Assessment of the Relationship Between Seismic Vulnerability and Seismic Risk Perception: A Case Study of Peshawar, Pakistan

Abstract

Earthquakes pose a serious threat to urban areas located in seismically active regions, particularly in developing countries where rapid urbanization and weak enforcement of building regulations increase the vulnerability of the built environment. Pakistan is highly exposed to seismic hazards due to its tectonic setting, and many residential buildings are constructed without adequate seismic design considerations. Therefore, assessing building vulnerability and understanding community perception of earthquake risk are essential for effective disaster risk reduction. This study investigates the relationship between the structural vulnerability of residential buildings and earthquake risk perception among residents in Peshawar, Pakistan. Two contrasting urban settlements were selected as case studies: WAPDA Town, representing a planned residential area, and Hashtnagri, representing an older unplanned settlement. A total of 400 buildings were surveyed through field investigations. Seismic vulnerability was assessed using the Rapid Visual Screening (RVS) method based on structural characteristics such as building age, number of floors, construction materials, structural irregularities, construction quality, and presence of seismic reinforcement features. A Physical Vulnerability Index (PVI) was developed to categorize buildings into different vulnerability levels. In addition, a questionnaire survey was conducted to evaluate earthquake risk perception among residents, and a risk perception index (RPI) was calculated. The results indicate that buildings located in the unplanned settlement exhibit significantly higher seismic vulnerability compared to those in the planned residential area due to poor construction practices, irregular structural configurations, and the absence of seismic-resistant features. Statistical analysis further reveals a positive relationship between physical vulnerability and earthquake risk perception, suggesting that residents living in structurally vulnerable environments tend to perceive higher earthquake risk. The findings highlight the importance of integrating structural vulnerability assessment with community awareness and preparedness programs. Implementation of seismic design provisions and improved enforcement of construction regulations, such as those specified in the Building Code of Pakistan 2022, can significantly reduce earthquake risk in rapidly growing urban areas. However, the present study did not directly evaluate the level of enforcement or compliance with the Building Code of Pakistan 2022 in either WAPDA Town or Hashtnagri. Therefore, the policy recommendations are intended as general implications derived from the observed vulnerability patterns.

1. Introduction

The frequency of natural disasters, such as earthquakes, floods, and tsunamis, has been rising globally, posing significant risks to vulnerable communities [1]. These events are inherently unpredictable and can occur anywhere, often transforming into disasters that result in loss of life, injuries, property damage, and dramatic changes to the geography of affected areas [2]. Asia is one of the most impacted regions globally [3,4], accounting for 43.3% of all disasters in 2009 [5]. Among natural hazards, seismic activities are regarded as some of the most destructive due to their capacity for widespread devastation [6]. The increasing rate of seismic activity, combined with rapid urbanization, including both planned and unplanned development, poverty, and limited public awareness, has significantly heightened the risk of earthquake-related losses [7,8]. Developing countries like Pakistan face increasing earthquake risks due to insufficient enforcement of building codes, lack of regulations, and inadequate urban planning. The devastating 2005 Kashmir earthquake demonstrated these vulnerabilities, resulting in 73,000 deaths, 80,000 injuries, and the displacement of 2.8 million people [9]. Unreinforced masonry (URM) buildings, widely used in Pakistan due to the affordability and availability of raw materials, suffered severe damage during this event. Despite their susceptibility, URM structures remain common. Historical evidence emphasizes that applying earthquake-resistant building codes is one of the most effective strategies for mitigating seismic disaster impacts, highlighting the urgent need for improved regulation and implementation [10]. Low-cost retrofitting strategies suitable for non-engineered masonry buildings commonly found in the study area include installation of horizontal bands, corner strengthening, improved roof-to-wall connections, wall strengthening measures, and regular maintenance of deteriorated structural elements. These practical interventions can substantially improve seismic performance in economically constrained communities.

