Mexico City’s Urban Trees Reforestation Based on Characteristics of

Plantation Sites

Héctor Javier Vázquez

and Mihaela Juganaru

Departamento de Sistemas, Universidad Autónoma Metropolitana, Unidad Azcapotzalco, Avenida San Pablo 420,

Col. Nueva el Rosario, C.P. 02128, Azcapotzalco, Ciudad de México, Mexico

Institut H. Fayol, Ecole Nationale Supérieure des Mines, 158, cours Fauriel, 42023, Saint Etienne, France

Keywords: Urban Trees, Plantation Sites, Categorical Variables, Correspondence Analysis, Cluster Analysis.

Abstract: Urban trees reforestation grounded in characteristics of plantation sites is necessary to tree maintenance and

health care. Decisions concerning when, where and which tree species to plant have important consequences

for tree survival and resilience. Through the application of Multiple Correspondence Analysis and Clustering

of qualitative criteria, it was possible to establish nine clusters based on the qualitative modalities of planation

sites and so to associate them with urban tree species. The use of indexes related to the percentage of

modalities with respect to the sample, specificity and homogeneity of clusters resulted useful criteria to

describe plantation sites. We study the case of urban trees in Mexico City.

1 INTRODUCTION

There is no doubt about the importance and benefits

of trees in urban environments, mainly: their

contribution to the environment, such as oxygen

generation, smog retention, particle filtering, carbon

dioxide sequestration and pollutants transformation.

Other functions, no less important, are water

retention, soil erosion reduction, climate formation,

temperature control and energy savings. Urban trees

also create microecosystems allowing the existence

of many other species, such as animals, fungi, plants

and microorganisms. Finally, urban trees are

appreciated for their psychological, aesthetic,

polychrome and economic functions; functions that

are undoubtedly important factors for improving the

quality of life of the urban population.

Over half of the world’s human population live in

cities, however urban trees species represent no more

than 6% of the 70,000 species living on earth (Ossola,

2020, Slik, 2015), In the city (Lüttge, 2023), trees are

distributed in streets and ridges (usually called

alignment trees), in parks and gardens (recreational or

not, public and private), in urban forests (with a high

significant density) and in many public and private

green areas (protected or not).

https://orcid.org/0000-0002-4329-3101

In Mexico City since the late twentieth century,

trees’ survival has been a growing concern, indeed

trees’ survival is estimated between 40 to 50 percent

(Deloya, 1993).

Despite different initiatives, such as

Environmental Laws (PAOT, 2023), the progressive

degradation of tree resources seems ungovernable,

not only because of environmental stress and urban

pressure, but also due to erroneous planting and

management practices (Benavides, 2004, Green,

2016); neglecting key aspects such as the trees’

ability to adapt to diverse urban conditions (types of

soil, pollution levels) along the 1.485 km² of Mexico

City (Aldama, 2002, Meza, 2010).

Urban Tree inventories (Chacalo, 1996, Segura,

1996) provide information about trees’ species

distribution along urban areas, their age distribution,

their state of health, their physical condition, the site´s

characteristics for planting, trees’ tolerance and

survival rates to certain environments. However, they

require significant financial resources, which are not

always readily available despite the obligation to

carry out periodic inventories. (Article 88 of the

Environmental Law of 2000). Most of the official

studies have been carried by sampling (PAOT, 2018).

These results are reinforced with Satellite Imagery

(Bravo-Bello, 2020), with experts’ opinions in

Vázquez, H. and Juganaru, M.

Mexico City’s Urban Trees Reforestation Based on Characteristics of Plantation Sites.

DOI: 10.5220/0012250300003598

In Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2023) - Volume 1: KDIR, pages 437-444

ISBN: 978-989-758-671-2; ISSN: 2184-3228

437

different fields related to tree planting practices and

with technical documents such as manuals, books,

catalogues and articles (Benavides, 2004,

CONABIO, 2023). From these multi sources, data

bases can be tailored (PAOT, 2000a, PAOT 2000b)

and using the statistical analyses and machine

learning methods an establishment of sound

management and suitable maintenance programs can

be built. One of the goals of these analyses is to

identify which species are better for a given site. A

previous work (Vázquez, 2016) focused on

identifying associations between species and

preferred plantation sites through association rules.

