam Mountain) and fault 3 zones. Most of it is mountainous terrain with a geological formation of limestone permeating with clay located 4 on previous rock failure zones. However, these indicators should be compared with the vulnerability analysis to 5 assess risk accurately. 6 7  According to the analysis of hazard factors, Figure 11 shows hazard severity categories, where the highest 2 hazard severity is the highest elevation, located nearby the steep mountain edges (Mouktam Mountain) and fault 3 zones. Most of it is mountainous terrain with a geological formation of limestone permeating with clay located 4 on previous rock failure zones. However, these indicators should be compared with the vulnerability analysis to 5 assess risk accurately. 6 7  According to the analysis of hazard factors, Figure 11 shows hazard severity categories, where the highest 2 hazard severity is the highest elevation, located nearby the steep mountain edges (Mouktam Mountain) and fault 3 zones. Most of it is mountainous terrain with a geological formation of limestone permeating with clay located 4 on previous rock failure zones. However, these indicators should be compared with the vulnerability analysis to 5 assess risk accurately. 6  According to the analysis of hazard factors, Figure 11 shows hazard severity categories, where the highest 2 hazard severity is the highest elevation, located nearby the steep mountain edges (Mouktam Mountain) and fault 3 zones. Most of it is mountainous terrain with a geological formation of limestone permeating with clay located 4 on previous rock failure zones. However, these indicators should be compared with the vulnerability analysis to 5 assess risk accurately. 6 According to the analysis of hazard factors, Figure 11 shows hazard severity categories, where the highest 2 hazard severity is the highest elevation, located nearby the steep mountain edges (Mouktam Mountain) and fault 3 zones. Most of it is mountainous terrain with a geological formation of limestone permeating with clay located 4 on previous rock failure zones. However, these indicators should be compared with the vulnerability analysis to 5 assess risk accurately. 6

Vulnerability assessment
The elements' value at risk was estimated to assess and calculate the vulnerability of urban areas and population. As for urban areas, the vulnerability of land uses, building age, number of floors, building conditions, construction materials, basic facilities, and road networks were studied. However, as for population, the vulnerability in each building and the population density in the study area were studied. Their measurement was standardised to conclude the vulnerability index map of the elements at risk. Table 6 shows the vulnerability factors and their weight, where the value of each category was changed to their relative weight in order to standardise all factors to facilitate the application of the general formula for risk assessment.
The hazard severity assessment map of the study area and its categories assessment ents' value at risk was estimated to assess and calculate the vulnerability of urban ar s for urban areas, the vulnerability of land uses, building age, number of floors, b nstruction materials, basic facilities, and road networks were studied. However, as for pop lity in each building and the population density in the study area were studied. Their measu sed to conclude the vulnerability index map of the elements at risk. Table 6 shows the vulne heir weight, where the value of each category was changed to their relative weight in o l factors to facilitate the application of the general formula for risk assessment.

Analysis of vulnerability factors(V)
1 Population density. El-Masaken area is considered one of the most densely populated areas, ranging from 500 to 750 person/acre, followed by Al-Zaraib area. The population density in El-Duwaiqa area and the extension areas is reduced as shown in Figure 12.
2 Land uses. When the vulnerable populations are at risk, the locations of buildings should be identified, such as kindergartens, hospitals, nursing homes, schools and their distances to services (civil defence and police) as shown in Figure 13. Meanwhile, the building used for activities in which the population has longer hours during the day is the most vulnerable.
3 Construction materials and type. The buildings with a concrete structure, which represent 62% of the area, are the least vulnerable to rock failure as shown in Figure 14.
. 11 The hazard severity assessment map of the study area and its categories ility assessment elements' value at risk was estimated to assess and calculate the vulnerability of urban areas and on. As for urban areas, the vulnerability of land uses, building age, number of floors, building ns, construction materials, basic facilities, and road networks were studied. However, as for population, erability in each building and the population density in the study area were studied. Their measurement dardised to conclude the vulnerability index map of the elements at risk. Table 6 shows the vulnerability nd their weight, where the value of each category was changed to their relative weight in order to ise all factors to facilitate the application of the general formula for risk assessment.  4 Building conditions. The buildings with bad conditions, which represent 14.88% of the area, are the most vulnerable to rock failure as shown in Figure 15.