While natural hazards cannot be entirely prevented, their impacts can be mitigated through effective preventive measures. Earthquakes, characterized by ground shaking lasting from seconds to nearly a minute, can cause catastrophic damage to life and infrastructure. The primary contributors to such damage include improper construction practices and a lack of public preparedness [11]. Building failures, often stemming from the inadequate performance of vertically loaded structural members, are the leading cause of casualties, injuries, and significant economic losses during earthquakes [12]. The vulnerability and behavior of structures during seismic events are influenced by their design, materials, and construction quality, necessitating a comprehensive understanding of their collective performance [13]. The extent of fatalities and damage in an earthquake depends on factors such as ground shaking intensity, population density, and the vulnerability of local buildings. Rapid urbanization and population growth in major cities have amplified the need for vulnerability assessments of critical structures, including buildings, bridges, and hydraulic systems [14]. Seismic vulnerability, defined as the susceptibility of structures to damage during an earthquake, provides a basis for predicting potential harm and informing disaster mitigation strategies [15]. Similarly, earthquake risk assessments evaluate potential economic, social, and infrastructural losses, aiding in the development of risk maps and disaster management plans [16,17]. Given the significant human and economic losses caused by earthquakes, the seismic vulnerability assessment of buildings and critical infrastructure in earthquake-prone regions is imperative for effective risk reduction.

For seismic evaluation of structures, there are many approaches available that contain comprehensive structural analysis and design [18]. The earthquake vulnerability of building structures in Egypt [19] and Jordan [20] has been assessed by the researchers using complex non-linear procedures. However, such methods are time-intensive and impractical for assessing a large number of buildings in a region [21]. To address this challenge, Rapid Visual Screening (RVS) methods have been proposed as effective alternatives for time-efficient seismic vulnerability assessments [22,23]. These methods are widely adopted to evaluate the vulnerability of building structures based on regional conditions and structural typologies [24,25]. The RVS method provides a preliminary evaluation of a building’s earthquake adequacy by observing its structural features, including typology (e.g., frame structures, infill walls, and shear walls), construction materials (e.g., concrete, steel, wood, and masonry), design approaches, and other relevant parameters. A score is assigned to each parameter, enabling the assessment of the expected seismic performance of the building. This method facilitates the vulnerability assessment of a large number of structures in a region efficiently. Other approaches, such as those using machine learning techniques [26], linear and nonlinear regression models [27,28], or multi-criteria assessments [29,30,31,32], have also been developed. However, the present study employs the RVS procedure, recommended by the national technical codes of several countries [22,32] for rapid seismic evaluations. Physical vulnerability assessment, a critical component of seismic risk evaluation, is integral to risk reduction strategies [22,32]. This study aims to assess the physical vulnerability of buildings in both an older (unplanned settlement) and a newer (planned settlement) area of Peshawar, comparing their structural performance to identify factors contributing to their vulnerability.

Although construction materials and structural typologies were observed during the survey, the present study primarily focuses on comparing the overall seismic vulnerability and risk perception characteristics between planned and unplanned settlements rather than isolating the independent effects of specific construction materials. The dominant construction types in Hashtnagri consisted mainly of non-engineered masonry structures, whereas reinforced concrete frame structures were more common in WAPDA Town.

Another relevant term used in seismic assessment studies is risk perception, which is the belief about the possibility of loss or potential harm. Many scientists characterize risk perception as a subjective intuition [33] since professionals and communities perceive risk in different ways [34,35]. However, community risk perception is treated as one of the determinants of the attitude. It can also aid in designing efficient preventive measures [36,37]. The literature on risk perception reveals that there is a correlation between risk perception and disaster preparedness [38,39,40,41]. In some societies, belief can affect perception more than experience [42,43]. Some of these aspects are recognized in the literature on hazard assessment [39,42]. Risk analysis, which focuses on risk assessment and management, highlights the importance of integrating risk perception with quantitative assessments to develop effective hazard management strategies [8,44,45]. Over the past two decades, many countries have created earthquake risk maps at the national level, combining risk perception insights with technical assessments to guide preventive measures and disaster mitigation efforts [17,46,47].

The northern region of Pakistan, including Peshawar, is highly susceptible to earthquakes due to its proximity to the tectonic boundary between the Indian and Eurasian plates. Peshawar (highlighted in the seismic zoning map of Pakistan, Figure 1), a densely populated and rapidly developing city, is classified in seismic Zone 2B (

Table 1. Recommended PGA values for seismic zones of Pakistan, according to the Building Code of Pakistan [48].