However, their use, in real situations, was limited due

to low thresholds, the significant number of rules, and

the presence of irrelevant associations. In this paper,

Multiple Correspondence Analysis and a Hierarchical

Classification Algorithm (Lebart 2006) are used to

identify attribute similarities and to build groups of

trees’ species based on their qualitative variables.

Clusters are described in terms of the modalities of

these qualitative variables, through indicators related

to homogeneity and specificity of individuals.

In the next sections, data presentation and their

multivariate categorical nature are recalled, followed

by a description of the statistical analyses and their

interpretation. Finally, the main results, including

clusters description, are presented.

2 METHODOLOGY

We use a collection of 134 species that are really used

as urban trees in public and private space in Mexico

City (PAOT 2000a). The data was collected, the

attributes were described, and the data processing was

realized.

2.1 Data

The data was obtained by combing two data sets.

These data is public and published on https://www.

emse.fr/~mihaela.juganaru/data/trees/. For each one

of 134 trees’ species, all the details are given. We will

explain the features /attributes and processing.

2.1.1 Data Attributes

The data set contains 134 trees’ species characterized

by their tolerance to specific environmental stress,

such as: cold (

tcold), dryness (tdry), mistreatment

(

tmiss) and soil salinity (tsal); the recommended

planting sites (sidewalks and ridges (

s_street),

urban recreational parks (

s_urbrp), parking lots

(

s_parlot), beneath or under electrical lines

(

s_beleclin), cemeteries (s_cem), sport fields

(

s_sport_f), urban forest (s_urbfor); and their

response to pollution (

sensitivity = 1,

tolerance = 2, resistance = 3, and

resilience = 4) to the following four levels of air

pollution:

•

VeryHighPollution = (SO2 > 500, NOx

> 2000,CO > 3000, PST > 2000)

•

HighPollution = (251 < SO2 < 500; 500

<NO

x < 2000; 500 <CO < 3000; 500 < PST

<2000)

•

MildPollution = (101 < SO2 < 250;100

<NO

x < 500;100 < CO < 500;100 < PST

<500)

•

LowPollution = (SO2 < 100;10 < NOx

<100; 10 < CO < 100; 10 < PST < 100).

2.2 Data Processing

In the aim to obtain interesting and useful results, we

must solve firstly the problem of missing vales, to do

a reduction of the number of features without losing

information and, finally, to apply an unsupervised

learning method.

2.2.1 Descriptive Statistics

The descriptive statistical analyses of the 134 species

attributes was carried out, limited to the counting of

modalities (without and with missing values) and

calculation of percentages. The imputation method

proposed by Jossé et al. (Jossé, 2012) was used to

treat missing modalities. This method resulted

suitable for treating absent categorical variables with

missing modalities as it respects the pre-existing

associations between variables without absent

modalities.

Once the absent modalities have been imputed,

the Multiple Correspondence Analysis is applied.

This step generates the coordinates of the individuals

with respect to a set or subset of factorial components.

2.2.2 Multiple Correspondence Analysis

Multiple Correspondence Analysis (MCA) is applied

to data characterized by categorical variables, with

two or more modalities (Lebart, 2006, Costa, 2013).

MCA is a generalization of the Correspondence

Analysis (CA) developed for the analysis of a

contingency table with two categorical variables. In

the case of the MCA, a complete disjoint table is

constructed, from a table where each variable is

recoded, according to the number of modalities. The

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438

crossing of the modalities allows to obtain a Burt's

contingency table. As with the CA method, the

application of the MCA generates components or

factorial axes associated with eigenvalues; a drastic

change in the profile of the eigenvalues defines the

number of axes to be retained and the percentage of

information analysed. On these axes the coordinates

of species, variables and modalities are established,

as well as the part of inertia to which each species,

variable or modality contributes to the formation of

axes (contribution). The coordinates of the

individuals (species) generated by the MCA are also

the basis for the imputation of absent modalities.

