Visualizing Travel Accessibility in a Congested City Center: A GIS-Based Isochrone Model and Trip Rate Analysis Considering Sustainable Transportation Solutions

Abstract

Urban settlements often deal with the massive transportation problems caused by mixed land-use development and improper travel services. This situation propels travel accessibility issues within urban centers. This research is intended to focus on the 3rd largest city of Pakistan’s Sindh province, i.e., Sukkur, where residents were found struggling to reach their desired destinations. The study area has naturally grown without planning guidelines, generating traffic congestion and haphazard land-use patterns. This research aims to measure accessibility within the city center using trip rate analysis and a GIS-based isochrone model (1-km radius). In total, 234 household trips were randomly considered according to Morgan’s sampling standards. The results revealed that scattered locations caused heavy traffic volumes without public transport facilities. The ratio of traveling by bike for shopping was recorded at 17.24%. Commuting by car; home-based, health, and shopping trips were ranked 1st (5.52%), 2nd (2.76%), and 3rd (1.38%), respectively. The isochrone-based maps were delineated to clarify the temporal accessibility features. Only three shopping activities were found to be accessible within 6 min. Most of the banks were found to be highly accessible. None of the health facilities were located within a 0–6 minute isochronal boundary. Two entertainment sites were accessible within 0–6 min. The residential neighborhoods were not close to the city center. Only three parks and six religious facilities were accessible within 6–12 min. The study findings clarified mixed land use activities accessed through multiple travel modes in the city center. Executing traffic management implications is a need of the time to induce sustainable transportation guidelines. Besides, the results may contribute to SDG 11.2, i.e., “affordable and sustainable transport systems” available for local commuters. The findings of this study are also relevant to evaluating the progress of some cities on SDG 11.2 regarding accessing feasible transportation services.

1. Introduction

After the Industrial Revolution, world cities grew at a rapid pace; however, most of the cities situated in developing countries became congested and lost their planned identity [1]. The growth of unplanned land use puts immense strain on transportation services to meet the basic travel accessibility requirements [2]. Substantial shifts in land use trends affect the number of trips, destinations, and travel modes [3,4]. Major cities in developing countries are struggling with urbanization, population growth, and motorization difficulties [5]. The notable issues included clogged roads, car crashes, increased land demand, travel inaccessibility, and adverse effects on transportation systems [6,7]. Significant improvements in transportation networks influence the number of journeys, destinations, and travel modes [8]. Most developed nations, notably America and countries in Europe, have integrated land use activities and transportation models to achieve sustainable transportation planning targets [9,10]. The majority of emerging nations, however, have not embraced sustainable planning strategies. In the meantime, a few cities on the Chinese mainland have begun to develop urban models that could integrate land use planning approaches, sustainable transportation measures, and environmental protection with the help of the planning process [11,12].

Interaction between transport and land use planning has been determined for years using various methods; hence, the well-known approach may be known as travel accessibility [13,14,15,16]. Conventional accessibility models fall short of taking on urban travel issues that require prompt solutions [17]. Accessibility is a dynamic tool that varies depending on the travel modes to cope with the present transportation networks and activity-distribution patterns [18,19]. A variety of sustainable accessibility models should be taken into consideration because, in theory, economic activities often depend on the adequacy level of travel accessibility [20]. Thus, to comprehend the urban system, it is imperative to map travel accessibility patterns, as remedial measures can be implemented.

There is a strong link between travel accessibility and land use activities [21]. Planned land use activities, together with the provision of sustainable transportation services, may encourage investors to gain socioeconomic benefits in the larger interest of the country [22]. In the 1970s, researchers highlighted the importance of accessibility parameters to evaluate transportation systems and their components concerning land use projects [23]. This was taken after a prolonged inaccessibility period while reaching essential locations and job opportunities [24,25]. Accessibility indicators define the location of an area concerning opportunities, events, or assets present in other places, as well as in the place itself, where “place” may be a country, a city, or a corridor, and “area” may refer to a state, a town, or a land use [26,27,28]. “Active” and “passive” are the two forms of accessibility that may be used to evaluate the accessibility standards of particular locations [29,30]. Moving from zone (i) to zone (j) for a given purpose, the active accessibility of a given zone (i) is a proxy linked to an easement, when an individual reaches certain opportunities located at zone (j) like a workplace and shopping.

Keeping in view the importance of travel accessibility, this study focuses on measuring accessibility by executing a GIS-based isochrone model and trip rate analysis. The study area is selected as Sukkur, Pakistan, struggling with issues in the context of horizontal growth, irregular expansion, unintegrated land uses, and a lack of public transportation services. This condition has turned the town into a motorized urban settlement, but the dramatic rise in traffic volume resulted in the development process of the city. The study area became more congested and crowded, which further propelled traffic-management issues over time. The standardized travel time to reach an activity is five minutes [31,32]. Meanwhile, it takes a longer travel time to access essential activities in the most congested urban centers in the world [33,34]. Therefore, this study plans to measure travel accessibility, as related problems could be diminished to strengthen the travel accessibility standards of local commuters. This research experimented with isochrone-based mapping to measure accessibility for the first time in the Pakistani context. None of the studies were found that ever discussed GIS-based isochrone modeling and trip rate analysis considering the local travel modes of the country. In the same way, a few examples can be cited in the available literature on this research subject matter globally.

2. Literature Review

The length of a trip from home to work using public transportation services can be employed to verify travel accessibility standards. Research on travel accessibility is limited to focusing on modern techniques [35,36]. Access to this information is available through newspapers, Internet providers, and libraries. Access to routine work is possible using certain travel modes, including public transportation services. In this context, employment-generating activities, shopping areas, community centers, health, or education institutions, and recreational facilities may be termed as opportunities [37,38,39]. The conventional hypothesis of accessibility assessment is restricted to destinations that can be visited in fixed time constraints [40,41,42].