Seismic Zones	PGA Values
1	0.05 to 0.08 g
2A	0.08 to 0.16 g
2B	0.16 to 0.24 g
3	0.24 to 0.32 g
4	>0.32 g

), with peak horizontal ground accelerations (PGA) ranging from 0.16 g to 0.24 g [48]. This study investigates and compares the seismic vulnerability of building structures and community risk perception in two contrasting areas of Peshawar: a newly planned settlement (WAPDA Town) and an older, unplanned settlement (Hashtnagri). The prevalence of non-engineered buildings in unplanned areas like Hashtnagri poses significant risks, as these structures lack sufficient lateral resistance despite performing adequately under gravity loads. There is relatively limited research available on the performance of non-engineered buildings [49]. Using the RVS method, the study identifies and ranks buildings in both settlements to evaluate their seismic vulnerability. Furthermore, it examines the relationship between structural vulnerabilities and community risk perception through statistical analysis. The insights gained aim to inform disaster mitigation strategies, helping to reduce the risks posed by earthquakes in urban settlements. The observed relationship represents an association rather than a direct causal relationship, as additional variables such as education level, socioeconomic conditions, prior earthquake experience, and media exposure may also influence community risk perception.

2. Methodology

This study involves two primary surveys: a building vulnerability assessment and an evaluation of seismic risk perception among the community. The findings from these surveys are used to rank buildings based on their vulnerability and analyze community risk perceptions. To explore the interdependence between these factors, a linear regression analysis is conducted. A similar approach has also been applied in earlier studies, such as Khan et al. [50], which provided a methodological foundation and informed the design of the present surveys.

The building vulnerability assessment employs the RVS method, a quick and cost-effective technique developed by the Applied Technology Council (ATC) and introduced in the FEMA 154 report in 1988 [51]. The RVS method is efficient and reliable for assessing the vulnerability of a large number of structures. It involves skilled screeners conducting street-level surveys to identify structural features that influence seismic performance. Key building attributes, such as construction materials, structural typology, and design characteristics, are evaluated to determine the vulnerability levels. This method is particularly advantageous for large-scale assessments where time and resources are constrained [23]. The following features of the buildings were considered during the RVS survey. In addition, the updated FEMA P-154 (2015 revision) guidelines were also considered to improve the reliability and consistency of the Rapid Visual Screening assessment framework.

• General building information, which includes a number of floors, age, type, maintenance conditions, etc.
• Structural information includes plan and vertical irregularities, structural and non-structural cracks, etc.
• Building apparent quality generally comprises the quality of materials and construction.
• Openings like irregular/unsymmetrical openings in walls and/or large openings in walls.
• Bands like lintel band, horizontal band, plinth band, and roof band.
• Water tank on the roof, its location, and capacity.
• Pounding effect is assessed by the distance between two adjacent buildings.
• Other information includes soil conditions, diaphragm action, heavy overhang, soft floor, short-column effect, frame action, etc.

Based on the assessment, buildings are categorized into two groups: those that fall within acceptable vulnerability limits and those deemed seismically hazardous, requiring further evaluation by experienced engineers. The second survey focuses on risk perception, aiming to assess community attitudes towards seismic risk. Risk perception refers to an individual’s interpretation of potential hazards that could lead to crises or emergencies, shaped by sensory information and personal experiences [23]. Unlike probability-based assessments, risk perception encompasses factors such as vulnerability awareness and individual attitudes. Research indicates that individuals with lower economic status and poorly constructed homes tend to exhibit higher levels of risk perception [8], whereas those with tertiary education and higher income levels are more likely to invest in the maintenance and rehabilitation of their homes [52]. To gather data on risk perception, residents of the study areas were surveyed regarding their views on potential seismic dangers. Responses were categorized based on the weightage assigned to the perceived severity of the threat. Finally, a linear regression analysis was conducted to investigate the relationship between building vulnerability and community risk perception, providing insights into their interdependence and informing risk reduction strategies.

