Impact of the Accessibility Generated by the Mexicali–San Felipe Highway on Reduction in Marginalization Levels in the Urban Periphery and Sub-Urban Areas

Abstract

The objective of this research is to determine whether levels of road accessibility in urban, peri-urban, and sub-urban localities within the municipalities of Mexicali and San Felipe, in Baja California, Mexico, can be associated with processes of territorial expansion, population growth, and changes in urban marginalization levels. This is assessed through a methodology that combines ex-ante and ex-post analysis, the use of the Urban Marginalization Index (UMI) at the AGEB scale, and a hierarchical accessibility classification (Levels A, B, and C), thereby contributing a replicable tool for analyzing socio-spatial impacts derived from road infrastructure. To this end, modernization, maintenance, and reconstruction works, as well as the construction of an interchange carried out between 2006 and 2017 along Federal Highway No. 5—specifically the Mexicali–San Felipe section—were examined in relation to the accessibility they provide to ten nearby localities. UMI values were estimated for 134 AGEB using data from 2000, 2010, and 2020, which enabled the assessment of changes in quality of life before, during, and after the execution of these works. The results show significant population growth in six localities, accompanied by territorial expansion processes. Localities with direct connection to the study corridor tended to exhibit middle to low marginalization levels, while those with indirect accessibility or direct access through another federal highway section tended toward middle to high levels, with some shifting to middle to low. It is concluded that road accessibility constitutes a relevant factor in the progressive improvement in socioeconomic conditions and quality of life in urban, peri-urban, and sub-urban areas.

1. Introduction

Road accessibility is a strategic factor that should be considered as a public policy instrument for the territorial, economic, and social development of localities in any state, region, or country, given that goods and people are transported through these networks [1,2,3,4,5]. Moreover, road infrastructure promotes, in its immediate surroundings, the construction of facilities related to education, healthcare, and basic household services, among other uses [6,7], all of which are fundamental elements for the development of populations and of sparsely urbanized or isolated territories [8].

In addition to contributing to a country’s improved competitiveness—derived from increased productivity and the optimization of the movement of goods and passengers—road infrastructure generates positive effects on well-being by helping to reduce social inequality and poverty [9,10]. At present, it is the primary means of transporting goods and connecting people across regions in Mexico, mobilizing 96.0% of annual passengers and carrying 55.0% of freight nationwide [11].

In Mexico, road infrastructure is primarily categorized into three types, each distinguished by specific geometric characteristics and physical conditions: federal corridors, feeder or secondary roads, and rural roads [12]. On the one hand, the federal network serves to connect the country’s major population, production, and consumption centers through extensive corridors that generally consist of four or more lanes and often traverse multiple states [13]. On the other hand, the feeder or secondary network integrates sub-urban localities with urban centers and productive hubs by means of road links that typically comprise two lanes and connect directly to the federal network [13]. In turn, the rural network provides access to small, hard-to-reach rural localities via roads with basic design features that may be either paved or unpaved [13].

Thus, accessibility to a federal highway corridor can serve as a significant factor enabling a wide spectrum of productive activities for residents of localities situated along the corridor’s alignment [14]. This effect is even more pronounced for those located in sub-urban areas or at a considerable distance from the municipal seat, given their need to consolidate and expand urban development [15]. Consequently, the territorial impact of federal road infrastructure depends on several factors, among which the layout, distances, and intersections with other axes are particularly significant [1,16,17]. Additionally, secondary road sections and rural roads, together with federal highway corridors, form an integrated network that enhances territorial accessibility and thereby supports the population’s basic needs [18], underscoring that secondary and rural roads are just as important as the federal highway network [19,20].

In light of the above, it is essential to make full use of the resources invested in road infrastructure, particularly in countries where opportunity costs directly affect the social development of regions with high marginalization levels, as is the case in Mexico [21]. It is therefore crucial to invest not only in the construction of new infrastructure but also in the maintenance and modernization of existing systems, given that the social and economic development of each region—as well as long-term sustainability—depends on the performance and reliability of these networks [7,22,23,24].

For this reason, the objective of the present study is to determine whether levels of road accessibility in localities characterized by different urban conditions (urban, peri-urban, or sub-urban) within the municipalities of Mexicali and San Felipe, Baja California, Mexico, can be associated with territorial and population growth, as well as with changes in urban marginalization levels, through improvements in housing conditions and access to basic services such as education and healthcare. It is also important to clarify that the analysis considers only the road accessibility generated by the federal and feeder (secondary) networks in peri-urban and sub-urban areas. This decision follows from the choice to use the Basic Geostatistical Area (AGEB, the acronym in Spanish) as the unit of territorial delimitation, given that AGEB can be located in urban and sub-urban zones. Rural areas and the rural roads are therefore excluded from the analysis.

However, in order to measure the impact generated by road infrastructure and the accessibility that it provides to a territory, it is necessary to evaluate the level of marginalization experienced by the population, which in turn reflects overall quality of life [1]. For this reason, the study also develops an Urban Marginalization Index (UMI) for urban, sub-urban, and peri-urban localities in the southern periphery of the municipal seat of Mexicali, Baja California, Mexico. These localities are connected, either directly or indirectly, to Federal Highway No. 5 along the Mexicali–San Felipe section. The index is constructed using the following indicators: educational conditions—(1) population aged 15 years or older with no schooling or incomplete primary education; access to healthcare—(2) population without access to health services; and housing conditions—(3) occupied housing units with earthen floors, (4) occupied housing units without electricity, (5) occupied housing units without piped water, and (6) occupied housing units without drainage.

In 1995, the National Population Council (CONAPO, the acronym in Spanish) carried out the first calculation of the Urban Marginalization Index (UMI) in Mexico, applying the indicator to each federal entity and municipality [25]. It should be noted that this indicator has been evaluated in the country every five years since it was first calculated, using the AGEB as the minimum territorial delimitation, as well as the population and housing data published by the National Institute of Statistics and Geography (INEGI, the acronym in Spanish) during the five-year period, through quick counts, and in the zero-year period, through censuses [26]. This approach provides estimates that make it possible to understand marginalization patterns within urban and sub-urban localities, and it has become one of the principal analytical and operational tools for designing social policies and strategies aimed at addressing the population’s socioeconomic disadvantages [1,25,26,27].

However, this research used the methodology developed by CONAPO to create its own estimate of the UMI, considering specific socioeconomic variables from 10 localities, and taking into account the population and housing censuses of 2000, 2010, and 2020. Furthermore, there is evidence that this methodology has been used in other studies to develop their own indicator in specific geographical areas with territorial inequalities [1,28,29,30,31,32].

