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This work is part of the Research Project, registered with the Research and Postgraduate Secretariat of the National Polytechnic
Institute: 20230596, called: “Residential segregation in the Context of Polycentrism and Urban Dispersion in Mexican Cities
Doctor en Urbanismo
Profesor investigador de la Escuela Superior de Ingeniería y Arquitectura.
Instituto Politécnico Nacional, Miguel Hidalgo, México.
https://orcid.org/0000-0002-8027-8648
rgomezma@ipn.mx
https://doi.org/10.22320/07183607.2024.27.49.08
1
2
Recibido: 07-05-2023
Aceptado: 21-05-2024
¿CIUDAD FRAGMENTADA O DESINTEGRADA? LOS MODELOS URBANOS APLICADOS A
LAS CIUDADES INTERMEDIAS EN MÉXICO DESDE LA GEODEMOGRAFÍA
FRAGMENTED OR
DISINTEGRATED CITY?
URBAN MODELS APPLIED
TO INTERMEDIATE
MEXICAN CITIES FROM
THE PERSPECTIVE OF
GEODEMOGRAPHY
1
RICARDO GÓMEZMATURANO 2
¿CIUDAD FRAGMENTADA O DESINTEGRADA? LOS MODELOS URBANOS APLICADOS A LAS CIUDADES INTERMEDIAS EN MÉXICO DESDE LA GEODEMOGRAFÍAO JOHANNA
RICARDO GÓMEZ-MATURANO
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PÁG. 108 - 121
ISSN 0717 - 3997 / 0718 - 3607
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Urban models are fundamental in the theoretical and empirical discussions about cities. However, the Latin American city models
proposed by German geographers have not been questioned much despite their use, and there are few studies outside the large
metropolitan areas. Therefore, this article, using geodemography, seeks to identify whether there is a residential structure pattern
in the intermediate cities of Mexico’s National Urban System. This methodological proposal looks to use new spatial analysis
tools focused on lifestyles and the study of one of the great layers that urban models have: their residential structure. The results
show that, rstly, using the models and their temporalities as a kaleidoscope, it is possible to identify the multiple patterns of
cities and not just a single model. Secondly, a new disintegrated pattern appears where the classical models of the Chicago
School are unrecognizable, and the fragmented city is left disintegrated.
Keywords:Utopian cities, intermediate cities, data analysis, residential segregation, urban modeling.
Los modelos urbanos son fundamentales en la discusiones teóricas y empíricas de las ciudades. Sin embargo, los modelos de
la ciudad latinoamericana propuestos por geógrafos alemanes no han sido muy cuestionados a pesar de su empleo y, por otra
parte, existen pocos estudios fuera de las grandes áreas metropolitanas de Latinoamérica. Por ello, se busca identicar si existe
un patrón de la estructura residencial de las ciudades intermedias del Sistema Urbano Nacional de México por medio de la
geodemografía. Esta propuesta metodológica busca traer nuevas herramientas de los métodos de análisis espacial, enfocados
en estilos de vida, y centrase en el estudio de una de las grandes capas que tienen los modelos urbanos, la de su estructura
residencial. Los resultados muestran en primer lugar que, utilizando los modelos y sus temporalidades como caleidoscopio, se
pueden identicar los múltiples patrones de las ciudades, y no un único modelo. En segundo lugar, aparece un nuevo patrón
desintegrado donde no son reconocibles los modelos clásicos de la Escuela de Chicago y donde la ciudad fragmentada quedó
desintegrada.
Palabras clave: ciudades utópicas, ciudades intermedias, análisis de datos, segregación residencial, modelos urbanos.
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I. INTRODUCTION
Urban models were fundamental elements in both
theoretical and empirical discussions in the 20
th
century
(Szupiany, 2018, p: 102). These had three fundamental
connotations, according to Janoschka (2005): a
constructive utopia, such as the garden city; others
generated by deductive logic, such as those of Christaller
or von Thünen; and the models that emerged from
the simplification of complex realities, known as city
structural models. The latter are mainly associated with
the work the Chicago School of Human Ecology carried
out in the 1920s: the concentric ring model, the sector
model, and the multi-core model (Linares, 2012, p:16).
At the end of the 20
th
century, emerging models were
called into question due to the crisis of modernity.