2.1. Case Study Areas and Sample Size

Peshawar is the largest and capital city of Khyber Pakhtunkhwa (KPK) Province in Pakistan, with a total city area of 215 km². It is located 185 km northeast of Islamabad, the capital of Pakistan. As a developing city and a prominent commercial and educational hub of KPK, Peshawar has experienced significant population growth over the past few decades. According to the 2017 Pakistan Bureau of Statistics survey, the district’s population is 4,269,079, with a total building stock of 489,843 structures [53]. The sample size for this study was determined based on the total building stock, using the Yamane (1967) Equation (1) [54].

$$n={\displaystyle \frac{N}{1+N{e}^2}}$$

(1)

In the equation, “n” represents sample size, “N” shows total population size, and “e” denotes the margin of error, set at 0.05 for a 95% confidence level. The Yamane (1967) equation was applied using e² as the acceptable sampling error term.

A total of 400 samples were collected for the study, with 200 samples obtained from each of the two selected areas: Hashtnagri and WAPDA Town. Hashtnagri, an older suburb in Peshawar, is characterized by a compact layout, high population density, and narrow streets (Figure 2a). In contrast, WAPDA Town is a recently developed area featuring a well-planned layout and modern construction practices (Figure 2b). Equal sample allocation was intentionally adopted to maintain consistency and comparability between the two study areas during the field survey process. However, higher population density in Hashtnagri may affect representativeness and could introduce potential sampling bias.

The soil types in both study areas were identified during pre-survey visits. The surveys were conducted over four months by a team of four members, including the authors and two trained students proficient in the local language. For the seismic risk perception survey, respondents were briefed on the purpose of the study, and their willingness to participate was ascertained before data collection. Since participation in the questionnaire survey was voluntary, the possibility of response bias cannot be excluded. Respondents with relatively higher educational awareness may have been more willing to participate, which could influence the observed risk perception levels. Foundation-related characteristics were not directly included in the RVS assessment because of observational limitations during field surveys. This omission may underestimate actual seismic vulnerability, particularly in areas with weak soil conditions or poor subsoil characteristics.

2.2. Scoring System for Seismic Vulnerability Assessment

In the RVS methodology, each building’s performance score is calculated based on a numerical scoring system. The RVS technique employs a ranking approach to classify structures according to their seismic vulnerability, categorizing them as highly vulnerable, moderately vulnerable, or less vulnerable. The seismic vulnerability of buildings is evaluated by comparing their performance scores to a predetermined “cut-off” score to determine whether further evaluation by skilled engineers is necessary. Additionally, the performance score helps assess the structural adequacy and the need for retrofitting. The assessment of buildings is carried out based on parameters recorded using the RVS method. These parameters include the number of floors, building age, building type, soft-floor presence, pounding and short-column effects, plan and vertical irregularities, water tank placement, and the presence of cracks and horizontal bands, among others.

The vulnerability of a structure, defined as the expected loss resulting from an event such as an earthquake, is quantified on a scale from 0 (no damage) to 1 (severe damage). Using the parameters detailed in

Table 2. The details of the indicators for physical vulnerability.

S. No	Attributes	Category	Weightage	Explanation
1.	Building age (years)	>45	1	Because of the effects of aging, aged buildings are more vulnerable.
		31–45	0.75
		16–30	0.5
		0–15	0.25
2.	Number of floors	≥4	1	High-rise buildings are considered more vulnerable.
		3	0.75
		2	0.5
		1	0.25
3.	Horizontal bands	Yes	10	Buildings with a plinth/lintel band are less vulnerable.
		No	1
4.	Plan irregularity	Yes	1	Buildings with irregular plans exhibit poor performance.
		No	0
5.	Vertical irregularity	Yes	1	Vertical irregularity creates a soft-floor effect.
		No	0
6.	Maintenance condition	Poor	1	Poor maintenance tends to increase vulnerability.
		Moderate	0.66
		Good	0.33
7.	Apparent construction quality	Poor	1	Poorly constructed buildings are more prone to damage.
		Moderate	0.66
		Good	0.33
8.	Quality of materials	Poor	1	Poor materials quality results in low seismic performance.
		Moderate	0.66
		Good	0.33
9.	Mortar type	Mud	1	Mud mortar walls are more vulnerable than cement mortar.
		Lime	0.66
		Cement	0.33
10.	Wall type	Stone	1	Stone masonry walls are weak due to poor bonding.
		Block	0.66
		Brick	0.33
11.	Ground surface	Steep	1	Buildings on the slope are more vulnerable.
		Mild	0.66
		flat	0.33
12.	Diaphragm	Flexible	0.5	Rigid diaphragms are less vulnerable.
		Rigid	1
13.	Dampness	damped	1	Damp buildings are more prone to damage.
		Slightly Damped	0.66
		undamped	0.33