5 Building heights. The tallest buildings represent the highest vulnerability, where more than 5 floors are constructed as shown in Figure 16.
6 The age of buildings. The study of the age of buildings is important to determine their vulnerability to rock failure, as old buildings are more vulnerable compared with modern buildings; the term modern refers to the period from 2011 until now as shown in Figure 17.
The following vulnerability map as shown in Figure 18 shows the highest vulnerability zones that are affected by the risk of rock failure. These zones are densely populated and contain degraded poor houses that are constructed by weak building materials such as mud and wood without ceiling. In addition, they mainly serve vital activities, whether economic or social, while they are located on roads with a poor dirty status.
Moreover, the map shows that the northern area of Manshiet Nasser (study area) is the most vulnerable, because of the high population density and the status of houses that are degraded, poor and constructed by weak building materials such as mud and wood without ceilings. constructed as shown in Figure 16. 20 21 6. The age of buildings. The study of the age of buildings is important to determine their vulnerability to 22 rock failure, as old buildings are more vulnerable compared with modern buildings; the term modern 23 refers to the period from 2011 until now as shown in Figure 17. 24 25 Fig. 12 Population density of the study area Fig. 13 Land uses of the study area constructed as shown in Figure 16. 20 21 6. The age of buildings. The study of the age of buildings is important to determine their vulnerability to 22 rock failure, as old buildings are more vulnerable compared with modern buildings; the term modern 23 refers to the period from 2011 until now as shown in Figure 17. 24 25 Fig. 12 Population density of the study area Fig. 13 Land uses of the study area The following vulnerability map as shown in Figure 18 shows the highest vulnerability zones that are 2 affected by the risk of rock failure. These zones are densely populated and contain degraded poor houses that are 3 constructed by weak building materials such as mud and wood without ceiling. In addition, they mainly serve 4 vital activities, whether economic or social, while they are located on roads with a poor dirty status. 5 Moreover, the map shows that the northern area of Manshiet Nasser (study area) is the most vulnerable, 6 because of the high population density and the status of houses that are degraded, poor and constructed by weak 7 building materials such as mud and wood without ceilings. 8 9  The following vulnerability map as shown in Figure 18 shows the highest vulnerability zones that are 2 affected by the risk of rock failure. These zones are densely populated and contain degraded poor houses that are 3 constructed by weak building materials such as mud and wood without ceiling. In addition, they mainly serve 4 vital activities, whether economic or social, while they are located on roads with a poor dirty status. 5 Moreover, the map shows that the northern area of Manshiet Nasser (study area) is the most vulnerable, 6 because of the high population density and the status of houses that are degraded, poor and constructed by weak 7 building materials such as mud and wood without ceilings. 8  The following vulnerability map as shown in Figure 18 shows the highest vulnerability zones that are 2 affected by the risk of rock failure. These zones are densely populated and contain degraded poor houses that are 3 constructed by weak building materials such as mud and wood without ceiling. In addition, they mainly serve 4 vital activities, whether economic or social, while they are located on roads with a poor dirty status. 5 Moreover, the map shows that the northern area of Manshiet Nasser (study area) is the most vulnerable, 6 because of the high population density and the status of houses that are degraded, poor and constructed by weak 7  The following vulnerability map as shown in Figure 18 shows the highest vulnerability zones that are 2 affected by the risk of rock failure. These zones are densely populated and contain degraded poor houses that are 3 constructed by weak building materials such as mud and wood without ceiling. In addition, they mainly serve 4 vital activities, whether economic or social, while they are located on roads with a poor dirty status. 5 Moreover, the map shows that the northern area of Manshiet Nasser (study area) is the most vulnerable, 6 because of the high population density and the status of houses that are degraded, poor and constructed by weak 7

Results and Discussion