2. Background and Area of Study

This section presents the characteristics that define the study corridor, organized into its main subsections, to determine the impact on the territory and the population in the case study. The Mexicali–San Felipe corridor covers a distance of 190 km, beginning in the city of Mexicali—the principal urban center and the municipal seat of Mexicali—and extending to the locality and municipality of San Felipe, heading south within the state of Baja California (Figure 1).

It is important to note that the corridor provides access to the regional road network for several localities, most of which are located in the agricultural zone of the Mexicali Valley, in the southeastern portion of the municipality of Mexicali. Within this area, six localities are classified as sub-urban and face shortages of basic infrastructure and services, including potable water supply and sanitation systems [25,26]. For the purposes of the present study, ten localities were selected based on their proximity to the highway corridor, as well as their population size and territorial extent. Nine of these localities are situated within the municipality of Mexicali, and one is located within the municipality of San Felipe.

The municipality of Mexicali serves as the capital of the state of Baja California and covers slightly more than 10,000 km². It is located in the northeastern part of the state and borders the city of Calexico, situated in Imperial Valley County, California, United States [34]. The municipality of San Felipe, in turn, spans nearly 11,000 km² and is located in the eastern portion of the state, sharing a large stretch of coastline with the Gulf of California [35].

Over time, the Mexicali–San Felipe corridor has undergone multiple modernization, maintenance, and reconstruction efforts, as well as the construction of an interchange. For the period considered in this study, the analysis begins with the modernization works carried out from early 2006 through 2011, aimed at improving connectivity among cities, ports, the border region, and tourist destinations, with plans to integrate secondary or feeder roads into the corridor [15,36]. Maintenance activities completed in 2013 between km 106 and km 111 were also reviewed [37]. In addition, construction of the El Faro Interchange began in 2014 at km 38 and was completed in 2015, with the objective of enhancing safe access to the Mexicali Valley [37]. Furthermore, in 2017, reconstruction works were conducted starting at km 181, along a 10 km section that leads to a feeder road [37].

The planning and execution of these maintenance and modernization works were carried out by the state and federal governments with the objective of strengthening the corridor running from north to south [37]. This corridor begins in the city of Mexicali and follows the coastline of the Gulf of California, crossing the municipality of San Felipe and its principal locality of the same name, before connecting with other routes such as Federal Highway No. 3, which provides access to the Pacific Ocean and, further south, to additional localities within the municipality.

This study demonstrates that the modernization of the Mexicali–San Felipe corridor contributes to improved economic and social conditions in six of the ten localities with the largest populations and territorial extent. To assess these effects, ex-ante UMI estimates (for the year 2000) and ex-post estimates (for 2010 and 2020) were generated, following the methodological framework that guides investment decisions within Mexico’s Ministry of Infrastructure, Communications and Transportation (SICT, the acronym in Spanish), in accordance with the guidelines established in the Federal Expenditure Budget.

2.1. Road Sections and Geometric Characteristics

To better analyze the territorial impact of the Mexicali–San Felipe corridor, it was divided into three sections (Figure 2).

The first section extends from km 0 to km 38, beginning in the municipal seat of Mexicali and ending at the El Faro Interchange. This section provides direct or indirect access to nine of the ten selected localities. Throughout the 38 km, the corridor comprises two asphalt-paved roadways—one for southbound travel and one for northbound travel—separated by a central median ranging from 3 m to 6 m in width (Figure 3). Each direction includes two 3.5 m lanes and a 3 m outer shoulder.

The second section begins south of the El Faro Interchange and covers approximately 122 km, from km 38 to km 160, reaching the area known as El Chinero. At the start of the interchange, the corridor consists of two separate asphalt-paved roadways, one in each direction, separated by a central concrete barrier (Figure 4).

Each direction includes two 3.5 m lanes and a 2.5 m outer shoulder. However, beyond the interchange and up to km 160, the corridor becomes a two-lane undivided section, with one 3.5 m lane in each direction and 2.5 m outer shoulders (Figure 5).

It is important to note that before reaching km 141, the El Chinero Interchange appears, where Federal Highway No. 5 (Mexicali–San Felipe) intersects with Federal Highway No. 3 (Figure 6).

Regarding the third section, which extends from the area known as El Chinero to the city of San Felipe, from km 160 to km 190, the corridor consists of two asphalt-pavement roadways—one for outbound traffic and one for inbound traffic—separated by a central median strip measuring 3 m in width (Figure 7). Each one has two lanes of 3.5 m each and an external shoulder measuring 3 m.

2.2. Economic and Demographic Impacts Along the Study Corridor

The combined population of the ten localities increased from 611,823 inhabitants in 2000 to 774,957 in 2010 and 813,092 in 2020 [33,39,40] (

Table 1. Main localities affected by the Mexicali–San Felipe highway.

Localities	Population
	2000	2010	2020
Mexicali	549,873	689,775	717,047
Guadalupe Victoria	15,561	17,119	19,081
San Felipe	13,123	16,702	17,143
Ejido Puebla	7421	15,168	21,269
Progreso	4462	12,557	13,106
Carranza	3552	6098	6205
Ciudad Coahuila	6479	5617	6503
Delta	4860	5180	5615
Nuevo León	3255	3655	3776
Michoacán de Ocampo	3237	3086	3347
Total	611,823	774,957	813,092

Source: author’s own elaboration using INEGI data [33,39,40].

), representing a 32.0% growth from 2000 to 2020. Despite this overall trend, population growth in some localities has stabilized or increased only slightly (Ciudad Coahuila, Delta, Michoacán de Ocampo, and Nuevo León), whereas others experienced more pronounced growth (Mexicali, Guadalupe Victoria, San Felipe, Ejido Puebla, Progreso, and Carranza). It is worth noting that this region, structured around the study corridor, supports tourism, agriculture, fishing, mining, commercial activities, service provision, and industrial operations from Mexicali to San Felipe. Several industries are established throughout the corridor, along with direct connectivity to a network of roads under various administrative levels and to railway infrastructure, creating an economic development hub for the region [41].

In the first section (km 0–38), access points connect the corridor to the Mexicali Valley, providing connectivity to sub-urban areas and fostering the development of economic activities associated with agriculture, commerce, services, and industry. Secondary activities such as manufacturing and construction, as well as tertiary activities including service provision, commerce, transportation, education, and health, are primarily concentrated in the municipal seat of Mexicali [42]. In contrast, primary activities such as agriculture are concentrated in the Mexicali Valley area [43]. Nevertheless, the economic growth driven by agricultural activity during the 1950s and 1970s has undergone significant transformation, giving way to industrialization and the expansion of the service sector, a trend that continues to the present day [44,45].