, a Physical Vulnerability Index (PVI) has been formulated for each building structure. Each indicator is assigned a weight within a range of 0–1, and the PVI for all building structures is calculated using Equation (2). The assigned weights were based on the previous RVS-related literature, expert judgment, and field observations relevant to the local construction context of Peshawar. However, formal validation techniques such as the Delphi method or factor analysis were not applied, which is acknowledged as a limitation of the study.

$$PVI={\displaystyle \frac{(W_1+W_2+W_3\dots W_{13})}{13}}$$

(2)

W₁ to W₁₃ denote the assigned weights for 13 specific indicators. Data for these indicators were collected during the survey using RVS forms. The vulnerability attributes are mathematically combined to estimate the seismic behavior of the surveyed buildings. The seismic vulnerability of each building is assessed using these 13 indicators, based on the results of the visual examination. An example of a vulnerability assessment for a building in WAPDA Town, as depicted in Figure 3, is provided below. The assessment is based on the indicators listed in Table 2. The assigned weights correspond sequentially to the indicators outlined in Table 2, illustrating the process of evaluating the building’s seismic vulnerability.

$$PVI={\displaystyle \frac{0.25+0.25+0+1+1+0.33+0.33+0.33+0.33+0.33+0.33+1+0.66}{13}}=0.47$$

In addition to the physical vulnerability assessment, this study incorporates an evaluation of risk perception. The physical vulnerability assessment forms were completed through face-to-face interviews, accompanied by essential photographs (Figure 4) capturing the key structural features of the buildings. The risk perception survey, however, was self-administered by the respondents, allowing them to provide insights based on their personal judgments.

2.3. Evaluation of Earthquake Risk Perception Indicators

House type and risk perception are interrelated. Construction of building structures according to codes and strengthening of existing buildings can significantly reduce the risk perception [55]. For each indicator contributing to the risk perception index (RPI), values are assigned within the range of 0 to 1, and the overall mean RPI value is calculated to fall between these limits. The RPI for each respondent is computed using Equation (3) [50]:

$$RPI={\displaystyle \frac{(W_1+W_2+W_3\dots .W_n)}{n}}$$

(3)

where W₁, W₂, W₃…, W_n represent the weights assigned to n specific indicators related to risk perception. For example, based on the indicators shown in

Table 3. The details of earthquake risk perception indicators.

S. No	Attributes	Category	Weightage	Explanation
1.	How likely is an earthquake to occur in the future?	Very high	1	Those perceiving the likelihood of an earthquake would perceive more risk.
		High	0.8
		Medium	0.6
		Low	0.4
		Very low	0.2
2.	The probability of future harm from an earthquake.	Very high	1	Those perceiving the likelihood of destruction of an asset by earthquake would perceive more risk.
		High	0.8
		Medium	0.6
		Low	0.4
		Very low	0.2
3.	How afraid are you of an earthquake?	Very high	1	Those who are relatively more afraid of earthquakes would perceive more risk.
		High	0.8
		Medium	0.6
		Low	0.4
		Very low	0.2
4.	The level of understanding of emergency protocols.	Very high	1	The knowledge about emergency protocols would be perceived as low risk.
		High	0.8
		Medium	0.6
		Low	0.4
		Very low	0.2
5.	The level of loss of lives in an earthquake.	Very low	1	Those who believe loss of lives might occur in a future earthquake perceive more risk.
		Low	0.8
		Medium	0.6
		High	0.4
		Very high	0.2
6.	The ability to cope with a future earthquake.	Very low	1	A better economy of households with high capability perceives low risk.
		Low	0.8
		Medium	0.6
		High	0.4
		Very high	0.2
7.	The level of harm/damage in the last seismic event.	Very high	1	The people affected by the past earthquake perceive more risk.
		High	0.8
		Medium	0.6
		Low	0.4
		Very low	0.2
8.	The structure’s resistance to an earthquake.	Very high	1	The more the respondent perceived the building as resistant, the lower the perceived risk.
		High	0.8
		Medium	0.6
		Low	0.4
		Very low	0.2
9.	The age of the respondent.	>35	1	The risk perception increases with age.
		31–35	0.8
		26–30	0.6
		21–25	0.4
		<25	0.2
10.	Do you live in a seismically active region?	Yes	1	People in a seismically active region will perceive more risk.
		No	0