However, Borsdorf (2003) affirmed their methodological
validity, defending their usefulness to the specificities
of the Latin American city. At the beginning of the 21
st
century, some urban models applied to Latin American
cities were developed, in particular, proposed by
researchers from other latitudes who used these cities
as analysis (Borsdorf, 2003; Borsdorf et al., 2002; Ford,
1996; Janoschka, 2002). Sometime later, some urban
researchers became concerned about adopting these
models. From Mexico, Álvarez (2010) questions the
applicability of the theoretical currents based on the
study of cities in North America, Europe, and Oceania to
the context of Mexican cities. This approach coincides
with the perspective of Delgadillo (2019), who argues
that “the adoption of concepts and theories developed
by researchers studying different urban realities and
in other linguistic contexts can provide a limited
understanding of local urban processes” (p.62).
In particular, on the models developed by German
geographers in Latin America, Orellana (2020) points
out that there is no further analysis despite being a
widely used reference by urban studies. Therefore, the
author argues that it is essential to question and refute
its applicability, for example, in intermediate urban
systems. In the same sense, Álvarez (2010) points out that
studies tend to focus on metropolitan areas, with limited
attention to medium-sized cities.
In this context, this research aims to identify whether
there is a pattern of the residential structure of the
Intermediate Cities of the national urban system of
Mexico through geodemography. This methodological
proposal seeks new tools to “analyze people according
to the place where they live” (Harris et al., 2005, p. 2). In
this way, with the data sources of the National Institute
of Statistics and Geography (INEGI) of 2020, and together
with the spatial analysis methods focused on lifestyles,
it is sought to have a sound methodology for the study
of one of the great layers that urban models have, that of
their residential structure.
II. THEORETICAL FRAMEWORK
The models of the Latin American city are up for
debate
The urban models applied to Latin America at the end
of the 20
th
century and the beginning of the 21
st
century
were developed by researchers from other latitudes,
who used these cities as analysis (Ford, 1996; Borsdorf,
2003; Janoschka, 2002). The first was Ford (1996), who
presented an urban model at the end of the 20
th
century
that retains the basic structure of rings and sectors of
the Chicago School models but introduces six significant
modifications. The second model is the joint proposal
of Borsdorf et al. (2002), which Borsdorf (2003) presents
as the historical development of Latin American cities
up to the fragmented city. However, the model that had
the most significant impact on academia was that of
Janoschka (2002), highlighting the emergence of insular
urban forms that differ from traditional city models in the
region (Figure 1).
After these publications, a large number of studies
appeared that sought to find out if these proposed
models followed the reality of Latin American cities
in different geographies such as Chile (Valdebenito,
2014; Orellana, 2020), Argentina (Linares, 2012; Buzai,
2014; Buzai & Montes (2020) or Mexico (Alvares, 2010;
Göbel, 2015; Aguilar & Mateos, 2011). Other studies
only mentioned them to frame their conclusions about
the transformation of the Latin American city without
any robust analysis or questioning the interpretative
delimitation of these models.
In particular, in Mexico, a study of 32 cities developed
based on three indicators found that these cities do
not entirely conform to the theoretical models of a
monocentric urban structure and, in addition, over time,
cities tend to be less concentric and develop another
type of spatial organization (Álvarez, 2010). Another study
in Mexico notes that “the Latin American city model by
Bähr, Borsdorf and Mertins describes many development
trends that occur in the process of the metropolization
of the urban agglomeration of Querétaro” (Göbel, 2015,
p. 59). However, Querétaro today represents a typical
city where tradition, modernity, and poverty are directly
confronted (Göbel, 2015). Another study that related
urban models and residential segregation sought to
identify demographic differentiation in the Metropolitan
Area of Mexico City. It found that they followed the
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Figure 1. Theories of the internal structure of the Latin American city. Source: Author’s elaboration based on Ford (1996), Borsdorf (2003), and
Janoschka (2002).
traditional residential segregation model regarding the
spatial distribution of socioeconomic groups (Aguilar &
Mateos, 2011). However, there are indications of a more
recent model of urban dispersion and fragmentation of
space, with the presence of socio-economic groups such
as the peripheral proletariat and the marginal urban-rural
periphery. In addition, office workers in housing units tend
to be located in interstitial areas and along main road
accesses (Aguilar & Mateos, 2011). This analysis generated
locations similar to those found in the study associated with
the pattern of residential segregation in Latin American
cities (Gómez-Maturano & Kunz, 2020)
As for the validity of the models of German geographers,
some authors nd many trends that occur in the city’s
metropolization process (Göbel, 2015; Aguilar & Mateos, 2011).