The derived essence of transportation demand necessitates a transition from mobility-based to accessibility-based assessment [43]. Mobility is, thus, adequately understood as a means to an end with proximity and remote electronic communication to promote accessibility [44]. To be consistent with the concept that transportation demand is predominantly derived, transportation and land use systems must be discussed and evaluated categorically in terms of accessibility rather than mobility [45]. In North America, accessibility planning has begun to influence planning practice at regional and land use scales and is more typically a complement than a replacement for mobility-based appraisal [46]. Globally, different countries have varied goals when it comes to travel accessibility. For example, the city zone in Wuhan, China, picked a place for a facility [47], and Naples, Italy, planned an urban area [48]. Place-centered (passive) and individual-centered (active) accessibility are the two prime categories of accessibility measurement [49]. The concept of individual-centered accessibility sees accessibility as a person’s capabilities to reach desired destinations and acquire services. On the other hand, the place-centered accessibility method highlights accessibility in terms of places or locations [50,51].

For 20 years, a group of transport researchers and analysts has pushed for accessibility initiatives to assess urban transportation systems [52,53]. In this regard, focusing on accessibility as a performance metric is promising since such an indicator acquires the contribution of the transport network to economic prosperity [54]. Accessibility initiatives validate the prospective methods for improved land use planning to extend the use of transportation facilities [55]. Contrary to popular belief, metropolitan planning agencies stand out in terms of implementing accessibility-based steps [56]. The Puget Sound Regional Council (PSRC), for example, executed a variety of accessibility tools in its long-range transportation plan assessment and regional scenario preparation [57].

Some of the oldest urban planning concepts are based on accessibility in the context of urban structures and agglomeration economies [58]. Nonetheless, recent trends have centered on the value of accessibility as a critical principle [59]. Accessibility has emerged as a fundamental aspect in encouraging active living and specifying vigorous access to nature. Cities facilitate inhabitants accessing a wider range of socially relevant assets [60]. Recent trends have disclosed the latest requirements for physical activity and connectivity to nature within communities. Later, the value of affluent access and certain options for addressing the needs of citizens may be treated to improve urban livability indicators [61,62].

Most researchers believe that mobility options, such as walking, cycling, or public transportation services, are beneficial for vibrant economic activities [63,64]. People enjoy frequent types of journeys, such as countryside drives or vacations. Even ordinary trips, like the purchase of grocery items from distinct locations, can take a longer travel time. However, research has shown that most people would like to spend less time while traveling to reach essential activities [65]. As travel demand increases, there is a rise in traffic congestion, which may put enormous pressure on accessibility parameters. Therefore, researchers have used the travel diary to obtain reliable transport data that may define important variables [66]. Primarily, age and car availability are the most critical person-specific explanatory variables, followed by income level. The relevance of transit accessibility for trip-generation rates is demonstrated in around half of the itemized research, confirming the initial notion of this dependency. In the meantime, the total number of trips may be computed as follows:

$$P_I=\sum h{N}_h{R}_h$$

(1)

where

$P_I$ = Total number of trips

$\sum h{N}_h{R}_h$= h highlights the number of household types that existed in a study zone.

N_h denotes the total number of household types as per availability of vehicles.

R_h clarifies trip production rates according to household types.

Equation (1) can assist in computing the household trips in a related study area to perform essential activities. Meanwhile, the generalized mathematical format reflecting the trip-generation regression model can be seen in Equation (2).

$$\mathrm{Y}={\beta }_0+{\beta }_1{\mathrm{X}}_1+{\beta }_2{\mathrm{X}}_2+{\beta }_3{\mathrm{X}}_3\dots {\beta }_n{\mathrm{X}}_{\mathrm{n}}$$

(2)

where

• Y = dependent variable (number of household trips generated within a study zone).
• X₁, X₂, X₃ … X_n = travel time, travel distance, trip cost, household size or income, etc.
• β₀, β₁, β₂, β₃ … β_n = regression beta constants.

Numerous factors can influence accessibility. These include transportation demand, mobility, land use patterns, the number of available activities, time, and the distance to reach a particular location. Thus, GIS-based isochrone modeling can be regarded as an optimum solution to measure relevant parameters of accessibility. The mathematical expressions of the isochrone technique can be seen in (3) and (4).

$$a_0\left(\mathrm{d}\right)=\mathrm{K}\left(\mathrm{d}\right)·W_{0d}\hspace{1em}{\mathrm{AA}}_0=\mathrm{K}\left(\mathrm{d}\right)·W_{0d}/\mathrm{m}$$

(3)

where

• ${\mathrm{a}}_0$(d) is the availability of activities within a highly accessible isochronal boundary.
• K(d). W_0d is the number of activities available in the destination zone.
• AA₀ highlights the availability of particular activities for class 0 that need 0–6 min of travel time.
• W_0d/m shows the travel time in minutes (m) commuted through a particular travel mode.

$$\begin{gathered} {\mathrm{W}}_{0\mathrm{d}}/\mathrm{m} (t_{0d}/\mathrm{m})=1{\mathrm{t}}_{0\mathrm{d}}/\mathrm{Car}\le {\mathrm{t}}_{\max } \\ \hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}0{\mathrm{t}}_{0\mathrm{d}}/\mathrm{Car}\le {\mathrm{t}}_{\max } \end{gathered}$$

(4)

where

• W_0d/m ($t_{0d}$/m) highlights the travel time required to reach destinations as per two classes 1 and 0.

In urban planning and public transportation management, the isochrone map is a traditional visual–analytical tool that may be used to measure place-centered accessibility with temporal constraints [67]. Using points, lines, or area isochrones, it shows the trip time from a specified origin point in the area of interest [68]. Isochrone maps serve as a passive accessibility measure by visualizing time [69], which is frequently more important to travelers than distance [70]. The digital maps may then be easily incorporated into spatiotemporal accessibility analysis [71] and are especially helpful in time-related accessibility metrics [72]. Using a three-dimensional space–time prism [73], the isochrone area can be seen as a horizontal slice, and its area can be used to calculate travel accessible at a time window. Thus, in the light of reviewed literature on accessibility measures, this study picks an isochrone-based accessibility tool to measure the accessibility of urban commuters for the first time in Pakistan.