Further details can be found in (Jossé, 2012, Vazquez,

2014).

2.2.3 Cluster Analysis

Clusters Analysis is applied on the initial categorical

data or on the factorial coordinates of individuals,

results of the MCA (Lebart 2006). If all the

components resulted from the MCA analysis are

considered (total number of modalities minus number

of variables) the results of the Cluster Analysis are

equivalent to those that would be obtained with the

initial categorical data, since in principle, there is no

loss of information. However, generating clusters

from coordinates avoids the need to find a suitable

metric for categorical data. In this work, the algorithm

of hierarchical classification agglomerative with the

method of Ward (method of the minimum variance)

and the Euclidean metric are applied. To get an idea

of the number of clusters, evaluations are made using

the Silhouette index and the Dunn index. The first

evaluates the degree of compaction of the clusters and

the second the separation between them (Brock

2008). The clusters are described in terms of the

modalities of a variable, using the following three

indicators (Lebart 2006):

• Global Proportion: percentage of individuals

(with respect to the total), that have the indicated

modality.

• Cla/Mod Ratio: number of species within the

cluster, presenting the modality with respect to the

number of times the modality occurs in all species

of the data set. This proportion can be seen as a

measure of the degree of specificity of the group

in relation to a modality.

• Mod/Cla Ratio: the number of species in the

cluster, which exhibit the modality, with respect

to the number of species within the cluster. This is

considered a measure of homogeneity of

individuals within the cluster in relation to

modality.

The test value (v.test) allows to evaluate the

difference between the proportions and the overall

proportion. In terms of the test value the difference is

significant if the test value is outside the range (-1.96,

1.96). This value gives more information over the p-

value, since the positive sign of the test value

indicates the existence of an overrepresentation in the

cluster and an underrepresentation in the negative

case. The positive values of v.test, suggest a positive

correlation with the group, while a negative value a

negative correlation.

Calculations for Multiple Correspondence

Analysis, Cluster Analysis and validation tests were

performed using the R program version for Windows

version 4.2.3 (R Core Team 2023). The FactoMiner

library (Lê, 2008) is used for MCA and Cluster

Analysis. The missMDA library (Jossé, 2012) was

used for the imputation of missing values.

3 RESULTS

We will present and interpret the Descriptive

Statistics, the results of Multiple Correspondence

Analysis and of the Clustering.

3.1 Descriptive Statistics

Concerning missing values, 57 values were detected

on variables mild pollution and high pollution; and 58

missing values were detected on variables about

pollution. This accounted for 20% of values for those

variables and affects 42.45% of the species. The

results before imputation (Vazquez, 2014) are: of the

134 individuals, 30.59% is composed of the genera

Pinus (22), Quercus (14) and Cupressus (5), while

53.73% make it up in addition to the three genera

mentioned, the genera Acacia (4), Ficus (4),

Juniperus (4), Prunus (4), Eucalyptus (3), Ligustrum

(3), Populus (3), Salix (3 ) and Ulmus (3). 46.27%

of the species are considered only trees, 14.18% are

identified only as shrubs, 23.13% are counted under

the category of trees "and" shrubs, 11.94% are trees

"and/or" fruit shrubs and the rest of the species are

classified as palms, although some are also

considered trees or shrubs. Only 11.94% of the

proposed species are fruit trees. Some species are

classified into more than one category; for example,

72.39% of trees’ species are classified as trees, but

some are also classified as shrubs, fruit trees or palms.

Just over 66% of the species are classified as

evergreen and the rest as deciduous.

Half of the species are native to Mexico (of these

10 are also native to the United States and one to

Mexico City’s Urban Trees Reforestation Based on Characteristics of Plantation Sites

439

Guatemala). A little more than a quarter (25.37%)

come from the Asian continent, 10.45% from the

European continent, 7.46% come from Africa or

Oceania and the rest from the United States and South

America. 46 trees of Mexican origin maintain their

foliage all year round.