Other researchers, in addition to the signs of the German
models, identify that the structural elements are synthesized
together with other models and that they sometimes
represent a historical evolution of city organization (Linares,
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2012; Buzai & Montes, 2020). Ultimately, with a more critical
perspective, it is concluded that the models of German
geographers do not explain the entire Latin American city
(Valdebenito, 2014) since cities do not entirely conform
to the theoretical models of a specic urban structure
(Alvarez, 2010). This is because there may be particularities
in cities, such as political and social processes and even
urban phenomena, such as conurbation, that modify them
(Orellana, 2020).
IV. METHODOLOGY
The object of study is the intermediate cities of Mexico,
considering what has been pointed out by authors
such as Alzate (2023), that its conceptualization is under
construction. In this sense, the characterization of a study
by Navarro et al. (2023) is returned to, where intermediate
cities in Mexico are dened as “those included in the
metropolitan context, with a population range between
500,000 and one million inhabitants, that are not part of
a higher-ranking metropolitan system” (p. 8). These cities
coincide in their characteristics with the UN list of cities
(2019), where Mexican cities are classied into three groups:
large metropolitan areas, metropolitan areas, and medium
urban areas (Table 1) (Figure 2). In this case, the so-called
metropolitan areas are considered intermediate cities in this
study.
As for the methodology, geodemography was returned to,
Urban agglomeration 2015 Population
Culiacán 754.000
Xalapa 719.000
Oaxaca de Juárez 655.000
Celaya 640.000
Durango 573.000
Pachuca de Soto 570.000
Ciudad Juárez 1.423.000
La Laguna 1.313.000
Querétaro 1.214.000
San Luis Potosí 1.126.000
Mérida 1.064.000
Mexicali 1.026.000
Aguascalientes 1.017.000
Cuernavaca 998.000
Chihuahua 950.000
Tampico 928.000
Acapulco de Juárez 920.000
Saltillo 901.000
Morelia 888.000
Veracruz 864.000
Villahermosa 825.000
Reynosa 810.000
Cancún 802.000
Hermosillo 789.000
Tuxtla Gutiérrez 763.000
Figure 2. Intermediate Mexican cities. Source: Prepared by the author based on the United Nations list of cities (2018).
Table 1. List of intermediate Mexican cities. Source: Prepared by the
author based on the United Nations list of cities (2018).
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which is the “analysis of people according to the place where
they live” (Harris et al., 2005, p. 2), i.e., knowing where someone
lives provides valuable information about how that person lives.
This spatial analysis method has the following structure. First,
data from the 2020 Population and Housing Census (INEGI, 2020)
were collected and input, from which the analysis variables
were selected, which refer to the people and places where they
live. Secondly, regarding the statistical techniques, a Principal
Components Analysis (PCA) was performed, the primary
objective of which was to reduce the dimensions and synthesize
the data input information into the procedure. Along with this
analysis, a correlation analysis was performed to reduce the
database’s dimensions, which comprised 61 variables (Table 2).
Short name of Variable Description of the Variable
GRAPROES Average level of schooling
HOGJEF_F Census households with female reference.
HOGJEF_M Census households with a male reference.
OCUPVIVPAR Occupants in inhabited private dwellings.
REL_H_M Male-female ratio
P12YM_SEPA Population aged 12 and over who were married or cohabiting.
P12YM_CASA Population aged 12 and over who are married or cohabiting
P12YM_SOLT Population aged 12 and over who are single or never cohabited.
P18YM_PB Population aged 18 and over with secondary education and above
P3YM_HLI Female population aged 3 years and over, who speak an indigenous language.
PAFIL_IPRIV Population aliated with private health services.
PAFIL_OTRAI Population aliated with another institution.
PAFIL_PDOM Population aliated in PEMEX, Defense, or Navy
PCON_DISC Population with disabilities
PDER_IMSS Population aliated with the IMSS.
PDER_ISTE Population aliated with the ISSSTE.
PDER_SEGP Population aliated with the Health and Welfare Institute.
PEA Population aged 12 and more who are economically active.
PNACENT Population born in the entity.
PNACOE Population born in another entity.
POB0_14 Population from 0 to 14 years.
POB15_64 Population from 15 to 64 years old.
POB65_MAS Population aged 15 to 64
POBTOT Total population.
POCUPADA Population aged 12 and over who are employed.
PRES2015 Population aged 5 and over residing in the entity in March 2015
PRESOE15 Population aged 5 and over residing in another entity in March 2015
PROM_OCUP Average number of occupants in dwellings
PSINDER Population without aliation with health services
PROM_HNV Average number of children born alive
TVIVHAB Total number of inhabited dwellings
TVIVPAR Total number of private dwellings
VIVPAR_DES Uninhabited private homes.