In the second section (km 38–160), which begins at the El Faro junction and extends to El Chinero, mining activities represent a major source of employment and form part of the primary sector in this area [15].

In the third section (km 160–190), extending from El Chinero to the main settlement of the municipality of San Felipe, bearing the same name, primary activities such as fishing stand out, along with tertiary activities such as tourism and commerce [46,47].

The Mexicali–San Felipe corridor is one of the key axes in the state that can enhance tourism-oriented development toward the southern and regional areas of the territory. Consequently, it has been subject to ongoing modernization and construction aimed at improving accessibility and user safety.

To provide a concise overview of the economic structure of the study corridor,

Table 2. Economic units by activity sector in localities impacted by the Mexicali–San Felipe corridor.

Activity Sector (EU)	Total Units	Share of Total (%)
(1) Agriculture, animal husbandry, forestry, fishing, and hunting	50	0.1
(2) Mining	4	0.0
(3) Manufacturing industries	2406	7.1
(4) Wholesale trade	1198	3.5
(5) Retail trade	11,197	33.2
(6) Professional, scientific, and technical services	934	2.8
(7) Temporary accommodation services and food and beverage preparation	4004	11.9
(8) Real estate services and rental/leasing of tangible and intangible goods	1560	4.6
(9) Other services	12,419	36.8
Total	33,772	100.0

Note: EU = economic units. Sector definitions follow INEGI. Detailed locality-level counts are provided in the Supplementary Materials (Table S1). Source: author’s own elaboration using INEGI data [48].

summarizes the number of economic units by activity sector across the ten localities. As shown, tertiary activities dominate the corridor economy, particularly other services and retail trade, followed by temporary accommodation and food services, while manufacturing represents a relevant share of economic units [48]. Detailed locality-level counts are reported in the Supplementary Materials (Table S1).

3. Literature Review

The term urban marginalization is associated with the concentration of deprivations within specific geographic spaces, such as localities or municipalities, rather than with the individual conditions of the people residing in those spaces, but instead with collective conditions [28,29,30,31]. In other words, a territory may exhibit high levels of urban marginalization even when certain residents have access to basic services such as piped water, electricity, or finished flooring. This perspective frames marginalization as an indicator of territorial inequalities and has generated strong interest in examining the level and variation in marginalization across different geographic scales [26].

Regarding Mexico, the UMI is used as an indicator to identify deprivations in goods and services, as well as levels of well-being experienced by the population across different territorial contexts. Since that time, the UMI has become a key tool for the formulation of public policies and programs aimed at anticipating or mitigating the impacts of urban expansion, while supporting timely planning of essential public services such as infrastructure, road paving, electricity supply, water provision, hospitals, and schools—elements required to ensure adequate housing and to improve population quality of life [1,32].

Internationally, deprivation and marginalization indices are constructed using similar multidimensional approaches focused on structural vulnerabilities. In the United Kingdom, the Townsend and Carstairs indices incorporate unemployment, overcrowding, car ownership, and housing tenure, while the Index of Multiple Deprivation (IMD) combines seven domains: income, employment, health, education, barriers to housing/services, crime, and living environment [49]. European indices, such as those used in France, emphasize education, health access, and housing quality [50]. In Latin America, multidimensional poverty indices highlight school attendance, healthcare, and basic housing infrastructure [51]. These align closely with the UMI’s core dimensions—education, health, and housing—ensuring methodological comparability across contexts.

On the other hand, assessing the relevance of investment projects in road infrastructure requires the consideration of socioeconomic, environmental, and technical studies, using a methodology that allows evaluation of project significance across multiple scales, ranging from the local to the international level [52,53,54,55,56]. This approach is necessary for public administrations or organizations responsible for promoting actions related to road construction and maintenance, which currently rely on a range of methods to support decision-making and to evaluate risks and adaptation measures. Commonly used approaches include cost–benefit analysis (CBA), cost-effectiveness analysis (CEA), and multi-criteria analysis (MCA), which are among the most frequently applied methods [54]. Nevertheless, public administrations typically employ cost–benefit analysis as the primary tool for the socioeconomic evaluation of investments in road infrastructure [57,58,59]. However, there are other alternatives to analysis such as impact assessment, which focuses on measuring the real changes generated by a project, program or policy, and determining whether those changes are actually due to the intervention or to other factors [1,60].

Both developed and developing countries adopt good governance practices in transport infrastructure planning, grounded in impact assessments conducted both ex-ante and ex-post [61,62,63]. Although ex-ante evaluations are more common for this type of infrastructure, ex-post assessments often prove to be highly valuable [63,64,65]. The main difference between these approaches lies in the timing of benefit consideration: under an ex-ante approach, benefits are projected, whereas under an ex-post approach, benefits have already materialized, even when project implementation remains ongoing [64,65,66,67].

These evaluations support improved decision-making by helping to identify potential risks, optimize resource use, and ensure that projects respond to actual mobility needs and economic development objectives. In addition, such assessments promote transparency, accountability, and citizen participation, thereby strengthening the legitimacy and effectiveness of public policies in the field of road transport [63,67]. Furthermore, investment project evaluation seeks to enhance operational efficiency and to estimate changes experienced by the beneficiary population, allowing assessment of the extent to which the objectives defined at the outset have been achieved [68,69]. In this context, evaluating the impacts associated with the construction of new road infrastructure, as well as other types of infrastructure, constitutes a fundamental component of public policy.

International evidence highlights the positive effects of road improvement initiatives on productivity. Konno [70] notes that, on a global scale, road infrastructure contributes to increased overall productivity by reducing transportation costs, expanding market access, and generating spatial externalities. In developing countries, productivity is estimated to increase between 0.05% and 0.15% for every 1% increase in road network extent. Laborda and Sotelsek [71] stipulate that, in Global South economies, higher road density and a greater proportion of paved roads are associated with significant increases in labor productivity and employment. These gains exhibit non-linear behavior, with more pronounced effects at middle-income levels. Furthermore, studies by the International Monetary Fund indicate that improvements in road infrastructure quality are correlated with higher average transport speeds, increases in business productivity, and higher GDP per capita in economies of the Global South [72]. In Latin America, the modernization of logistics corridors has contributed to reducing transport costs and territorial gaps [73].

Therefore, allocating resources to appropriate road infrastructure in developing countries is strictly necessary in order to build and maintain corridors that articulate the territory and ensure societal benefits [74]. This task involves substantial investment of financial and technological resources, as well as strong institutional and managerial capacity [75]. The importance of such investment lies in the promotion and strengthening of productive sectors such as industry, commerce, services, and agriculture, thereby fostering economic growth along the corridor [76].