In relation to tolerance to stress, 82.84% tolerate

frost (

tcold), 49.25% are tolerant to water scarcity

(

tdry), while 32.84% are tolerant to salinity (tsal).

However, 70.15% of species cannot stand

mistreatment (

tmiss). A species may be intolerant to

all types of stress, just to one or more types of stress.

11.94% of species are tolerant to all four types of

tolerance, 35.07% tolerate at least three types, just

over half (55.22%) tolerate at least two types of

tolerance and 7.5% of species are intolerant. Of the

species, native to Mexico, 64 tolerate frost, 33

withstand frost, 21 are tolerant to salinity and 20

tolerate mistreatment.

Table 1: Tolerance to pollution for 134 trees.

Three Pollution

Levels/ Four

Modalities

Mean

Pollution

High

Pollution

Very high

Pollution

Sensible = 1 4 33 95

Tolerant = 2 47 49 24

Resistent = 3 76 52 15

Resilient = 4 7 0 0

134 134 134

Each species is recommended for one, two or at

most seven planting sites. All are suitable for

recreational forests, 97.01% are recommended for

parks and gardens (

s_urbrp), 89.55% and 86.57%

are proposed, respectively, for sports fields

(

sport_f) and cemeteries (s_cem) and 78.36% are

suggested for parking lots (s_parlot). 54.48% are

considered suitable to be planted under energized

cables (

s_beleclin) and 52.99% are not suitable to

be planted in streets and or ridges (

s_street). Of

course, some species are characterized by their

versatility in terms of plantation site. 79.85% can be

planted on at least 5 of the 7 sites, 67.16% on at least

6 of the 7 sites and 19.4% are proposed for any of the

7 sites. In relation to the sensitivity, tolerance,

resistance and resilience of the species at different

levels of air pollution; original data showed 42% of

species with missing modalities (Vazquez, 2014).

Table 1 presents, after imputation, the frequency

distribution of tolerance to different levels of

pollution: mean pollution, high pollution, very high

pollution.

3.2 Multiple Correspondence Analysis

The MCA is carried out, considering the following

active variables:

tree, shrub, palm, fruit,

evergreen, tdry, tcold, tsalt, tmiss,

street, s_urbrp, s_beleclin, s_cem, s_parlot,

sport_f, Very High Pollution, High

Pollution and Mean Pollution. This represents

66.65% of the total inertia in three components

(33.41% in the first, 20.89% in the second and

12.35% in the third). No gains of more than 1% are

observed after removing variables with low

frequency. Figure 1 presents the projection on the two

first components (54.3%) of the 134 species. In this

projection 9 groups of species are distinguished.

Figure 1: Projection on two first axes with 54.3% of total

inertia and the clusters.

3.3 Cluster Generation

Cluster Analysis is applied to the coordinates of the

134 species based on the factorial components. The

results with two components (54.30% of the total

inertia) show distinction of clusters (Fig. 1). The

validation tests, using the Dunn and Silhouette

indices, for the hierarchical classification algorithm

with the Ward method suggest between 4 and 11

clusters. However, considering the interest of end

users, the configuration with nine clusters seemed

adequate to identify extreme groups such as the palm

group (cluster 3) and the citrus group (cluster 9).

Each cluster is described in terms of the

modalities of the 18 variables, through three

indicators: Global proportion. the Cla/Mod ratio

and the (Mod/Cla) ratio. Not all differences between

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440

the Cla/Mod ratio and the overall ratio are

significant. For example, in cluster 1, for the modality

"tree", the global proportion is obtained by dividing

97 (species with this modality) by 134 (total number

of species). This results in 79.39% (rounding to two

figures). The Cla/Mod for the "tree" modality is

22.68%. (Fig. 2) is calculated by dividing the number

of times species in the cluster exhibit the "tree"

modality divided by 97 (number of total species with

the "tree" modality). In this example, the difference

between the ratio Cla/Mod = 22.68% and the Global

proportion = 79.39% is significant at 0.05 level of

significance (v.test = 3.55). Therefore, this modality

has a positive correlation with Cluster 1. The

Mod/Cla ratio for the same "tree" modality is

calculated by dividing 22 (the number of times the

species in the cluster exhibit the tree modality) by 22

(the number of species with tree modality in the

cluster). The value of 100%, for this modality,

indicates that the cluster is homogeneous, because all

the species in this cluster are trees.