VIVTOT Total number of dwellings
VPH_1CUART Private dwellings inhabited with only one room
VPH_1DOR Houses with one-bedroom
VPH_2CUART Houses with two bedrooms.
VPH_2YMASD Houses with two or more bedrooms.
VPH_3YMASC Houses with three or more bedrooms.
VPH_AGUADV Homes that have piped water in the housing area.
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Short name of Variable Description of the Variable
Table 2. List of the variables selected for cluster analysis. Source: Prepared by the author based on the 2020 Population and Housing Census
(INEGI, 2020), some names were abbreviated.
The second statistical process was the cluster analysis, which
aims to group individuals with similar characteristics and is
assisted by a dendrogram. Thus, in addition to creating groups,
this analysis sought to hierarchize the datasets to have a
predetermined order in which similar observations are grouped
using the spatial analysis units called Basic Geostatistical Areas
(BGA), the census areas in Mexico.
Finally, in conceptual terms, this study will refer to
geodemographic groups as the groups that, in the classical
models, were called the upper, middle, and lower classes.
V. RESULTS
Who are the geodemographic groups, and how do they
live?
The cluster analysis and the dendrogram based on Harris et al.
(2005) showed three groups in almost all cities as the fewest
groupings. Each group has specic characteristics in their
housing, such as the degree of urbanization, the satisfaction
with housing, certain types of people from the educational point
of view, family status, life cycle, socioeconomic characteristics,
access to health, and migration. In particular, clusters one and
three are opposite in their characteristics, and cluster two is a
mixture of both. In some cases, the dierence between the two
main groupings is not very high, for example, in Cancun, Merida,
Aguascalientes, Oaxaca, Acapulco, and Cuernavaca. However,
in another, it shows considerable dierences, as is the case of
Culiacán, Saltillo, Durango, Mexicali, Xalapa, Morelia, and Pachuca
(Figure 3).
As for the characteristics of the housing, cluster three has more
private homes; in general, they have more rooms, they have
a oor that is not the earth, toilets, and a water tank; on the
contrary, those in cluster one are not private homes, in general,
they have fewer rooms, there are more unoccupied homes, and
they have less infrastructure. As for the degree of consolidation
of urbanization, number three has drainage, water, and
electricity; on the contrary, number one has a lower degree of
consolidated urbanization.
In addition, regarding the satisers of everyday life, cluster three
mostly has the internet, computers, laptops or tablets, video
game consoles, landlines, paid TV services, and paid-for movie,
music, or video streaming services. On the contrary, cluster
one is characterized by not having these satisers of everyday
life. Finally, regarding mobility, cluster three has a car, van,
motorcycle, or scooter, while cluster one uses bicycles more as a
means of transport.
VPH_BICI Homes with a bicycle as a means of transport.
VPH_C_ELEC Homes with electricity.
VPH_CEL Homes with cell phone
VPH_CISTER Homes with a cistern or tank
VPH_CVJ Homes with video game consoles.
VPH_DRENAJ Houses with drainage.
VPH_EXCSA Housing with toilet.
VPH_INTER Homes with Internet.
VPH_NDACMM Homes with a car or van, not a motorcycle or scooter.
VPH_PC Homes with a computer, laptop, or tablet.
VPH_PISODT Houses with oors made of materials other than earth.
VPH_SINCINT Homes without a computer or Internet
VPH_SINTIC “Housing without information and communication technologies (ICT)”
VPH_SNBIEN Houses without any assets
VPH_SPMVPI Homes with paid movie, music, or video streaming service
VPH_STVP Homes that have to pay for TV service.
VPH_TELEF Homes with a landline.
VPH_TINACO Houses with water tank.
VPH_TV Homes with TV
VPH_SINRTV Homes without radio or television
VPH_SINLTC Homes without a landline or a cell phone
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Figuea 3. Radar graph of clusters 1 (blue line) and 3 (orange line) of the Intermediate Cities of Mexico with selected variables. Source: Preparation
of the authors based on the geodemography methodology described in Harris et al. (2005).
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Cluster three is characterized, from an educational point of
view, by having a higher preparation; that is, they have at
least high school studies; cluster one generally has a lower
education. In terms of household types, cluster three has
more married people, with more male heads of household,
and they are larger families; cluster one has fewer married
people, more separated people, and more female heads of
household. For the life cycle, cluster three has a mixture of
children, young people, adults, and older adults, and the one
has a more young and adult population than children and
older people.