3. Data and Methods

To achieve the study objectives, we selected appropriate methods with the help of the reviewed literature. Trip rate analysis and a GIS-based isochrone model were picked for this study. Consequently, the nature of the study objectives required a variety of data inputs that can be reviewed henceforth.

3.1. Data

Before moving further toward the collection of suitable data, it is always vital to first discuss the demographics of the study area. So, the population of Sukkur, according to various censuses and projections, has been detailed in

Table 1. Population, area, and density of Sukkur.

Census	Estimated Population
1998/2017	2008/2020	2015/2022	2020/2025	2021/2030
908,373	1,100,033	1,221,578	1,362,668	1,526,868
Area and Population Density
Area (Sq. k.m)		5.165
Density (per sq. k.m)		175.900

.

Table 1 indicates the existing and projected demographics of the study area. The administrative boundaries of Sukkur city were divided into 20 wards (administrative units). In the year 2022, the population of Sukkur was estimated at 1,221,578. The sample size was determined by dividing the overall population ratio by the population of each ward. Thus, the population of a single ward was estimated at 1,221,578/20 = 61,078.900. Based on a significance level following Krejcie and Morgan [74], the sampled population was computed by taking 1% of the total population, i.e., 61,078.900 × 1/100 = 610.789. This number of inhabitants was considered for the data-collection process. Therefore, a total number of 234 sampled household trips were considered to complete the objectives of this study. This sample size was found to be appropriate when compared to the average household size of Sukkur, i.e., 234 × 7.69 = 1800. This value is almost three times higher than the determined population sample. The questionnaire survey was conducted to procure the data from the 234 randomly selected commuters, as described in Table 2. The survey lasted for approximately fifteen days. The peak and off hours were specifically chosen to further clarify the travel-accessibility problems. The survey was conducted by two teams of undergraduate students at Mehran University of Engineering and Technology, Pakistan.

3.2. Study Area

Sukkur is a town situated on the west bank of the Indus River in the Pakistani province of Sindh. It is Pakistan’s 12th most populous city and is ranked 3rd in Sindh province [75]. The study area can be seen in Figure 1.

In Figure 1, the yellow color shows the whole area of the Sukkur District. Meanwhile, the Sukkur Center is depicted in orange. City centers always face congestion due to increased travel demand over the years. Appropriately, a GIS-based isochrone model and trip rate analysis were executed to measure the accessibility standards of the local commuters.

3.3. Trip Rate Analysis

The phrase “trip rate analysis” refers to the total number of average trips generated to perform essential activities in each zone. Hence, trip rate analysis was used to compute the number of trips produced in the study zone. Considering Equation (1), the total number of trips was determined:

      = 71 + 71 + 191 + 436 + 143 + 366 + 50 + 199 + 492 + 10
 = 2030 internal trips within the zone.

This is the massive number of trips generated in the study area that further intensified the congestion and delay problems. Therefore, increasing travel time or delays, combined with higher travel costs, reduced the accessibility standards of the local commuters. Finally, a sample size of 234 household trips was selected by randomly considering multiple trip purposes, as clarified in Table 2. Considering the sampled population, i.e., 610.789, the trip data of 234 households were found to be appropriate, keeping in view that the average household size is 7.69. Hence, the sampled data were found ideal and well beyond the standard sample size, which truly reflects the population size of 1800, i.e., three times higher than the actual population sample. Table 2 clarifies the seven types of trip purposes, including shopping, business, health, and recreation. In total, 40 household trips were completed by car, bike, and Ravi pickup for shopping. Likewise, 25 trips were produced by car or bike, and the purpose of the trips was noted as banking/business.

Table 2. Sampled household trips using travel modes for specific trip purposes.

Number of Household Trips (Sampled)	Trip Purposes	Travel Modes
40	Shopping	Car, Bike, Ravi pickup 1
25	Bank/business	Car, Bike
35	Health	Car, Bike, Ravi pickup 1, Rickshaw (tuk-tuk) 2
17	Entertainment	Car, Bike
50	Home-based	Car, Bike, Ravi pickup 1
35	Recreational	Car
32	Religious	Car, Bike

¹ A Ravi pickup is a four-wheeler cargo van used for the transportation of goods and people. ² A rickshaw (tuk-tuk) is a three-wheeler vehicle used to access local urban activities.

Table 2. Sampled household trips using travel modes for specific trip purposes.

Number of Household Trips (Sampled)	Trip Purposes	Travel Modes
40	Shopping	Car, Bike, Ravi pickup 1
25	Bank/business	Car, Bike
35	Health	Car, Bike, Ravi pickup 1, Rickshaw (tuk-tuk) 2
17	Entertainment	Car, Bike
50	Home-based	Car, Bike, Ravi pickup 1
35	Recreational	Car
32	Religious	Car, Bike

¹ A Ravi pickup is a four-wheeler cargo van used for the transportation of goods and people. ² A rickshaw (tuk-tuk) is a three-wheeler vehicle used to access local urban activities.

Certain types of travel modes can be seen in Table 2. It should be noted that Ravi pickup is a 1000 cc four-wheeler cargo van locally assembled in Pakistan. In this country, a Ravi pickup is often used for the travel of people and the transportation of goods. This vehicle assists the local population and businesses in carrying out the loading and transportation of services. The loading capacity of the Ravi pickup vehicle is 600 kg. On the other hand, a rickshaw (tuk-tuk) is a three-wheeler vehicle operated across Pakistan. The rickshaw (tuk-tuk) is Pakistan’s largest informal public transport mode. Sazgar is a premier local manufacturer in Pakistan. The rickshaw (tuk-tuk) has a carrying capacity of six passengers plus a driver. It is ideal for fixed routes in urban areas of Pakistan, particularly for school-going children, shopping, and public sector employees.

Table 3. Cross-classification of trip rate analysis with availability of vehicles per household.