, the RPI of respondents has been calculated below using Equation (3) in their respective order. However, differences in respondents’ educational backgrounds across the two study regions were not separately analyzed, which may have introduced a potential response bias in the risk perception results.

$$RPI={\displaystyle \frac{0.8+0.6+0.6+0.4+1+0.6+0.8+0.4+0.6+1}{10}}=0.68$$

3. Results and Discussion

3.1. Physical Vulnerability Assessment of Buildings

The physical vulnerability of buildings was assessed using a scoring methodology based on the vulnerability factors outlined in

Table 4. Vulnerability levels of buildings based on vulnerability factor ranges.

Level of Vulnerability	Vulnerability Factor Range
Low	≥0.25 ≤0.45
Medium	>0.45 ≤0.65
High	>0.65

. Statistical analysis revealed that Hashtnagri exhibited a significantly poorer performance score compared to WAPDA Town. The heightened vulnerability in Hashtnagri is attributed to several factors, including high-rise unplanned construction, lack of adherence to building codes, inadequate enforcement by regulatory authorities, aging structures, and limited awareness among residents regarding safe construction practices. Additionally, the prevalence of unreinforced masonry buildings, substandard construction materials, and inadequate maintenance exacerbates the vulnerability of this area.

In contrast, WAPDA Town demonstrated a higher proportion of low-vulnerability buildings, reflective of planned development, adherence to building standards, and the use of modern construction techniques. Figure 5 highlights the distribution of vulnerability levels across both regions, with 28% of Hashtnagri’s buildings categorized as highly vulnerable compared to just 10% in WAPDA Town. The high vulnerability in Hashtnagri was primarily due to structural deficiencies such as plan and vertical irregularities, absence of horizontal bands, poor maintenance, and unauthorized vertical extensions in narrow streets. The urban characteristics of Hashtnagri include dense population, informal settlements, and poorly maintained infrastructure, which further compound its physical vulnerability. Rapid urbanization has led to deteriorating conditions, increasing risks to human lives, property, and infrastructure. In the event of a significant earthquake, these vulnerabilities could result in catastrophic damage.

Physical Seismic Vulnerability at the Household Level

A detailed comparison of the two regions was conducted using individual vulnerability indicators listed in Table 2. Notably, there were no significant differences between Hashtnagri and WAPDA Town in terms of plan and vertical irregularities and dampness of structures, as shown in Figure 6 and Figure 7.

However, marked differences were observed in attributes such as apparent condition, material quality, and overall structural quality. WAPDA Town demonstrated superior results for these attributes, with over 50% of the buildings classified as having good maintenance, material quality, and apparent condition. Conversely, Hashtnagri displayed significantly lower percentages for these indicators, as illustrated in Figure 8.

The assessment of vulnerability is a critical component in estimating seismic risk. In this study, the two selected regions were assessed and compared based on established vulnerability factor ranges, which may vary depending on user requirements and the seismic characteristics of the area. Enhancing the resilience and flexibility of building structures requires the mitigation of physical vulnerabilities. Key strategies for reducing physical vulnerability include ensuring proper maintenance, adhering to building codes and regulatory standards, minimizing plan and vertical irregularities, opting for cement mortar instead of lime or mud mortar, raising community awareness about construction practices, and making informed choices regarding building materials tailored to the seismic conditions of the region.