In the socio-economic category, Cluster Three has a higher
economically active population and a higher employed
population, while Cluster One is less connected to the
labor market. In health, cluster three, in general, is more
aliated with health services; on the contrary, those in
cluster one are not aliated with these health services but
are more aliated with the Health Welfare Institute (social
health model); therefore, they are characterized by being
a population with more people with some disability. As for
migration, cluster three has a larger population born in the
entity; on the contrary, cluster one is characterized by having
a migrant population.
Some cities do not necessarily respond to these
characteristics from a demographic point of view. However,
in some specic cases, there are dierences, such as tourist
cities, and others are considered typical cities in their
characteristics.
The geodemographic patterns of Mexican
intermediate cities.
From the spatial point of view, the intermediate cities of
Mexico were classied into dierent geodemographic
patterns. The rst is the pattern of concentric circles;
examples are Pachuca, Morelia, Tampico, Cancun, and
Xalapa. In these cities, the high geodemographic group
is characterized by having better housing, living in spaces
with a better degree of urbanization, and more satisfactory
Figure 4. The geodemographic pattern of concentric circles. Source: Author’s elaboration.
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housing (cluster three). They are located in the center, and
their presence decreases as one moves away from the
center. The middle geodemographic group, characterized
by a mixture (cluster two), occupies the second ring, and
the lowest is located in peripheral sectors (cluster one). On
the other hand, another city in concentric circles, but where
the low geodemographic group is located in the center
of the city, is Tuxtla in Chiapas, where the middle groups
are located in the second ring and the high ones on the
periphery. Interestingly, most of these cities are in central
and southern Mexico (Figure 4).
The second pattern is concentric circles and sectors in San
Luis, Celaya, and Mexicali. In this, it can be seen that the
highest income geodemographic groups (cluster 3) are
located in the third ring on the periphery but grouped into
sectors in the city. Those with low incomes (cluster 1) are
located both on the peripheries and in the central part of the
city in small fragmented sectors. Finally, the middle occupies
the second ring, sharing space with the upper class in some
cases (Figure 5).
Figure 5. The geodemographic pattern of concentric circles and sectors and the polarized pattern in concentric circles and fragmented sectors.
Source: Preparation by the Author.
The third geodemographic pattern is that of fragmented
sectors in La Laguna, Durango, and Juárez. In this case,
the geodemographic groups with the highest incomes
are located in the so-called high-income cone, but in
a fragmented way, mixing with the middle and lower
classes. On the other hand, the lower income groups
are scattered throughout the city, mainly in the center,
in the second contour, and on the periphery, but with
emphasis on one sector of the city. On the other hand,
the middle groups are found as the space that brings the
city together (Figure 5).
The fourth pattern is the city fragmented into concentric
circles, represented by Chihuahua, Saltillo, Merida,
Aguascalientes, Culiacán, and Hermosillo. In this case,
the geodemographic groups with the highest incomes
are located mainly on the periphery of cities in the form
of concentric circles but in a fragmented way without
generating sectors. In the second contour, the middle
class is present, which allows for the location of many
fragments of low and high groups. Generally, the sectors
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with the lowest incomes are located in a fragmented way in the
center, in the second contour, and on the periphery of the city
(Figure 6).
The fifth geodemographic pattern is the disintegrated one,
where the large sectors referred to in the fragmented city
models are not identified; this pattern seems pulverized.
Examples are the cities of Querétaro, Villahermosa, Oaxaca,
Acapulco, Cuernavaca, and Veracruz. These cities are
determined by having multiple nuclei, not sectors, similar to
the different socio-demographic groups, high, medium, and
low (Figure 7).
VI. DISCUSSION
The results show that the city models of German geographers do
not explain all Latin American cities from the geodemographic
point of view, which is evidenced by the rst patterns identied
in concentric circles and sectors. These cities are related to the
model of Burgess, Hoyt of the Chicago School, and Ford (1996).
However, in these cities, except for Tuxtla, the central parts are
still used by the urban elites, as was identied by Borsdorf et al.
(2002), but for the colonial city that they called compact, from
1550 to 1810, and the city of the rst phase of urbanization until
1920, which they called a sectoral city.