Household Categories with Vehicles Available per Household	Household Size
0	3–5	5–7	8–10
1	3–5	5–7	8–10
2	3–5	5–7	8–10
3	3–5	5–7	8–10

indicates four different household categories ranging from 0–3 according to the availability of vehicles. For each category, three slabs of household size were defined, i.e., 3–5, 5–7, and 8–10. The required number of households was acquired from the census report of 1998/2017, and the same was projected for the year 2017/2030. From the sampled data, the trip rate was driven. Finally, the number of household trips (trip rate) and total household trips generated in a day per zone were decided. Likewise, it should be noted that only 234 sampled trips were considered randomly to accomplish the objectives of this study.

3.4. Isochrone Model

The integral accessibility concept was followed in this study, which is defined as the average number of perceived opportunities for an operative station at a particular location to see a relationship between activities and available travel modes. Alternative places are actual locations where people may perform certain activities, such as shopping, or recreation. Multiple types of factors can influence accessibility standards. These include travel demand, trip purpose, land use patterns, travel time, and the availability of suitable travel modes. These factors can directly or indirectly affect transportation activities, practices, and mode choices in city centers. City centers always face congestion due to increased travel demand. There was no suitable traffic management plan available in Sukkur. Public transport and pedestrian facilities were not found to be suitable in the study area. Consequently, due to acute traffic congestion, more travel time was required to reach the desired destinations. Hence, to address travel accessibility gaps in the city center of Sukkur, researchers observed trips concerning certain travel modes. Afterward, the isochrone-based travel-accessibility model was executed to visualize the time required to reach certain destinations considering the chosen travel modes and trip purposes.

The mathematical formats of the isochrone model can be seen in Equations (5)–(7).

$$a_0 \left(\mathrm{d}\right)=\mathrm{K}\left(\mathrm{d}\right)·W_{0d} {\mathrm{AA}}_0=\mathrm{K}\left(\mathrm{d}\right)·W_{0d/\mathrm{m}}$$

(5)

where

• ${\mathrm{a}}_0$(d) verifies the availability of activities within a highly accessible isochronal boundary.
• K(d). W_0d is the number of activities available in the destination zone.
• AA₀ shows accessibility depending on the isochronal boundary.
• K(d)⋅${\mathrm{W}}_{0\mathrm{d}}$/m confirms the number of activities available in the isochronal boundary as per its relationship with Equation (6).

The number “1” is assigned if activities are reachable within the available time limit of the isochronal boundary, otherwise the number “0” is assigned.

$$\begin{gathered} \hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}1 t_{0d}/\mathrm{Car}\le {\mathrm{t}}_{\max } \\ {\sum }_{d=1}^n=W_{0d}/m (t_{0d}/m)= \\ \hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}0 t_{0d}/\mathrm{m}>{\mathrm{t}}_{\max } \end{gathered}$$

(6)

where

• $\sum _{d=1}^n=$ destinations reachable within the time limits of specified classes as seen in (7).

Different temporal criteria were used to measure the threshold values of isochronal boundaries seen in Equation (7):

$$\begin{gathered} \hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em} 1 \mathrm{if} t_{0d}\le 6 \min \\ \hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em} 2 \mathrm{if} 6 \min < t_{0d}\le 12 \min \\ \hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\mathrm{Classes}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}=\hspace{1em}\hspace{1em}\hspace{1em} 3 \mathrm{if} 12 \min <t_{0d}\le 18 \min \\ \hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em} 4 \mathrm{if} 18 \min < t_{0d}\le 24 \min \\ \hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em} 5 \mathrm{if} 24 \min < t_{0d}\le 30 \min \end{gathered}$$

(7)

The five diversified classes mentioned in Equation (7) depict the isochronal boundaries, which were mapped according to the isochrone distance that people traveled within their time limits from the reference point. The distinct categories depicted in Equation (7) state that if an activity time is ≤6 min, it should be mapped in the 1st isochronal boundary. If the activity time is >6 min and <12 min, it is placed in the 2nd isochronal boundary. Similarly, if the activity time is >12 min but <18 min, it is situated in the 3rd isochronal boundary. A similar approach is used for the rest of the categories.

4. Results

Due to its unplanned growth, Sukkur city has faced a massive traffic congestion problem over the years. Simultaneously, its residents have been found struggling to reach their desired destinations on time. Residents face travel delays to reach desired destinations, which negatively affects their performance in completing necessary activities efficiently. So this study was articulated by executing the trip rate analysis and a GIS-based isochrone model (within the city center and a 1 km radius). Furthermore, the average cumulative trips generated by specific household categories according to household size were studied as depicted in

Table 4. Trip Rates by Specific Types of Households Concerning Household Size.

Household Categories with Vehicles Available per Household	Trip Rates as per Household Sizes
	3–5	6–7	8–10
0	0.250	0.500	0.250
1	0.409	0.227	0.363
2	0.330	0.660	0.000
3	0.660	0.330	0.000

.

Table 4 reveals household categories with available vehicles, i.e., 0, 1, 2, and 3, concerning household size ranges from 3 to 5, 6 to 7, and 8 to 10. As per the data, when the households have 0 available vehicles, an average of 0.250, 0.500, and 0.250 trip rates were noted in conjunction with the respective household sizes, like 3–5, 6–7, and 8–10.

4.1. Existing and Estimated Housing Units

According to the census report 2017, there were a total of 43,643 households in Sukkur city. Sukkur's municipal areas were divided into 20 wards (locally administered land use divisions). Hence, there were 2182 households found in each study zone. Over time, there must have been a growth in the housing units and population.

The demographic data were obtained from the census report of 2017, with 908,373 inhabitants, and the same was projected as 1,526,868 up to the year 2030 (please see Table 1). For estimating the number of housing units from 2017 to 2030, we have divided the increased population, i.e., (1526, 868–908, 373 = 618,495) by the average household size, i.e., 7.69 [76]. Thus, the total number of households was found to be 80,428. Suppose 50% of the houses were constructed within 13 years; still, 40,214 housing units are required to meet the population needs up to the year 2030. Now, by adding both available housing units in the year 2017, i.e., 43,643, and the year 2030, i.e., 40,214; the total estimated number would be 43,643 + 40,214 = 83,857. Now, dividing the estimated total housing units by 20 wards, the number of housing units was calculated to be 4192 in the study zone.