The multivariate statistics were used according to the methodology that links the occurrence of rock collapse in a given cell (pixel) with the occurrence of several factors in the same cell. The area map was presented as cells (10m * 10m). Each cell had a value of H and V, with a total of 45,723 cells/ pixels. The general risk assessment equation was applied by multiplying the vulnerability (V) to the severity of hazard (H) using the Map Algebra tool in the GIS programme to assess the final risk. The weighted linear combination model resulted in a rock failure susceptibility index map RSI demonstrated in figure 19, where it shows that the most risky areas are in the eastern border of El-Razzaz area and also the southern border of El-Zarayeb area, which are the edges of Mount Mouktam, while the least risky areas are south of El-Duwaiqa and its extension area. y weak building materials such as mud and wood without ceiling. In addition, they mainl s, whether economic or social, while they are located on roads with a poor dirty status. er, the map shows that the northern area of Manshiet Nasser (study area) is the most vuln e high population density and the status of houses that are degraded, poor and constructed b rials such as mud and wood without ceilings. y the risk of rock failure. These zones are densely populated and contain degraded poor houses that are d by weak building materials such as mud and wood without ceiling. In addition, they mainly serve ities, whether economic or social, while they are located on roads with a poor dirty status. eover, the map shows that the northern area of Manshiet Nasser (study area) is the most vulnerable, f the high population density and the status of houses that are degraded, poor and constructed by weak aterials such as mud and wood without ceilings.
he vulnerability assessment map nd Discussion multivariate statistics were used according to the methodology that links the occurrence of rock in a given cell (pixel) with the occurrence of several factors in the same cell. The area map was In case of the rockslide history map, a value is set for each cell equal to 1, where the previous rock failure happened in this cell and 0 if no previous rock failure occurred in this cell. The maps of the triggers and causes of the rock failure were prepared by the GIS programme, which calculates the degree of hazard using the following factors: geology, slope direction, slope curvature, faults, stream density, terrain roughness index, proximity to drainage systems, historical record of previous slides, land cover, torrents accumulations paths, topography and slopes. They were standardised and their relative weights were determined by the previous equations, by unifying all factors on a numeric scale from 0 to 1 to facilitate their calculation as shown in Table 7. The vulnerability maps were prepared. The vulnerability of the Map Algebra tool in the GIS programme to assess the final risk. The weighted linear combina ulted in a rock failure susceptibility index map RSI demonstrated in figure 19, where it shows tha y areas are in the eastern border of El-Razzaz area and also the southern border of El-Zarayeb a the edges of Mount Mouktam, while the least risky areas are south of El-Duwaiqa and its exten he risk assessment map (final map) se of the rockslide history map, a value is set for each cell equal to 1, where the previous rock fai in this cell and 0 if no previous rock failure occurred in this cell. The maps of the triggers and ca ck failure were prepared by the GIS programme, which calculates the degree of hazard using factors: geology, slope direction, slope curvature, faults, stream density, terrain roughness in to drainage systems, historical record of previous slides, land cover, torrents accumulations pa y and slopes. They were standardised and their relative weights were determined by the prev , by unifying all factors on a numeric scale from 0 to 1 to facilitate their calculation as shown in T lnerability maps were prepared. The vulnerability of the population and urban areas are meas to land use, building age, number of floors, number of inhabitants in each building, basic facili conditions, construction materials, and road network and its conditions. The measurement ed by a digital scale from 0 to 1, and the final map of vulnerability was extracted. nted as cells (10m * 10m). Each cell had a value of H and V, with a total of 45,723 cells/ pixels. The al risk assessment equation was applied by multiplying the vulnerability (V) to the severity of hazard (H) the Map Algebra tool in the GIS programme to assess the final risk. The weighted linear combination l resulted in a rock failure susceptibility index map RSI demonstrated in figure 19, where it shows that the risky areas are in the eastern border of El-Razzaz area and also the southern border of El-Zarayeb area, are the edges of Mount Mouktam, while the least risky areas are south of El-Duwaiqa and its extension 9 The risk assessment map (final map) In case of the rockslide history map, a value is set for each cell equal to 1, where the previous rock failure ned in this cell and 0 if no previous rock failure occurred in this cell. The maps of the triggers and causes e rock failure were prepared by the GIS programme, which calculates the degree of hazard using the ing factors: geology, slope direction, slope curvature, faults, stream density, terrain roughness index, mity to drainage systems, historical record of previous slides, land cover, torrents accumulations paths, raphy and slopes. They were standardised and their relative weights were determined by the previous ions, by unifying all factors on a numeric scale from 0 to 1 to facilitate their calculation as shown in Table  e vulnerability maps were prepared. The vulnerability of the population and urban areas are measured ding to land use, building age, number of floors, number of inhabitants in each building, basic facilities, ing conditions, construction materials, and road network and its conditions. The measurement was ardised by a digital scale from 0 to 1, and the final map of vulnerability was extracted.