Likewise, authors such as Kantianis et al. [77], Levkovich et al. [78], and Tegebu and Seid [79] discuss the influence of road infrastructure on territorial dynamics, particularly regarding effects on population distribution and economic activities. In turn, the accessibility enabled by road infrastructure, by affecting transport costs, becomes a key element of competitiveness, as it improves the movement of people and goods, including flows associated with infrastructure construction activities [80]. This effect is especially significant in peripheral or rural areas with limited infrastructure, where road development can function as a driver of development [81,82,83]. Consequently, in isolated regions, the construction of transport routes can reduce territorial inequalities by integrating such areas into production and consumption circuits [84]. In this way, road infrastructure not only facilitates economic growth but also contributes to improved quality of life and promotes more balanced territorial development [85,86], particularly through roads that provide access to peripheral areas [2].

Derived from the above, territorial development constitutes a valid argument for supporting the construction of road infrastructure [15,87], given that road networks form an integrated system that evolves in response to space–time dynamics, destination-related decisions, node selection, user accessibility, and adaptation to different travel speeds, among other factors, as infrastructure conditions change over time [88]. In this context, addressing population accessibility needs through the provision of appropriate infrastructure represents one of the most relevant functions and one of the highest responsibilities assumed by public administrations [89,90,91,92].

On the other hand, Ge et al. [93], Ng et al. [94], and Gómez [95] indicate that municipal seats or areas with higher levels of urbanization tend to exhibit higher accessibility levels than other zones. This condition is associated with factors such as geographic location, population density, service availability, and the presence of infrastructure. In contrast, regions with limited accessibility often experience more negative socioeconomic outcomes as a result of insufficient road networks or poor connectivity [93,96,97]. For this reason, the present study treats accessibility as a key component of territorial analysis, primarily linked to the location of urban and sub-urban areas, as well as to the characteristics of the existing road network.

4. Materials and Methods

This section presents the methodology used to evaluate the impact of road accessibility on changes in urban marginalization associated with the population of a given territory (Figure 8). To this end, the UMI must be assessed at different points in time, which requires statistical information on population and housing, as well as the adoption of a territorial scale as the unit of analysis linked to urban conditions. This approach involves examining critical aspects related to three dimensions: education, health, and housing. In addition, guidelines are established for determining road accessibility levels associated with each locality included in the analysis.

4.1. Definition of the Analysis Period

As a first step, the analysis periods must be defined, as these periods determine the territorial and population impacts of road infrastructure actions before, during, and after implementation. To achieve this, the study adopts an ex-ante and ex-post methodological approach [64,65,66,67].

Transport infrastructure evaluations commonly distinguish ex-ante and ex-post approaches. Ex-ante analyses often employ CBA to project economic profitability by monetizing costs and benefits [65,98]. However, other analytical alternatives exist, such as impact assessment, to measure changes before the project stage, prior to the execution of improvement works (ex-ante analysis) [1]. In contrast, ex-post evaluations assess realized socioeconomic impacts, such as changes in quality of life, without requiring benefit monetization. This study adopts an ex-post impact evaluation framework using the Urban Marginalization Index (UMI) at the AGEB level to quantify territorial and social changes associated with road accessibility improvements [66,98].

4.2. Identification of Territorial Conditions of Localities and Determination of Minimum Analysis Areas

Before proceeding with the evaluation of quality of life in the study localities, these areas must be subdivided into smaller territorial units in order to identify, in greater detail, variations in population and housing characteristics within each area. To this end, information produced by governmental and planning institutions can be employed. In the Mexican context, this role is fulfilled by the INEGI, which defines the Área Geoestadística Básica (AGEB) as the minimum territorial delimitation unit representing an urban or sub-urban area [26].

On the other hand, it is necessary to identify the urban condition of the localities included in the analysis, as this allows assessment of the impact that public policies have on territorial development. Such conditions may correspond to urban, sub-urban, or other contexts associated with an urban environment.

4.3. Determination of Road Accessibility Levels

In addition, it is necessary to identify the accessibility level of each locality by considering geographic location, road typology, and connectivity and distance with the federal network [1,16,17]. This type of accessibility analysis considers the degree of connection between two points located in the same territory, incorporating the distance factor. Connectivity with different routes and proximity to major urban centers are fundamental for a territory [93,94,95]. Accordingly, a hierarchical accessibility classification is proposed. Level A includes localities with direct connection to the federal highway corridor under study; Level B includes localities that access the road network through a federal highway other than the one analyzed; and Level C includes localities with indirect connection to the federal highway through the feeder or secondary road network.

4.4. Evaluation of Urban Marginalization

To assess quality of life in Mexico, the UMI is used as a proxy indicator [25,26]. The index is calculated using information provided by INEGI, with territorial disaggregation at the AGEB level.

In infrastructure investment projects aimed at evaluating the reduction in marginalization levels in impacted areas, the use of the UMI as a monitoring tool proves to be highly effective for verifying objective achievement. This index enables the classification and ranking of analysis units, facilitating territorial stratification based on criteria that reflect homogeneity or heterogeneity across territorial areas, using the principle of minimum variance [15,25,26]. For this purpose, AGEB are used as analysis units, encompassing urban, peri-urban, and sub-urban zones. These units represent one of the three main territorial divisions defined within the MGN (National Geostatistical Framework, the acronym in Spanish) of INEGI and have been employed in multiple studies related to population analysis [99,100,101,102,103].

The socioeconomic dimensions and indicators selected to calculate the UMI make it possible to assess progress in the population’s quality-of-life level in each AGEB through the analysis of access to fundamental services such as education, health, and housing (

Table 3. Breakdown of dimensions by indicators used to estimate the UMI.

Dimensions	No.	Indicators
Education	1	% of population without school and/or with incomplete low levels of education
Health	2	% of population without right to health services
Housing	3	% of occupied housing units with earthen floor
	4	% of occupied housing units without electricity
	5	% of occupied housing units without piped water
	6	% of occupied housing units without drainage

Source: author’s own elaboration using CONAPO data [25,26].

). It is worth mentioning that, since 1995, CONAPO has considered these three dimensions and six indicators as the structural and minimum elements that guide UMI development, which are supported by a theoretical–conceptual basis [25], seeking to capture the lack of accessibility to education (indicator 1), and the lack of access to health services (indicator 2) and housing conditions (indicators 3–6). However, since 2020, more indicators related to overcrowding and access to goods in housing have been added [26]. Therefore, the main argument for choosing these indicators is based on the dimensions that structure the marginalization indices presented in national and international studies, as well as the availability of information, comparability at the AGEB level in an ex-ante and ex-post analysis, and the relevance of monitoring the social impact through infrastructure projects.