Table 5. Estimated household sizes in the zone to vehicle availability.

Vehicles Available per Household	Household Size
	3–5	6–7	8–10
0	284	568	284
1	1090	630	1009
2	151	302	0
3	75	37	0

clarifies the number of vehicles available as per different ranges of household size. When household size ranged from 3 to 5, 284 households were found without any vehicle, i.e., “0”. Furthermore, when the household size categories were 6–7 and 8–10, a total number of 568 and 284 households had no vehicles. In the same way, when the household size was 3–5, 1090 households had only one vehicle. For household sizes ranging from 6 to 7 and 8 to 10, a total number of 630 and 1009 households possessed only one vehicle. Further, the percentage of trip distribution according to trip purposes using specific travel modes can be seen in Figure 2.

As depicted in Figure 2, most of the trips were completed by the travel mode of the bike. Car, rickshaw (tuk-tuk), and Ravi pickup were ranked second, third, and fourth, respectively. Figure 2 also clarifies the residents’ mode of choice to access certain essential activities in the study area. The total proportion of home-based trips completed by bike was almost 22.76%. Furthermore, 20.69% of work-based trips were noted using the travel mode of the bike. Using the same travel mode, 17.24% of the trips were conducted for shopping. For the travel mode of car, the proportions for various purposes, like home-based, health, and shopping, were found to be 5.52%, 2.76%, and 1.38%, respectively. The aim of developing Figure 2 was to understand the model split based on land use and trip purposes.

In the choice of travel mode (modal split), travel distance plays a significant role. The expansion of cities in an irregular pattern is becoming one of the causes of excessive trip generation. Hence, factors that affect accessibility standards were determined. Meanwhile, factors like demographics, travel distance, travel cost, trip time, and travel modes were examined in this study.

4.2. Execution of Isochrone Model for Prescribed Activities

Certain types of trip purposes were recorded and mapped in light of Equations (5)–(7). Instantly, three shopping areas were measured concerning the number of shops that were traveled to within 0–6 min. Following the parameters of the isochrone model, commuters who took 9 min to reach shopping areas available within 1 km were studied. AA₀ refers to shopping activities for class 1 that require ≤ 6 min of travel time and is calculated using Equation (8).

AA₀ = 3 × 1 + 0

(8)

Only three shopping activities were found to be accessible within 6 min, which are shown in the first isochronal boundary of Figure 3. The number “0” represents that there were only three activities accessible within 6 min other than “0”. In the zone, if any activity took a travel time > 6 min based on the predefined categories, isochronal lines were drawn according to travel time.

4.3. Delineating Isochronal Boundaries

First, the region was separated into different zones, and then an isochrone technique based on route references was employed. General requirements for producing isochronal boundaries to measure active accessibility can be reviewed as follows:

• Sampled travel time data were collected, which can be seen in Tables 7–13.
• Average travel distance was derived through the Google Maps distance calculator.
• Isochronal boundaries and activities were mapped with the help of GIS for predefined classes.
• The mapping of the isochrone boundary was based on the commuter’s average travel time to reach desired destinations. Travel time was classified into various categories, i.e., ≤6 min, 6–12 min, 12–18 min, 18–24 min, and 24–30 min.

The information about the isochrone boundaries for each of the five classes can be seen in

Table 6. Classification of isochronal boundaries.

Isochronal Boundary (Class-Wise)	Travel Time	Boundary Distance from a Reference Point
1	≤6 min	0.667 km/667 m
2	6–12 min	1.333 km/1333 m
3	12–18 min	2 km/2000 m
4	18–24 min	2.667 km/2667 m
5	24–30 min	3.333 km/3333 m

.

Table 6 highlights the mapping phenomenon of isochronal boundaries based on travel time and distance. Activities that fall under the first isochronal boundary of (0.667 km) from the city center (Ghanta Ghar) can be reached in ≤6 min. The second isochronal boundary depicts that the travel time to reach certain activities falls within the range of 6–12 min. The third clarifies that activities can be completed in 12–18 min, while the fourth revealed that activities located under it can be reached in 18–24 min. The fifth isochronal boundary highlighted that 24–30 min may be required to access essential activities. It should be noted that the isochronal boundaries may overlap with each other because of the same end and starting travel time slots, i.e., 0–6, 6–12, 12–18, etc.

4.4. Development of GIS-Based Isochrone Maps

Based on five isochronal boundary classes, the isochrone maps were generated according to household trip purposes, as shown in Figure 3, Figure 4, Figure 5, Figure 6, Figure 7, Figure 8 and Figure 9. The travel cost estimations for shopping can be seen in Table 7.

Table 7. Travel cost, distance, and time estimations for shopping trips.

Travel Modes’	Travel Distance (m)	Travel Time (min)	Fuel Cost (PKR)	Parking Cost (PKR)	Tolls (If Any)	Indirect Cost	Total Cost *
Car	4952.660	44.573	26.520	20	No	0.049	46.922
Bike	1486.330	10.772	20.266	10	No	0.014	30.551
Ravi Pickup	2273.330	12.760	10.028	20	No	0.022	30.185

* Total travel cost is shown in Pakistani Rupees (PKR).

Table 7. Travel cost, distance, and time estimations for shopping trips.

Travel Modes’	Travel Distance (m)	Travel Time (min)	Fuel Cost (PKR)	Parking Cost (PKR)	Tolls (If Any)	Indirect Cost	Total Cost *
Car	4952.660	44.573	26.520	20	No	0.049	46.922
Bike	1486.330	10.772	20.266	10	No	0.014	30.551
Ravi Pickup	2273.330	12.760	10.028	20	No	0.022	30.185

* Total travel cost is shown in Pakistani Rupees (PKR).