Figure 2: Mod/Cla and Cla/Mod for cluster 1.

For all modalities with positive correlation, it is

possible to describe cluster 1 with the Mod/Cla ratio:

“all species are trees (100%), there are no shrubs

(100%), fruitless trees (100%). In relation to the site,

no species are recommended for sites under cables

(100%), 95.45% of the species are proposed for

parking lots and 81.82% for sidewalks and ridges.

100% tolerate frost, 95.45% cannot stand salinity and

77.27% cannot withstand drought. 81.82% are

sensitive to high pollution and 13.64% are sensitive

to medium pollution”. For the Cla/Mod ratio, the

description of cluster 1, we have that: “32.84% are

non-shrub species, this cluster includes 22.68% of all

the trees and 18.64% are fruitless species. As far as

the planting site is concerned, 36.07% of all the

species are not recommended for planting on sites

under cables, 25.35% of all the species are proposed

for sidewalks and ridges and 20% of all the species

prescribed for parking. For environmental tolerance,

this group includes 25% of all species that do not

tolerate drought, 23.08% of all species that do not

tolerate salinity and 19.82% of all species that

tolerate frost. Regarding sensitivity to pollution, this

group includes 75% of species sensitive to medium

pollution and 54.55% of species are sensitive to high

pollution”.

As in the previous case, the percentages of species

with a given modality are presented, with respect to

the 134 species and with respect to the species within

the cluster and the test values. Without intending to

be exhaustive, some outstanding features, concerning

the homogeneity (Mod/Cla ratio) of these clusters

are:

• On Cluster 2 (Fig. 3) 12 species the

Mod/Cla ratio show that these species are

adequate for parking lots (100%), none

tolerate drought or abuse. However, 91.67%

of the species are tolerant to medium

pollution and 83,335 to high pollution. 25%

• On Cluster 3 (Fig. 4) 18 species are suitable

for parking lots, sidewalks and ridges;

83.33% are not recommended for sites under

cables. A significant percentage tolerates

drought (83.33%), salinity (61.11%) and

abuse (50%).

• Cluster 4 (Fig. 5) show that relevant

characteristics for the 14 species in this

group are their tolerance to medium

(64.29%) and high (85.71%) pollution. In

relation to all the data almost 25% (24.49%)

tolerate high pollution. 64.29% are not

evergreen species.

• Cluster 5 (Fig. 6) accounts 19 species with

95.74% of trees, evergreen (94.74%).

84.21% of the species in this cluster are

resistant to medium pollution and 68.42% to

high pollution. 21.05% of species are

resistant to medium pollution and 25% of

species resistant to high pollution.

Concerning soil, 73.68% of the species in

this group are drought tolerant and 78.95%

of the species are proposed for sites under

cables.

• On Cluster 6 (Fig. 7)10 species are shrubs,

80% are fruit trees and suitable for places

where there are cables. They are

characterized by their intolerance to salinity

or mistreatment. The 90% do not tolerate

drought. As for pollution, 90% tolerate

medium and high levels of pollution.

• On Cluster 7 (Fig. 8) 13 species in this group

are evergreen and resistant to high levels of

Mexico City’s Urban Trees Reforestation Based on Characteristics of Plantation Sites

441

contamination. 92.31% are resistant to

medium pollution levels. Some are resistant

to very high levels of contamination

(38.46%). A good number are tolerant of

drought (92.31%), salinity (92.31%) and

mistreatment (84.62%) They are not

recommended for cemeteries and recreation

parks.