Estimated value
Relative class 1.00-0.75 Very high 0.75-0.55 High 0.55-0.30 Moderate 0.30-0.10 Low 0.10-0.00 Very low A database was prepared using GIS to link the triggers of rock failure with the vulnerability of the elements k, in order to conclude the map of the rock failure hazard index in the study area and to know the quences of assessing the risk of rock failure on land use, road network and population. This helps in land isk management to develop mitigation, treatment and adaptation strategies. The application on the study includes conducting a survey to determine the rock failure and its characteristics by analysing the aerial population and urban areas are measured according to land use, building age, number of floors, number of inhabitants in each building, basic facilities, building conditions, construction materials, and road network and its conditions. The measurement was standardised by a digital scale from 0 to 1, and the final map of vulnerability was extracted.
A database was prepared using GIS to link the triggers of rock failure with the vulnerability of the elements at risk, in order to conclude the map of the rock failure hazard index in the study area and to know the consequences of assessing the risk of rock failure on land use, road network and population. This helps in land and risk management to develop mitigation, treatment and adaptation strategies. The application on the study area includes conducting a survey to determine the rock failure and its characteristics by analysing the aerial photographs and the field study, and a spatial correlation between rock failure and catalysts to develop recommendations for the settlement of land use in the region. The research proves that the use of such a model is an effective and cost-saving tool for mapping the rock failure risk assessment. It can identify rock failure subsidence in susceptible zones. It can also identify vulnerable locations of infrastructure that Environmental Research, Engineering and Management 2020/76/2 108 are exposed to such a risk. Measuring and building codes could, therefore, be applied at the early stages of planning; therefore, such maps are recommended prior to the zone and site selection phases.

Conclusions
Designing a risk assessment and a forecasting approach is important to promote the concept of sustainability in environmental risk management, because many countries do not have standard criteria for assessing the risk of rock failure. As a result, the risk assessment of rock failure is still evolving. A set of data must be available for each type of risk to start the risk assessment process, followed by standardising the weights of these criteria according to the researcher or decision makers' vision. The stage of calculating the risk and its impact on the urban areas and population is necessary to calculate the economic value of the elements at risk. The risk assessment is a step in a larger process based on the results of the assessment, because it is the basis for planning and decision-making. There are many ways to calculate the risk and vulnerability methods that vary according to the type of risk and many other factors. Conducting more detailed studies based on this topic in the study area are further needed and must be encouraged more. The map of the final risk assessment of rock failure shows the areas most vulnerable to future rock failure. This helps population to avoid exposing to death and damage in urban areas. It is the basic map to be relied on when planning this area in the future. The proposed approach helps to analyse the factors causing the occurrence of rock slides in the area of Manshiet Nasser, so the risk severity index map is produced to show the factors of vulnerability and the inferring elements at risk and their vulnerability.