The patterns where the anity with the current models begins
to be identied are the so-called fragmented sector and the
fragmented pattern in concentric circles. In these, it is possible
to identify that pointed out by Linares (2012) and Buzai and
Montes (2020), who synthesize patterns together, as these cities
are a mixture of Burgess’ concentric circles’ models, the sectors
of Hoyt, that of Ford (1996) and the so-called polarized city
identied by Borsdorf et al., (2002), for the seventies, where the
groups are located in opposite sectors of the city, but in this
case in a fragmented way as was identied in the models of
Figure 6. The geodemographic pattern fragmented into concentric circles. Source: Preparation by the author.
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Figure 7. The disintegrated geodemographic pattern. Source: Preparation by the Author.
German geographers (Borsdorf et al., 2002; Janoschka, 2002; and
Borsdorf, 2003).
Finally, in the disintegrated pattern, the sectors and concentric
circles that are still identied in the Ford (1996), Borsdorf (2003),
and Janoschka (2002) models no longer appear. This pattern
seems closer to the new Urban Sprawl models in studies
worldwide (Seevarethnam et al., 2021) and in Latin America
(Silva & Vergara-Perucich, 2021). This could be explained by
the conurbation phenomenon identied by Orellana (2020)
or because the city grew dispersed along the main roads.
Therefore, sectors that gather social groups are not identied
but appear fractured throughout the territory. In these cities, the
fragmented city seemed disintegrated; this new pattern needs
to be analyzed in greater depth in future studies.
The study carried out had limitations in proposing an urban
model. On the one hand, only one of the layers of the urban
structure was worked with, the residential structure that
allowed identication of the geodemography, which left
aside other factors, such as the road network, the location of
industry, commercial activities, centralities, the existence of
closed neighborhoods, degradation processes, informality, and
gentrication. On the other hand, the previous models are based
on the analysis of the evolution of large cities, so it refers to the
processes.
This study considered only the situation in 2020. Therefore,
intermediate cities and the possibility of proposing some models
could be considered future lines of research. Finally, the applied
methodology allowed us to identify how they live and who, in
the classical models, are generically called upper, middle, and
lower class. The high-income geodemographic group lives in
their own homes, they have more rooms for family members,
and generally, they will have their housing nished with all the
necessary additions. They live in the consolidated areas of the
city, and in those newly created with all the urban services,
they have most of the satisfactory ones, from the typical ones
120
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like pay television to having all the ICTs; their mobility is
supported with automotive means. These people generally
have university studies, live in nuclear families, where
men exercise greater domination, in diverse spaces in the
life cycle, have greater integration into work, have health
services, and are generally a native population. The low-
income geodemographic group often presents a duality of
these characteristics.
VII. CONCLUSIONS
The results show that no urban model explains all the
geodemographic patterns without considering a unique
pattern in the intermediate cities in Mexico. However, as
a whole, all the models allow us to understand complex
cities, combining patterns and temporalities and perhaps
identifying a pattern in that kaleidoscope that allows us to
understand the cities. This is in order not only to identify the
model to which a city belongs, but to the city that would be
transformed in the future: a polarized city, a city segregated
into sectors, a fragmented city, a scattered city, or that new
pattern that seems to be emerging from the disintegrated
city.
This is not the diuse city or the Urban Sprawl that was
looking for a new, less hierarchical spatial organization. Nor is
it a fragmented city, since it is not only broken and separated,
but the disintegrated city seems to be the dissolution and
decomposition of the city, losing spatial unity and social
cohesion that could have severe consequences for the
quality of life for people by dismembering community
relations, replacing them with highly individualized spaces
where the weakening of the community is appreciated. At
the moment, these data provide a basis for future research.
However, it is essential to explore this new vein to increase
knowledge about the urban and metropolitan phenomenon
in Mexico.
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IX. ACKNOWLEDGEMENTS
Thanks must go to the students of the Delfín del Verano
Cientíco 2023 program: Xochitl Jazmin Padilla Cabrera, Enrique
Mendiola Bretón, Andrea Carolina Arroyo Guzmán, Alfredo
Gabriel Velazco Cardoso, Athony David Bautista Bernardino,
Juan Esteban Mejía Sánchez, Maria Paula Muñoz Cardona, María
Guadalupe Ramírez González, Eliana Gyneth Bellón Daza, and
Betzabe Hernández Flores; to the intern, Nazly Zharikc Vargas
Moreno from Universidad Unitrópico, in Yopal Colombia;
the intern, Paulina Alessandra González Cruz from ESIA. U.
Tecamachalco; and nally, the CONAHCYT post-doc student,
Victor Reyes García.