To calculate this index, statistical data from population and housing censuses are used, based on three structural dimensions: educational status—(1) population aged 15 years and over with no schooling or incomplete primary education; access to healthcare—(2) population without entitlement to health services; and housing conditions—(3) occupied housing units with dirt floors, (4) occupied housing units without access to electricity, (5) occupied housing units without access to potable water, and (6) occupied housing units without drainage.

Following Figure 9, threshold values are defined to classify the level of urban marginalization. An AGEB is classified as Middle–High when the indicator value is between the mean and one standard deviation; High when it is between one and two standard deviations above the mean; and Very High when it exceeds two standard deviations. Conversely, an AGEB is classified as Middle–Low when the value is between the mean and one standard deviation below the mean; Low when it lies between one and two standard deviations below the mean; and Very Low when it exceeds two standard deviations below. This analysis was performed using SPSS (version 28.0), and the results obtained allow the categorization of the UMI to be established.

To determine the UMI for each selected AGEB, the calculation is based on the weighted sum of the selected indicators, in accordance with CONAPO guidelines [25,26]:

$$\mathit{UMI}= {{\displaystyle \mathit{\sum }}}_{j=1}^6 a_j Z_{\mathit{ij}}$$

(1)

where

UMI = Urban Marginalization Index by AGEB;

_j = the indicators that contribute to the level of marginalization (_j = 1 ... 6);

a_j = weight assigned to indicator _j (derived from the principal components matrix generated using SPSS);

Z_ij = standardized value of indicator _j (obtained by subtracting the mean and dividing the result by the corresponding standard deviation for each indicator).

After summing the values of the socioeconomic indicators corresponding to each AGEB, the level of marginalization is established using a normal distribution (Figure 9). Subsequently, the UMI is compared under ex-ante and ex-post conditions, and a Geographic Information System (GIS) is used to visualize the results.

Subsequently, the urban marginalization results for each locality can be associated with the levels of accessibility provided by the road network. This approach makes it possible to define the impact on the population from different territorial perspectives.

5. Results

This section presents the results of the UMI-based quality-of-life assessment for the AGEB within the study localities under ex-ante and ex-post conditions. It then examines how changes in urban marginalization relate to the local territorial setting and to road accessibility associated with the highway infrastructure.

5.1. Analysis Period

To conduct this study, baseline (ex-ante) conditions were assessed using population and housing census data from 2000 for the ten localities. Ex-post conditions were assessed using the 2010 and 2020 censuses to examine conditions during and after the implementation of modernization, conservation, interchange construction, and reconstruction works along the Mexicali–San Felipe highway section.

This assessment is based on modernization works carried out along the Mexicali–San Felipe highway section, as recorded in the SHCP’s fiscal calendar for 2006–2011 [15,36], and on information reported by SCT in the Balance de Obras and project portfolio records for 2013, 2014, 2015, and 2018 [37]. It should be noted that pavement conservation works were conducted in 2013; interchange construction activities took place between 2014 and 2015; and reconstruction works were implemented in 2017, consisting of pavement repair and rehabilitation of part of the substructure.

5.2. Population and Territorial Conditions by Locality and AGEB: Ex-Ante vs. Ex-Post

The study localities exhibit territorial conditions that may be urban, urban-peripheral, or sub-urban (

Table 4. Territorial condition of the study localities and number of AGEB in ex-ante and ex-post situation.

Localities	Territorial Conditions	2000		2010		2020
		Total AGEB	Population	Total AGEB	Population	Total AGEB	Population
Mexicali	Urban periphery	21	42,849	36	73,795	40	89,976
Delta	Sub-urban	4	4860	6	5180	7	5615
San Felipe	Urban	15	13,123	16	16,702	16	17,143
Michoacán de Ocampo	Sub-urban	1	3237	1	3086	1	3347
Ejido Puebla	Sub-urban	4	7421	8	15,168	17	21,269
Progreso	Sub-urban	7	4462	16	12,557	16	13,106
Ciudad Coahuila	Sub-urban	6	6479	6	5617	6	6503
Nuevo León	Sub-urban	2	3255	4	3655	4	3776
Carranza	Sub-urban	5	3552	5	6098	6	6205
Guadalupe Victoria	Sub-urban	10	15,561	13	17,119	16	19,081
Total		75	104,799	111	158,977	129	186,021

Source: author’s own elaboration using INEGI data [33,39,40].

), where the population may be distributed across one or more AGEB that comprise each locality (Figure 10).

It can be observed that eight of the ten localities present a sub-urban territorial condition, with a population within the area of analysis representing 46.6% in 2000, 43.1% in 2010, and 42.4% in 2020. The remaining share of the population resides in urban areas; however, a large proportion is concentrated in the urban periphery south of the locality of Mexicali, accounting for 40.9% in 2000, 46.4% in 2010, and 48.4% in 2020. These figures indicate a population trend toward residence in urban areas.

With regard to the total number of AGEB across the ten localities, an increase of 72.0% is observed from 2000 to 2020, rising from 75 to 129, respectively. However, the urban or sub-urban growth derived from the emergence of new AGEB has not been uniform among the localities. A more accelerated process is identified in four localities—Mexicali, Ejido Puebla, Progreso, and Guadalupe Victoria—while a less accelerated process is observed in Delta, San Felipe, Nuevo León, and Carranza. In contrast, Michoacán de Ocampo and Ciudad Coahuila maintain the same number of AGEB throughout the period. These results indicate that localities with larger populations and higher population growth are generally those that have experienced a greater increase in the number of AGEB between 2000 and 2020. In most cases, such localities are also located closer to the municipal seat, with the exceptions of Guadalupe Victoria and San Felipe, although the latter functions as the municipal seat of the municipality with the same name.

In the case of the locality of Mexicali, this area corresponds to an urban zone that contains 429 AGEB [33]. However, 40 of these AGEB are considered to be directly impacted by the Mexicali–San Felipe highway section, as these are located in the southern urban periphery of the locality and together concentrated a total population of 89,976 inhabitants in 2020. It is worth noting that, from 2000 to 2020, the number of AGEB in this peripheral area almost doubled, increasing from 21 to 40. In addition, these AGEB are contiguous with the AGEB of Ejido Puebla, resulting in a total of 57 AGEB within this zone.

With respect to the total number of sub-urban AGEB concentrated in eight localities, an increase of 87.2% is observed, rising from 39 to 73 between 2000 and 2020. However, the cases of Ejido Puebla and Progreso stand out, as these localities increased the number of AGEB by 325.0% and 128.6%, respectively.

5.3. Analysis of Road Accessibility Levels by Locality

According to the geographic location of the ten localities, and after analyzing the road typology that connects them with the rest of the road network, two localities—Mexicali and San Felipe—were identified as presenting accessibility level A, since direct connectivity exists with the Mexicali–San Felipe federal highway segment (

Table 5. Road accessibility levels of localities.