Figure 3. Vehicular-based isochrone line distribution for shopping-based trips.

Figure 3. Vehicular-based isochrone line distribution for shopping-based trips.

Table 7 displays that the average travel cost for shopping using the mode car was recorded at PKR 46.922. The average travel cost using the mode bike was PKR 30.551, and the average cost using a Ravi pickup was PKR 30.185. Hence, the average cost of all three modes was recorded at PKR 35.909. The average travel distance and time of a single trip for shopping using the car mode were noted as 4952.660 m and 44.573 min, respectively. The same values using the bike mode were recorded as 1486.330 m and 10.772 min. To achieve the distance of 2273.330 m using mode Ravi pickup, it took 12.760 min average time for a single trip. Figure 3 was drawn for shopping purposes using the same data as described in Table 7. In Figure 3, the shopping locations are denoted with 10 dark black circles. Three of the shopping locations were universally accessible within 0–6 min. Five shopping locations were reachable in 6–12 min, as depicted in the red area. Only two shopping areas were found to be less accessible, as they were available within the time slot of 12–18 min. Travel costs and related data about the trips related to business purposes can be seen in

Table 8. Travel cost, distance, and time estimations of business trips.

Travel Modes’	Travel Distance (m)	Travel Time (min)	Fuel Cost (PKR)	Parking Cost (PKR)	Tolls (If Any)	Indirect Cost	Total Cost *
Car	750	10	4.016	20	No	0.007	24.077
Bike	650	9	8.862	10	No	0.006	18.986

* Total travel cost is shown in Pakistani Rupees (PKR).

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Table 8 indicates that the average trip costs using the car and bike modes for business purposes were recorded as PKR 24.077 and PKR 18.986, respectively. The average cost of both modes was found to be PKR 21.531. It should be kept in mind that the average distance was noted as 750 and 650 m, respectively. The average travel time was found to be 10 min using the travel mode of car and 9 min using the bike.

The isochrone-based model for business trips followed the same predefined procedure. Banking trips were observed as the major business trips in the study area. In the business zone, other destinations were also noticed, such as schools, hospitals, mosques, commercial areas, parks, playgrounds, and graveyards. This further clarified the mixed land use features of the study area. The existence of multiple activities in any zone always affects the choice of travel mode, as shown in Figure 4.

Figure 4. Vehicular-based isochrone line distribution for business-based trips.

Figure 4. Vehicular-based isochrone line distribution for business-based trips.

Figure 4 shows that most of the commercial banks are located within the highly accessible zone, i.e., 0–6 min. A few of them were available at 6–12 min travel time. The customers accessed different banks on a car or bike, according to local traffic situations during peak and off-hours of the day. The estimated cost, travel time, and distance characteristics of trips made to access health facilities can be seen in

Table 9. Estimation of travel cost, travel distance, and time for health trips.

Travel Modes’	Travel Distance (m)	Travel Time (min)	Fuel Cost (PKR)	Parking Cost (PKR)	Tolls (If Any)	Indirect Cost	Total Cost *
Car	683.330	17.500	3.659	20	No	0.006	23.714
Bike	1866.660	10.000	25.450	10	No	0.001	35.791
Ravi Pickup	0	0	0	0	No	0	0.000
Rickshaw (tuk-tuk)	270.000	5.000	10.705	15.000	No	0.002	25.730

* Total travel cost is shown in Pakistani Rupees (PKR).

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Table 9 shows travel characteristics of trips for the purpose of health. The average costs in PKR using the car, bike, Ravi pickup, and rickshaw (tuk-tuk) modes were found to be 23.714, 35.791, 0.000, and 25.730, respectively. The total average cost was computed as PKR 28.412. The average travel distance covered by a car for a single trip for health purposes was recorded as 683.330 m, and the average time was determined as 17.500 min. The distance traveled through the travel mode of the bike was the highest at 1866.660 m. The travel time was found to be comparatively shorter than the car, i.e., 10 min. This was because of the traffic situation in the study area, as bikes can be maneuvered easily in congested busy streets. The trips made by the rickshaw (tuk-tuk) covered 270 m, and the average time for a single trip for health purposes was recorded as 5 min. It can be observed that the distance of a single trip was walkable within 1 km. However, people opted for motorized vehicles to reach the desired destinations. The possible reasons are the unavailability of a walking environment, pedestrian tracks, or public transport facilities. As a result, more than 2000 trips were made within the zone every day, which put immense pressure on the overall traffic situation of the study area. The isochrone-based model for health trips can be seen in Figure 5.

Figure 5. Vehicular-based isochrone line distribution for health-based trips.

Figure 5. Vehicular-based isochrone line distribution for health-based trips.

It is shown in Figure 5 that the situation of health accessibility was not satisfactory in the study area. Only three health institutions were found accessible within the travel time range of 6–12 min. Only three health facilities were accessible within 12–18 min, whereas the rest of them were accessible within the range of 24–30. As compared to other related activities, health services were found to be inaccessible, as none of the hospitals were found to be accessible in the 0–6 time slot. After that, trips made for entertainment purposes were measured, which are shown in

Table 10. Estimation of travel cost, travel distance, and time for entertainment trips.

Travel Modes’	Travel Distance (m)	Travel Time (min)	Fuel Cost (PRs.)	Parking Cost (PRs.)	Tolls (If Any)	Indirect Cost	Total Cost *
Car	820.000	9	4.284	20	No	0.082	24.423
Bike	966.660	11	13.180	10	No	0.096	23.452

* Total travel cost is shown in Pakistani Rupees (PKR).

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Only two travel modes were recorded when commuters accessed recreation or entertainment locations, as shown in Table 10. When commuters selected a car as a travel mode, it cost them PKR 24.423. In the meantime, the total cost was computed as PKR 23.452 for the bike travel mode. The average cost of entertainment trips was determined as PKR 23.937. The average travel distance and time by car for entertainment-based trips were 820 m and 9 min, respectively. The same results were recorded as 966.660 m and 11 min when commuters chose the travel mode bike. It should be noted that entertainment-based trips were for dinner gatherings, cinemas or theatres, gymnasiums, parks, zoos, etc. An isochrone-based map was created for the entertainment-based trips, as seen in Figure 6.