3.2. Seismic Risk Perception at the Household Level

The relationship between respondents’ age and their perception of earthquake risk was analyzed by categorizing individuals into five age groups: 15–20, 21–25, 26–30, 31–35, and above 35 years (Figure 9). The analysis revealed that 36% of respondents were above 35 years old, while 33.5% belonged to the 15–20 age group. Interestingly, the age group of 26–30 years was more prevalent in Hashtnagri, whereas the 21–25 age group was more represented in WAPDA Town. Previous studies suggest that older individuals, particularly those over 65 years, face greater exposure and vulnerability during emergencies and disasters [56]. These findings are consistent with recent research, which highlights that individuals above 60 years are most susceptible to seismic risks [40,57].

When the respondents were asked whether they lived in a seismically active region, responses varied significantly between the two study areas (Figure 10). In WAPDA Town, 53% of respondents acknowledged living in a seismically active area, compared to 42% in Hashtnagri. These findings suggest a disparity in awareness levels, possibly influenced by urban planning and educational differences between the two regions.

At the household level, seismic risk perception and associated fear are influenced not only by the physical vulnerability of structures but also by access to resources and individual characteristics [57]. The indicators used to evaluate earthquake risk perception, derived from the literature on common hazards (Table 3), provide a framework for understanding and improving risk awareness and preparedness. These indicators also aid in exploring the interrelationship between various factors influencing risk perception.

A comparative analysis of seismic risk perception (Figure 11) indicates that individuals in the Hashtnagri region exhibit a higher risk perception index (0.84) compared to those in WAPDA Town, where the index value is 0.64. This difference is indicative of the interplay between structural conditions, community awareness, and perceived vulnerability. Residents in areas with older, poorly constructed buildings, such as Hashtnagri, are likely to have higher risk perceptions due to their direct exposure to visible vulnerabilities, while planned regions like WAPDA Town benefit from enhanced structural safety and community planning. The findings suggest that improving access to resources, promoting community awareness, and ensuring adherence to building codes can mitigate seismic risk perceptions, particularly in highly vulnerable regions like Hashtnagri. These measures not only reduce physical vulnerability but also foster a greater sense of security among residents.

4. Relationship Between PVI and RPI

To evaluate the association between physical vulnerability and seismic risk perception, a statistical linear regression analysis was conducted. The analysis considers building vulnerability as the independent variable and risk perception as the dependent variable, employing Equation (4) to model the relationship:

$$Y=ax+B$$

(4)

Figure 12 and Figure 13 illustrate the relationship between the PVI and the RPI for WAPDA Town and Hashtnagri, respectively. The results indicate a clear positive correlation: as physical vulnerability increases, risk perception also rises. This observation underscores the importance of regulatory measures, preparedness, and precautionary interventions to mitigate seismic hazards effectively.

The strength of the relationship between PVI (independent variable) and RPI (dependent variable) was further analyzed using Pearson’s correlation coefficient (r). The result revealed that a positive correlation exists between the two variables in both areas. The survey conducted in WAPDA Town showed a positive correlation (r = 0.511, p-value = 0.000), whereas in the Hashtnagri area, the correlation is relatively better (r = 0.722, p-value = 0.000) than in WAPDA Town, as shown in

Table 5. Empirical relationships between RPI and PVI.

Regions	R2	df	F	β	p-Value	á	Relationship
Hashtnagri	0.521	1	216.160	0.625	0.000	0.255	RPI = 0.625 * PVI + 0.255
WAPDA Town	0.262	1	70.165	0.472	0.000	0.320	RPI = 0.472 * PVI + 0.320

. These findings, detailed in Table 5, indicate that residents in more physically vulnerable areas, such as Hashtnagri, perceive greater seismic risk compared to those in planned localities like WAPDA Town. Additionally, paired sample t-tests were conducted to assess differences in vulnerability perception between the two study areas. The results demonstrate significant differences in both Hashtnagri (t-value = 14.702, p-value = 0.000) and WAPDA Town (t-value = 8.376, p-value = 0.000). The findings suggest that in regions with limited access to quantitative data, such as developing countries like Pakistan, seismic risk perception can serve as a valuable alternative for assessing vulnerability. The observed relationships emphasize the critical need for structural retrofitting, adherence to building codes, and community awareness to enhance earthquake resilience in older structures. For WAPDA Town, the regression equation RPI = 0.472 * PVI + 0.320 explains 26.2% of the variance (R² = 0.262), while for Hashtnagri, RPI = 0.625 * PVI + 0.255 accounts for 52.1% of the variance (R² = 0.521). The results, summarized in Table 5, underscore the stronger dependency of risk perception on physical vulnerability in Hashtnagri, reflecting its unplanned infrastructure and poor building conditions compared to the planned environment of WAPDA Town.