Localities	Level of Accessibility	Dist. FHN	Accessibility Description
Mexicali	A	-	Locality directly connected to the federal highway corridor of the case study
Delta	C	24.20	Locality indirectly connected to the federal road network through a secondary or feeder road
San Felipe	A	-	Locality directly connected to the federal highway corridor of the case study
Michoacán de Ocampo	C	10.15	Locality indirectly connected to the federal road network through a secondary or feeder road
Ejido Puebla	B	-	Locality that accesses the road network through another federal highway
Progreso	B	-	Locality that accesses the road network through another federal highway
Ciudad Coahuila	C	33.50	Locality indirectly connected to the federal road network through a secondary or feeder road
Nuevo León	C	16.25	Locality indirectly connected to the federal road network through a secondary or feeder road
Carranza	C	16.00	Locality indirectly connected to the federal road network through a secondary or feeder road
Guadalupe Victoria	C	31.45	Locality indirectly connected to the federal road network through a secondary or feeder road

Note: Dist. FHN = Distance to the federal highway network (km). Source: author’s own elaboration.

). Two additional localities—Progreso and Ejido Puebla—exhibit accessibility level B, as access to the road network occurs through another federal highway section, specifically Federal Highway No. 2, which provides connectivity to other localities in Baja California and to the state of Sonora (Figure 1). In contrast, six localities located in the Valle de Mexicali present accessibility level C, namely Delta, Michoacán de Ocampo, Nuevo León, Ciudad Coahuila, Guadalupe Victoria, and Carranza, since connectivity to the federal road network occurs indirectly through secondary or feeder roads. It is important to note that multiple feeder or secondary roads connect with these localities (Figure 1), facilitating connectivity to municipal seats and, in turn, to the main sources of economic activities and service availability, generating greater benefits for the population and contributing to improvements in quality of life. However, it was identified that the localities of Delta, Guadalupe Victoria and Ciudad Coahuila are the ones that have the greatest distance from the route to a section of the federal highway, respectively.

5.4. UMI Analysis by AGEB in Ex-Ante and Ex-Post Conditions

Considering the ex-ante and ex-post evaluation approaches, UMI values were calculated for 134 AGEB belonging to the ten localities (Supplementary Materials, Table S2), taking into account three points in time: the year 2000 as the stage prior to road infrastructure works; 2010 as the period during road works execution; and 2020 as the phase following road works completion.

It should be noted that some AGEB appear only in the year 2000 and were no longer reported in 2010. Specifically, four AGEB fall into this situation: 3954 and 4064 in the locality of Mexicali, 5077 in Delta, and 3102 in Guadalupe Victoria. This occurs because these AGEB were reassigned new codes in subsequent years or were merged into other AGEB. Conversely, 40 AGEB emerged in 2010 and remains present to date, 18 AGEB emerged in 2020, and 72 AGEB have been consistently reported since the year 2000.

Figure 11 summarizes the overall distribution of UMI levels across all AGEB for the three census years, highlighting a progressive shift away from critical categories (High/Very High) towards less severe levels.

In 2000, the UMI distribution indicates that 29.3% of the AGEB (22 out of 75) were classified in the High and Very High levels, 45.3% (34 out of 75) in Middle–High, and 25.3% (19 out of 75) in the combined Middle–Low and Low levels (Figure 11). By 2010, the share of AGEB classified at critical levels (High and Very High) decreased to 11.7% (13 out of 111), while Middle–Low and Low together represented 42.3% (47 out of 111) (Figure 11). In 2020, High and Very High together accounted for 4.7% (6 out of 129), whereas Middle–Low reached 56.6% (73 out of 129), and the Low category was no longer observed (Figure 11). Overall, Middle–High and Middle–Low together accounted for 95.3% (123 out of 129), suggesting a more balanced territorial condition in terms of access to basic housing services, health services, and education.

At that time, modernization works on the road corridor had not yet begun; therefore, the corridor allowed a maximum speed of 80 km/h along much of the alignment, with a surface in fair physical condition and cross-section widths limited to a single lane per direction along the 190 km corridor length. These conditions implied a high risk of traffic accidents due to the circulation of private vehicles, motor homes, buses, and freight transport.

Between 2002 and 2007, the Annual Average Daily Traffic (AADT) along this corridor increased from 2910 to 7357 vehicles per day. In addition, an accident analysis conducted in 2006 estimated material losses of approximately 3.8 million pesos, identifying excessive speed, encroachment into the opposing lane, and improper overtaking as the main causes [104].

By 2010, as interventions along the Mexicali–San Felipe corridor progressed, safety and accessibility conditions improved, allowing a higher level of service. This was achieved through the redesign of the pavement surface and roadway geometry to support maximum operating speeds between 105 and 110 km/h, along with wider cross-sections [36]. It should be mentioned that these speeds remain the maximum allowed to this day.

Consistent with these changes, the share of AGEB classified at critical levels (High and Very High) decreased in 2010 compared to 2000, from 29.3% (22 of 75) to 11.7% (13 of 111). At the same time, the distribution became more concentrated in the Middle–High level, which accounted for 45.9% (51 of 111), which is slightly higher than the 45.3% observed in 2000 (34 of 75). AGEB classified as Middle–Low and Low together represented 42.3% (47 of 111), exceeding the 25.3% observed in 2000 (19 of 75). Overall, these results suggest a reduction in territorial marginalization in 2010, which is consistent with improved quality-of-life conditions for the population. It should be noted that modernization works were completed in 2011, confirming improvements in connectivity among localities, ports, the border, and tourist destinations, while anticipating the complementary role of secondary or feeder roads [36]. The above substantially increased the AADT to a total of 9117 vehicles per day in 2011 [105].

In 2020, the distribution of UMI levels across the AGEB shows a marked improvement. A clear reduction is observed in the High and Very High categories, which together accounted for 4.7% (six of 129), compared with 29.3% (22 of 75) in 2000, representing a decrease of 24.6 percentage points. A decline is also observed in the Middle–High category, which accounted for 38.8% (50 of 129), compared with 45.9% (51 of 111) in 2010, reflecting a reduction of 7.1 percentage points. Conversely, in 2020 there is a clear shift toward the Middle–Low level, which reaches 56.6% (73 of 129), representing an increase of 32.6 percentage points relative to 2000. However, the Low category is no longer observed in 2020, indicating a concentration in the Middle–High and Middle–Low levels, which together account for 95.3% (123 of 129) of the total AGEB. Overall, this distribution suggests a more balanced territorial condition in terms of access to basic housing services, health services, and education.