Figure 6. Vehicular-based isochrone line distribution for entertainment-based trips.

Figure 6. Vehicular-based isochrone line distribution for entertainment-based trips.

Only two entertainment locations were found to be universally accessible within the time limit of 0–6 min as depicted in Figure 6. In total, nine entertainment places were accessible within 6–12 min. Just one entertainment facility required 18–24 min of travel time. Hence, it can be said that the overall picture of entertainment accessibility was found to be satisfactory, as most of the sites were accessible within 15 min of travel time.

Referring to Table 11, the average travel cost of home-based trips was determined to be PKR 46.922, 30.550, and 30.185 using the modes car, bike, and Ravi pickup, respectively. The total average cost using the same modes was found to be PKR 35.886. The average travel distance covered by car was 4952.660 m, and the average time of a single trip was calculated as 15.55 min. For travel by bike, the same parameters were measured as 1486.330 m and 14.766 min. Using the Ravi pickup mode, these parameters were found to be 2273.330 m and 15 min. From this description, it can be justified that homes were situated in the urban vicinity. The sprawl in the study area in recent years forced commuters to travel longer distances to reach the urban core. Travel distances highly influenced the choice of travel modes, especially for home-based trips. The non-existence of an adequate public transportation system forced residents to purchase vehicles. However, in Sukkur, there was no public transportation system, only Ravi pickups over the specified routes. The graphical representation of home-based trips can be seen in Figure 7.

Table 11. Estimation of travel cost, travel distance, and time for home-based trips.

Travel Modes’	Travel Distance (m)	Travel Time (min)	Fuel Cost (PKR)	Parking Cost (PKR)	Tolls (If Any)	Indirect Cost	Total Cost *
Car	4952.660	15.550	26.520	20	No	0.049	46.922
Bike	1486.330	14.766	20.266	10	No	0.014	30.551
Ravi Pickup	2273.330	15	10.028	20	No	0.022	30.185

* Total travel cost is shown in Pakistani Rupees (PKR).

Table 11. Estimation of travel cost, travel distance, and time for home-based trips.

Travel Modes’	Travel Distance (m)	Travel Time (min)	Fuel Cost (PKR)	Parking Cost (PKR)	Tolls (If Any)	Indirect Cost	Total Cost *
Car	4952.660	15.550	26.520	20	No	0.049	46.922
Bike	1486.330	14.766	20.266	10	No	0.014	30.551
Ravi Pickup	2273.330	15	10.028	20	No	0.022	30.185

* Total travel cost is shown in Pakistani Rupees (PKR).

Figure 7. Vehicular-based isochrone line distribution for home-based trips.

Figure 7. Vehicular-based isochrone line distribution for home-based trips.

Only one residential area was found near the urban center within the travel time slot of 6–12 min. In the same way, just one residential neighborhood was situated in the travel time zone of 12–18 min. Four residential regions were placed in the travel time slot of 18–24 min, and the rest of the six were located in the 24–30 travel time slot. Thus, it can be stated that the accessibility standards of the residents were comparatively not satisfactory when they were accessing the city center. The data about trips to access recreation facilities, e.g., parks, can be seen in

Table 12. Estimation of travel cost, travel distance, and time for recreation-based trips.

Travel Modes’	Travel Distance (m)	Travel Time (min)	Fuel Cost (PKR)	Parking Cost (PKR)	Tolls (If Any)	Indirect Cost	Total Cost *
Car	350	7	1.874	20	No	0.035	21.934

* Total travel cost is shown in Pakistani Rupees (PKR).

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Just one travel mode was observed, i.e., car, accessing recreational facilities, as highlighted in Table 12. The average travel cost was computed as PKR 21.934, whereas the distance and time were measured as 350 m and 7 min. It should be noted that for recreation trips, only parks were available in the study area. Henceforth, the recreation-based trips were plotted efficiently and can be seen in Figure 8.

Figure 8. Vehicular-based isochrone line distribution for recreation-based trips.

Figure 8. Vehicular-based isochrone line distribution for recreation-based trips.

By observing Figure 8, one can easily see that only three parks were available in the 6–12 min zone. Four of them were accessible within 12–18 min of travel time. Only one of the parks was within an 18–24 min isochronal boundary. One can also observe a park found outside the study area. So, the situation was not that bad as far as recreation-based accessibility standards are concerned in the study area. The statistics about religious-based trips can be seen in

Table 13. Estimation of travel cost, travel distance, and time for religious trips.

Travel Modes’	Travel Distance (m)	Travel Time (min)	Fuel Cost (PKR)	Parking Cost (PKR)	Tolls (If Any)	Indirect Cost	Total Cost *
Car	200	10	1.071	20	No	0.002	21.082
Bike	220	10	2.999	10	No	0.022	13.061

* Total travel cost is shown in Pakistani Rupees (PKR).

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Table 13 exhibits that the average cost for the car travel mode for religious trips was PKR 21.087. The average travel cost by bike was PKR13.061, and thus, the total average cost was computed as PKR 17.074. The average travel distance and time of a single trip by car were measured as 200 m and 10 min, respectively. Using the bike mode, 220 m was accessed within the same time as the mode car. From this information, it is illuminated that religious activities were found nearer to the city center at a walkable distance. However, there was a massive difference in average travel time for religious trips because of the huge traffic volume and concentration, etc.

As shown in Figure 9, active accessibility was measured using isochronal boundaries based on travel time and distance. There are several religious facilities in the middle of the highly accessible zones, i.e., 0–6 and 6–12 min. This situation highlights that urban planning codes were not followed for religious facilities. As a result, massive trips were generated specifically on Friday prayers that congested the center of the city.

Figure 9. Vehicular-based isochrone line distribution religious-based trips.

Figure 9. Vehicular-based isochrone line distribution religious-based trips.