5. Engineering Implications

The findings of this study have several implications for earthquake risk reduction in urban areas. Buildings located in unplanned settlements often lack basic seismic-resistant features such as horizontal reinforcement bands, proper structural connections, and adequate construction quality. These deficiencies significantly increase the likelihood of structural damage during earthquakes. Due to the comparatively higher vulnerability of Hashtnagri, priority should be given to retrofitting older masonry structures and improving local infrastructure, whereas in WAPDA Town, emphasis should be placed on the strict implementation of building codes and planned urban development to minimize future seismic risk.

The implementation of seismic design provisions specified in the Building Code of Pakistan 2022 could substantially reduce the vulnerability of residential buildings. In particular, enforcement of basic construction standards for masonry structures, including the use of horizontal bands and improved mortar quality, can greatly enhance seismic performance.

Urban planning policies should also focus on regulating building extensions and improving spacing between structures to reduce the risk of pounding during seismic events. Retrofitting programs targeting older masonry buildings in highly vulnerable areas could further contribute to reducing potential earthquake losses.

6. Conclusions

This study evaluates and compares the prevailing conditions in the unplanned and planned regions of Peshawar, aiming to provide insights into potential scenarios during a seismic event. By employing the RVS method, the study highlights the vulnerabilities present in Hashtnagri, an older, unplanned urban area. Findings reveal that masonry structures, which dominate the residential building category, are particularly susceptible to earthquakes due to various vulnerability factors. The research underscores the importance of addressing urban physical vulnerabilities and proposes policy-based strategies to support the redevelopment and seismic resilience of areas like Hashtnagri.

The findings underscore the urgent need for a comprehensive and long-term plan to rehabilitate unplanned parts of the city. This includes mitigating the daily risks faced by residents through better urban planning and enforcement of construction regulations. The study further establishes a significant correlation between the physical vulnerability of buildings and residents’ risk perception in both planned and unplanned settings. In Hashtnagri, 27.5% of buildings exhibit high seismic vulnerability compared to only 10% in the planned WAPDA Town, which is less than 50% of the old Hashtnagri. This disparity can be attributed to unregulated urban growth, poor construction practices, and a lack of adherence to seismic safety measures in unplanned areas, leading to higher vulnerability and increased risk perception among residents.

The risk perception index exhibits significant variation with changes in the physical vulnerability of buildings. This finding indicates that individuals residing in highly vulnerable structures tend to perceive substantially higher levels of risk. Such insights are valuable for formulating future risk-mitigation strategies and for guiding preparedness and planning efforts. Given that conducting detailed vulnerability assessments for all buildings within a region is often impractical, questionnaire-based surveys offer an efficient alternative for identifying the types of risks faced by the community and for informing targeted interventions.

This research provides valuable insights for authorities, urban planners, and communities, offering guidance for sustainable urban development and risk management strategies. It highlights the importance of proactive measures to reduce seismic vulnerabilities and foster resilience, ensuring safer living conditions for residents in both planned and unplanned urban areas.

7. Assumptions and Limitations

• All buildings were observed from the outside and through face-to-face interviews to predict their physical condition; however, testing and close observations would certainly provide better insight.
• Foundations play an important role in assessing the vulnerability of a structure; however, due to observation difficulty, they were excluded from this study.
• The weightage assigned to each vulnerability factor varied from 0 to 1. The weightage was based on the opinion of the researcher and varied from person to person.
• The effects of planning status and construction materials were not assessed separately due to the mixed nature of the building stock. Future studies may improve this by using comparative building groups and statistical analyses to better distinguish the individual contribution of different vulnerability factors to seismic risk.
• Uneven population and building density across the study area may have introduced minor sampling bias, which could slightly influence the overall vulnerability estimates.