These changes are consistent with the program of interventions implemented along the corridor, including pavement conservation works in 2013 and reconstruction works in 2017 [37], as well as the construction of the El Faro Interchange in 2015. Together, these actions likely contributed to improving comfort and safety conditions, along with accessibility through feeder or secondary roads [37]. These works made it possible to reach AADT of up to 10,293 vehicles per day on the road section during the year 2016 [41] and up to 11,427 vehicles per day in the year 2017 [106].

Focusing on individual localities, the following analysis summarizes how UMI levels evolved between 2000, 2010 and 2020 in each of the ten localities. To improve readability and avoid excessive small-area detail,

Table 6. Key UMI indicators by locality and year (2000/2010/2020).

Locality	Access Level	AGEB (n), 2000/2010/2020	Critical (%)	Lower Marginalization (%)	Dominant UMI Level, 2020
Mexicali	A	21/36/40	14.3/2.8/0.0	47.6/63.9/72.5	Middle–Low
San Felipe	A	15/16/16	46.7/12.5/0.0	26.7/43.8/75.0	Middle–Low
Ejido Puebla	B	4/8/17	0.0/25.0/5.9	25.0/37.5/70.6	Middle–Low
Progreso	B	7/16/16	57.1/18.8/18.8	0.0/31.2/37.5	Middle–High
Delta	C	4/6/7	0.0/0.0/0.0	0.0/50.0/71.4	Middle–Low
Michoacán de Ocampo	C	1/1/1	0.0/0.0/0.0	0.0/0.0/100.0	Middle–Low
Nuevo León	C	2/4/4	0.0/0.0/0.0	50.0/25.0/50.0	Middle–Low
Ciudad Coahuila	C	6/6/6	50.0/66.7/16.7	16.7/0.0/16.7	Middle–High
Guadalupe Victoria	C	10/13/16	40.0/7.7/6.2	20.0/23.1/31.2	Middle–High
Carranza	C	5/5/6	20.0/0.0/0.0	0.0/40.0/0.0	Middle–High

Note: Critical = High + Very High. Lower marginalization = Low + Middle–Low. n is the number of AGEB per locality and year. Road accessibility levels (A–C) follow the classification reported in Table 5. Source: author’s own elaboration using INEGI data [33,39,40].

reports aggregate indicators by locality, whereas the full AGEB level results are available in the Supplementary Materials (Tables S3–S6).

Table 6 summarizes locality-level differences in the evolution of UMI categories between 2000 and 2020, highlighting heterogeneous trajectories across the corridor. Overall, the results indicate that the two main localities directly served by the Mexicali–San Felipe corridor (Mexicali and San Felipe) are predominantly characterized by Middle–Low marginalization in 2020. A similar pattern is observed in Delta, Michoacán de Ocampo, Nuevo León, and Ejido Puebla, despite differences in their connectivity to the federal highway network (via feeder/secondary roads or through a different federal highway). By contrast, Progreso, Ciudad Coahuila, Guadalupe Victoria, and Carranza remain predominantly Middle–High in 2020, indicating that improvements are spatially uneven and may not be explained by accessibility alone.

6. Discussion

The results obtained in the present research make it possible to corroborate that road accessibility constitutes a relevant factor in the territorial configuration of localities located under peripheral and sub-urban conditions. However, it is important to note that such influence does not manifest uniformly across the territory, since the degree of impact depends on the type of existing connection, the hierarchy of the road network, and the level of integration of each locality with respect to the corridor under analysis.

In this regard, the application of the UMI at the AGEB scale made it possible to identify with greater precision the intra-urban differences present among the analyzed localities, demonstrating that the benefits derived from modernization, conservation, reconstruction, and interchange construction works carried out along the Mexicali–San Felipe corridor are not distributed uniformly. Instead, such benefits respond to specific conditions of accessibility, location, and availability of complementary infrastructure, such as feeder or secondary roads. This finding highlights the relevance of employing micro-territorial units of analysis, since at broader scales, such as the municipal level, these differences tend to become diluted or remain undetected.

In addition, the classification of localities according to levels of direct and indirect accessibility to the road corridor under study made it possible to understand why certain localities exhibit more favorable patterns in urban marginalization levels compared with others, even when forming part of the same road corridor. This finding suggests that primary infrastructure alone does not guarantee generalized improvement processes; rather, the presence of feeder roads or secondary routes, as well as interchanges that strengthen the integration of more distant localities or those with limited connectivity alternatives, proves to be essential.

Beyond connectivity, the results also suggest that road accessibility has also influenced the configuration of economic activity specialization along the corridor. In this regard, a greater consolidation of industrial, agricultural, commercial, and service activities is identified in the northern sector, primarily linked to the urban locality of Mexicali; whereas toward the southern end, in the direction of the urban locality of San Felipe, economic dynamics associated with mining, tourism, and fishing activities are observed. This territorial differentiation reinforces the notion that road infrastructure does not function solely as a transport element, but rather as a structuring axis of economic functions and spatial organization of the territory.

To contextualize local economic change, a macro-regional comparison was conducted using Economic Census data for Mexico and Baja California, for the 2003–2018 period (

Table 7. Economic units by sector and level, census years, growth rates and counterfactual comparison (2003–2018).

Level	Sector	2003	2008	2013	2018 Observed	Growth 2003–2018 (%)	2018 Counterfactual *	Obs–CF
National	Primary	21,252	19,443	20,407	24,372	14.70%	—	—
	Secondary	347,676	461,034	512,346	605,413	74.00%	—	—
	Tertiary	2,241,215	2,750,205	3,107,425	3,488,603	55.60%	—	—
	Total	2,610,143	3,230,682	3,640,178	4,118,388	57.80%	—	—
Baja California	Primary	407	280	269	390	-4.20%	—	—
	Secondary	4971	6608	7888	8815	77.40%	—	—
	Tertiary	46,195	59,632	70,374	76,710	66.10%	—	—
	Total	51,573	66,520	78,531	85,915	66.60%	—	—
Mexicali–San Felipe corridor	Primary	48	31	35	51	6.30%	55	-4
	Secondary	1258	2002	2271	2546	102.40%	2189	357
	Tertiary	12,501	16,059	18,912	20,636	65.10%	19,452	1184
	Total	13,807	18,092	21,218	23,233	68.20%	21,696	1537

Note: * Counterfactual values calculated by applying national sectoral growth rates (2003–2018) to the corridor’s 2003 baseline. Source: author’s own elaboration using INEGI data [107,108,109,110].

). Over this interval, total economic units increased by 57.8% at the national level and 66.6% in Baja California. In contrast, the Mexicali–San Felipe corridor increased from 13,807 to 23,233 establishments, representing a 68.2% growth rate.