5. Discussion

In the choice of travel modes (a modal split), travel distance plays an important role. Presently, the expansion of cities in an irregular pattern is becoming one of the causes of more trip generation, which puts immense pressure on urban traffic. Thus, the study objectives were set to measure and delineate household trips according to certain trip purposes. Concurrently, the trips to shopping, business, health, entertainment, home, recreation, religious, etc., were mapped with the help of a GIS-based isochrone model.

The results showed that city centers have been increasingly congested over time because of informalities in land use and transportation regulations. As a result, the highest percentage of trips was generated by the bike and car modes, which put enormous pressure on traffic volume in city centers. The average speed was reduced, leading to an autonomous increase in trip time, travel expenses, and journey distance. This situation severely damaged the accessibility standards of the commuters as specified by executing the isochrone boundaries of the study area.

Based on the study findings, it would not be wrong to state that the study area was found to be congested and resembled most cities in developing countries. Therefore, to remove traffic congestion in the city center of Sukkur, there is a dire need to develop and execute urban master planning guidelines focusing on the shift of heavy traffic-generating activities outside the main city hub. It is further explained that Sukkur city should opt for a land use planning approach that could reduce the agglomeration of essential activities. In this way, the traffic pressure from the center may be lessened, which may further propel the walking or cycling environment for better connectivity.

This research recommends strategies focusing on the reduction in car or bike dependency. To enhance the right of way, it is recommended that restrictions be imposed on on-street parking during the peak hours of the day. This decision may improve the traffic flow and diminish traffic delays. The traffic management plan should be devised by the concerned departments to ensure the free flow of traffic. The residents should also be advised to refrain from going into the city center during peak hours to prevent traffic congestion and travel delays.

6. Research Contribution

Travel accessibility refers to ease and comfort while reaching desired destinations. In this context, this study attempts to measure the accessibility standards of urban commuters living in the fifth-largest populated country in the world. Sukkur city is one the busiest commercial hubs in Sindh province, where people were found struggling to access desired destinations. Hence, this research can be considered as the first of its type focusing on the accessibility problems of urban commuters.

The provision of sustainable transportation services is the basic right of citizens, especially women, children, and the elderly, as represented in SDG-11.2. By the year 2030, everyone should have access to safe, inexpensive, and environmentally friendly modes of transportation. From this perspective, the outcome of the study contributed to SDG-11.2, as shown in Figure 10.

Figure 10. Relationship between research output and SDG-11.2.

Figure 10. Relationship between research output and SDG-11.2.

As depicted in Figure 10, multiple trip purposes of local commuters were studied while accessing daily activities considering the features of travel time. The GIS-based isochrone model and trip rate analysis were performed for the first time in the Pakistani context to study the travel accessibility patterns of urban commuters living in Sukkur. Most of the studies can be found easily in the literature, where the world’s researchers have executed the isochrone method to measure accessibility. Furthermore, this study’s concept is not often found in the literature, where isochrone models were implemented in congested city centers or central business districts (CBDs). However, this study contributed to the existing knowledge with the following perspectives:

• The isochrone model is rarely quantified in underdeveloped or developing countries such as Pakistan.
• An isochrone-based accessibility measure was tested in a congested city zone, where public transportation facilities were not available, nor were land use standards followed in the scope of urban planning.
• In this study, multiple trip purposes were noted together with certain travel modes. It was found that the isochrone model was not executed, confirming the trip purposes and travel mode data, as clarified in this study.
• GIS-based isochrone maps were generated focusing on time for trip purposes using certain travel modes. Such mapping contribution is novel in the Pakistani context. In the same way, few studies were found globally that focused on the accessibility issues of the local commuters.
• The existing research method of the study was modified to adopt the local commuting characteristics of citizens. This was designed to include trip data following the local conditions of the country, e.g., time, distance, cost, and travel modes.

It was found that local commuters faced the problems of travel delays, traffic jams, and the absence of public transportation facilities. Hence, this study was conducted to clarify the realities on the ground related to travel accessibility problems. Decision-makers may formulate policy implications based on the findings of this research to uplift commuting standards in the local context. From this perspective, the findings of this study may assist policymakers in formulating strategies for the provision of sustainable and accessible transportation services.

7. Conclusions

This study was conducted to measure accessibility considering the purposes of household trips, travel modes, travel time, travel distance, travel cost parameters, etc. This research showed that higher population and vehicular densities impact the three main factors of accessibility, such as travel time, travel cost, and travel distance. Hence, travel accessibility was measured in the context of perceived urban locations that were reachable within 1 km by executing the GIS-based isochrone modeling technique. The bike was found to be frequently used by commuters to reach certain destinations. The home-based trips were recorded as 22.76%, and trips generated to access work locations were noted as 20.69% using the bike travel mode. About 17.24% of the trips were generated using the bike mode to access shopping activities. Precisely 5.52% of the home-based trips were recorded using the car. Simultaneously, 2.76% and 1.38% of the trips were shown to be to access health and shopping activities, respectively. Concerning isochrone boundaries within 1 km based on trip distance and time to reach various activities, cars, and bikes were mostly chosen by the local commuters. None of the health facilities were situated in the isochronal boundary of 0–6 min. Only three parks were available in the time slot of 6–12 min, whereas most of the commercial banks were accessible within 0–6 min. The majority of the residential neighborhoods were situated far from the city center. Many essential activities were agglomerated within the city center of Sukkur. The generated trips put enormous pressure on traffic volume, resulting in congestion and delays. Therefore, this study recommends the execution of integrated sustainable approaches to land use and transportation planning to eliminate travel accessibility issues. In light of the available literature, the methodology of this study may be considered novel. The isochrone-based practice has never been experimented with to measure accessibility in Pakistan. The study findings can contribute to a better travel situation in not only Sukkur but also the rest of the congested urban centers in the developed and developing world. This research can help in the development process of congested free urban centers that promote walking and excellent public transportation networks. The findings of the study may contribute to SDG-11.2 for the better provision of affordable transportation facilities.