• On Cluster 8 (Fig. 9) 17 shrub-type species

(94.12%) are not recommended for

sidewalks and ridges (88.24%), but 94.12%

are recommended for sites under cables.

They are resistant to high pollution levels

(70.59%). Some withstand very high

pollution levels (29.41%), and others are

even suitable for medium pollution levels

(17.65%).

• On Cluster 9 (Fig. 10) 9 species of this group

are of the shrub type. 66.67% are fruit trees.

All are recommended for sites under cables;

None is proposed for parking lots, or for

sidewalks and / or ridges. The 77.78% are

not recommended for sports fields. As for

tolerance, 77.78% show intolerance to frost.

Figure 3: Mod/Cla and Cla/Mod for cluster 2.

Figure 4: Mod/Cla and Cla/Mod for cluster 3.

Figure 5: Mod/Cla and Cla/Mod for cluster 4.

Figure 6: Mod/Cla and Cla/Mod for cluster 5.

Figure 7: Mod/Cla and Cla/Mod for cluster 6.

Figure 8: Mod/Cla and Cla/Mod for cluster 7.

KDIR 2023 - 15th International Conference on Knowledge Discovery and Information Retrieval

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Figure 9: Mod/Cla and Cla/Mod for cluster 8.

Figure 10: Mod/Cla and Cla/Mod for cluster 9.

This typology is not definitive since in addition to

considering the importance of integrating other

characteristics, it is necessary to involve one or more

specialists in the process of defining and interpreting

groups. For example, five groups were initially

proposed, but interpretation proved difficult and

confused some key species such as palms and fruit

trees. For methodological purposes, the grouping of

the 134 species into nine clusters makes it possible to

establish a few criteria for their distinction. It is thus

possible, for example, to distinguish the group

(cluster 1) of species characterized by trees, proposed

for sidewalks, ridges and parking lots, tolerant to

drought, but sensitive to high pollution, from the

group (cluster 7) of species tolerant to frost, salinity

and abuse, and resistant to high levels of

contamination.

4 CONCLUSIONS

The typology presented, with 9 clusters, is not

definitive, but it sets the basis to assign trees’ species

to different planting sites characterized by modalities

such as levels of tolerance to mistreatment, water

scarcity, tolerance to different levels of contamination

of each species. Multiple Correspondence Analysis

was adequate for exploring categorical data and

assessing the significance of missing modalities.

Through coordinates, modalities and individuals

(species) in the axes, it was possible to detect and

impute missing values without altering the structure

of the data. In this way the MCA turned out to be

robust to estimate absentees.

The description of each cluster in terms of Global

proportion, Cla/Mod ratio, Mod/Cla ratio, although

difficult to describe them at the beginning, their use

resulted more useful and straightforward, compared

to the use of association rules.

In a subsequent project, it seems desirable to

integrate new features. However, manual integration

would be time consuming, also leaving open the

possibility of making various mistakes, since the

information is scattered in different texts and few

experts show willingness for this activity. To embrace

more features, it is proposed to integrate an automatic

text extraction procedure and thus reduce the

possibility to capture and to transform information

into compatible formats.

ACKNOWLEDGEMENTS

Héctor Javier Vázquez acknowledges the

Universidad Autónoma Metropolitana-Unidad

Azcapotzalco and the Mexican National Council for

Humanities, Science and Technology (CONAHCYT)

for the Grant (Proposal No. 208133-2013,

Multidisciplinary (Area 8). He also wishes to

acknowledge Professor Nathalie Leborgne-Castel,

Professor Dirk Redecker, Professor Daniel Wipf and

their entire teaching team of the Master program

Integrative Biology of Plant-Microorganism-

Environment Interactions at Burgundy University for

the opportunity, they gave him, to immerse in the

field of Plant and Tree Biology.

Finally, he would like to offer his special thanks

to Professor José Alejandro Reyes Ortíz for his

support and encouragement.

Authors acknowledge retired Professor Alejandro

Aldama for his remarks and advice for improving

English writing.

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