Sectoral dynamics further clarify this pattern. Between 2003 and 2018, secondary activities in the corridor grew by 102.4%, exceeding the national secondary growth rate (74.0%). Tertiary activities increased by 65.1% locally, compared to 55.6% nationally. Primary activities grew modestly in both contexts.

To explicitly control for differences in initial economic structure, a sectoral counterfactual projection was estimated, applying national sector-specific growth rates to the corridor’s 2003 baseline. Under this scenario, approximately 21,700 establishments would have been expected by 2018 under national structural trends. The observed total (23,233) exceeds this benchmark, indicating a positive differential relative to national dynamics. In aggregate terms, the corridor’s final position was therefore moderately stronger than it would have been under national sectoral growth dynamics.

While causality cannot be strictly established, this differential performance suggests that local economic dynamics were not limited to a passive replication of broader macroeconomic trends.

Although the results reveal a general trend toward improved conditions associated with quality of life, it must be considered that such transformations may also be influenced by external factors, including regional economic dynamics, sectoral public policies, demographic processes, or urban development strategies independent of road infrastructure. In this regard, the present study does not establish a strictly causal relationship but rather identifies a consistent association between road accessibility and the evolution of socio-spatial conditions within the analyzed territory.

Overall, the methodology employed proved to be appropriate for capturing medium- and long-term changes associated with interventions in the road network, which opens the possibility for application in other territorial contexts with similar characteristics. At the same time, the findings encourage reflection on the importance of incorporating accessibility and territorial equity criteria into the planning of future infrastructure projects, particularly in localities with lower levels of connectivity, in order to promote more balanced and sustainable development processes.

It is worth mentioning that, as future lines of research, it is intended to add to the road accessibility evaluation processes with other aspects that allow identifying improvements in service levels on the roads under study, such as improvements in travel speed, reduction in travel delays and reduction in accidents that occur on the same.

7. Conclusions

This research shows that road accessibility exerts a territorial influence on urban, urban-peripheral, and sub-urban environments along the Mexicali–San Felipe segment of Federal Highway No. 5. Differences in accessibility conditions were associated with differentiated effects on connectivity, service provision, and opportunities for improving population quality of life. In addition, the methodological approach integrated an ex-ante and ex-post analysis to evaluate the Urban Marginalization Index (UMI) at the AGEB scale, which proved effective for assessing the socioeconomic impacts derived from a series of works carried out between 2006 and 2017, including road modernization, conservation, and reconstruction, as well as the construction of an interchange that links the analyzed corridor with other feeder or secondary roads. Within this context, the study identified the following main findings:

• The hierarchical classification of accessibility was confirmed as an appropriate framework for explaining the different levels of territorial impact associated with road infrastructure.
• The main argument for choosing the UMI and its indicators is based on a methodology that has been proven for years, the availability of information to develop it, and the studies that support its implementation when it comes to analyzing territorial inequalities.
• The use of the UMI at the AGEB scale made it possible to identify intra-urban and sub-urban inequalities that would not be observable at the municipal or locality scale.
• The ex-ante and ex-post methodological approach proved effective for identifying gradual and cumulative changes in quality of life through the use of the UMI, in direct association with road works and the accessibility conditions enabled by such interventions.
• The road corridor functions not only as transport infrastructure, but also as a structuring element that influences urban expansion, land use patterns, economic distribution, and territorial reorganization.
• Complementary works, such as feeder roads, secondary road networks, and interchanges, are decisive for the consolidation of accessibility and for the functional integration of the territory.
• The proposed methodological framework is replicable in other contexts where census data and AGEB spatial delimitation are available.

The results indicate that improved operational conditions along the corridor were associated with stronger social and economic conditions of the population in ten surrounding localities, although with varying degrees of intensity. A more significant impact was observed in localities with larger population size and territorial extent, such as Mexicali and San Felipe, where marginalization levels tended to decrease more noticeably and a process of urban expansion became evident through the increase in the number of AGEB. In contrast, other localities—particularly those with a lower degree of direct connectivity—exhibited more moderate yet positive improvements, as observed in Delta, Michoacán de Ocampo, Ejido Puebla, and Nuevo León. An even lower level of improvement was identified in Progreso, Ciudad Coahuila, Guadalupe Victoria, and Carranza; however, this situation highlights the need to develop additional branches or feeder connections that strengthen territorial integration.

In addition, complementary works—such as the construction of interchanges and the presence of feeder or secondary road networks providing access to sub-urban localities and connecting them with major urban centers such as Mexicali and San Felipe—were identified as playing a key role in the functional integration of the corridor. These elements promote processes of urban redistribution and strengthen specific economic sectors along the corridor. In the first section, economic development is mainly associated with industrial and agricultural activities; in the second one, activities are oriented toward mining; and in the third section, dynamics related to tourism and fishing become evident. In several cases, these effects proved to be more decisive than the geographic distance between the localities and the corridor.

These findings suggest that, when designing and intervening in a road corridor, it is essential to account for the accessibility conditions of localities that are farther from the main alignment or have limited connectivity. In this regard, incorporating specific interconnection alignments should be considered to promote more direct communication with the main corridor, while simultaneously strengthening links with major population centers or municipal seats.

The methodological proposal based on the hierarchical classification of accessibility, through the establishment of accessibility levels (Levels A, B, and C) and the use of the UMI at the AGEB level, proved to be a robust and replicable tool for evaluating long-term territorial transformations. In this context, the study demonstrates that road infrastructure not only fulfills a transport function but also operates as a structuring element of the territory, capable of modifying land use patterns, promoting urban expansion and economic development, and contributing to socio-spatial cohesion. Furthermore, the methodology for deriving UMI levels relied exclusively on variables associated with quality of life, such as education, health, and housing, which made it possible to identify that localities with lower accessibility exhibited less favorable marginalization outcomes when compared with better-connected localities.

On the other hand, to conduct a more detailed analysis of the territorial and population-related information of the localities located within the study area and adjacent to the Mexicali–San Felipe highway, georeferenced map representations were developed using a Geographic Information System (GIS). This approach made it possible to examine the relationship between road accessibility levels and urban marginalization levels.

Finally, it is concluded that improvements in road accessibility are consistently associated with processes of territorial transformation and reductions in urban marginalization in urban, urban-peripheral, and sub-urban areas. While a strictly causal relationship cannot be definitively established, the evidence suggests that accessibility constitutes a relevant structuring factor in shaping socio-spatial dynamics. These findings highlight the importance of incorporating accessibility criteria into the planning of road infrastructure projects, particularly in localities with lower levels of connectivity, in order to promote more balanced and inclusive development.