instituto tecnológico y de estudios superiores de - LabSIG

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INSTITUTO TECNOLÓGICO Y DE
ESTUDIOS SUPERIORES DE MONTERREY
CAMPUS MONTERREY
DIVISIÓN DE INGENIERÍA Y ARQUITECTURA
PROGRAMA DE GRADUADOS EN INGENIERÍA
URBAN HEAT ISLANDS IN MONTERREY, MEXICO
USING REMOTE SENSING IMAGERY AND GEOGRAPHIC
INFORMATION SYSTEMS ANALYSIS
THESIS
PRESENTED AS PARTIAL FULLFILLMENT OF THE REQUIREMENTS FOR
THE DEGREE OF
MASTER OF SCIENCE
IN
ENVIRONMENTAL SYSTEMS
ANA LUCRECIA RIVERA RIVERA
MONTERREY, N.L
JUNE 2012
Instituto Tecnológico y de Estudios Superiores de Monterrey
Campus Monterrey
División de Ingeniería y Arquitectura
Programa de Graduados en Ingeniería
The members of the thesis committee recommended the acceptance of the thesis of Ana
Lucrecia Rivera Rivera as a partial fulﬁllment of the requirements for the degree of
Master of Science in Environmental Systems.
Thesis Committee:
Diego Fabián Lozano García
Advisor
Rena Porsen Overgaard, Ph.D.
Synodal
Sandrine Marie Denise Molinard Babin
Synodal
Mario Guadalupe Francisco Manzano Camarillo, Ph.D.
Director of the Program of Master of Science in Environmental Systems
June 2012
DEDICATORIA
Con cariño para mi familia:
A mis padres por estar conmigo y creer en las metas establecidas; por haberme guiado
sabiamente hacía el camino de la educación; a mis hermanas por aguantarme; a Rodolfo,
por haber sido tío y hermano.
A Ricardo, en quien deposito mis sueños, esperanzas y futuro.
A la memoria de Concepción Rivera,
que siempre estará conmigo, en todo momento.
A mis perros, en especial a mi “Gober Precioso”
por lo largos paseos y desviarme de mis preocupaciones del día.
Dios mío:
Me respondiste cada vez que te invoqué y aumentaste la fuerza de mi alma. Por ello te
doy gracias de todo corazón por las bendiciones recibidas, Por el conocimiento que
viene de ti y encierra una incalculable riqueza. Que no sea arrogante por ello.
Dame humildad para compartir mis conocimientos. Recuérdame diariamente la
obligación que tengo de ser útil a los demás. Dame valentía y constancia para ayudar a
quienes más lo necesitan. Y que todo sea para mayor gloria tuya.
Así sea.
AGRADECIMIENTOS
Al Dr. Fabián Lozano por haberme dado la oportunidad y proporcionado los recursos
financieros para realizar mis estudios de maestría. Pero sobretodo quisiera agradecerle
de manera muy especial por amigo perruno que puso a mi cargo y cuidado. A todos los
profesores del programa (Martín Bremer, Mario Manzano, Nelly Correa, Ernesto
Enkerlin) por sus conocimientos compartidos.
Agradezco mucho al staff de Labsig, especialmente a Patricia Vela y Fabiola Yépez por
las mañanas de café y largas charlas compartiendo puntos de vista.
A mi comité de tesis, Sandrine y Rena, mujeres y profesionistas que admiro.
A las chicas del Centro de Calidad Ambiental, por su apoyo administrativo pero sobre
todo por su amistad: Perla, Claudia, Stephanie, Erika, Karla y a Miriam.
A Diana Salomón por las valiosas tardes de pláticas des estresantes, en las que hacíamos
y deshacíamos el mundo.
A Amanda Castillo por su amistad, que me ha acompañado literalmente desde el primer
día de mis estudios profesionales.
A Lora Head por sus enseñanzas académicas pero también de vida. El trabajo de un
profesor va más allá del salón de clases.
A Magdalena y Ricardo Neri V. por su hospitalidad.
Al ITESM y al CONACYT por el apoyo económico.
Urban Heat Islands in Monterrey, México
Using Remote Sensing Imagery and Geographic Information
Systems Analysis
Ana Lucrecia Rivera Rivera
The lack of urban planning causes Heat Island formation and, because of this, it is
important to analyze the current situation in order to be able to delineate better
environmental parameters to achieve urban sustainable development, reducing the
negative effects of uncontrolled urban growth, which will allow better living ways.
The uncontrolled urban expansion of the Metropolitan Area of Monterrey produces
an environmental degradation. Traditional types of construction materials, air
conditioners, industrial activities, and the lack of greens areas rise the temperature. The
phenomenon is known as Urban Heat Island (UHI), and causes health problems,
excessive use of resources, such as water and energy. Inhabitants of the Metropolitan
Area of Monterrey (MAM) started to suffer the negative consequences of the accelerated
unplanned city grow, which comes with an environmental degradation of land surface
and deforestation among other consequences, like the alteration of natural hydrologic
flows, as a result of these changes.
This research analyzes the relationship between land surface temperature and land
use -land cover, in the MAM using Remote Sensing Imagery. Social characteristics of the
population were included to learn if there is a relationship between social stratum and
the effect of heat islands, using Geographical Information Systems. The results provide
valuable information to design better guidelines for sustainable urban growth. Areas of
heat stress were identified. Spatial relationships between land use, land cover and
temperature are relevant. Images show not only the distribution and intensity of UHI
but also give a more descriptive knowledge about the inhabitants suffering from heat
stress.
Such analysis will give a basic knowledge of climate behavior of the city and aims to
help planning authorities to take better future decisions and could contribute to an
improved use of natural resources, for urban development, and to consider the
importance of green areas. It is urgent to elaborate sustainable territorial development
plans which seek environmental protection, less harmful human practices, and improve
to living standards for the population. The analysis of climate conditions is extremely
necessary to take strong planning decisions and formulate design guidelines; every
place is unique and should have its own statements. It is also necessary to consider that
cities are not independent regions, but that they are inside an ecosystem, so their
environmental problems have a relation on a bigger scale, such as global warming.
Contents
List of Tables...................................................................................................................... viii
List of Figures .................................................................................................................... ix
Chapter 1
Introduction ................................................................................................. 1
Chapter 2 Literature Review ........................................................................................ 2
2.1 Urban Growth ....................................................................................................... 2
2.2 Territorial Planning ............................................................................................. 3
2.3 Climate Knowledge ............................................................................................... 4
2.4 Heat Islands .......................................................................................................... 5
2.4.1 Definition .................................................................................................. 5
2.4.2 Classification ................................................................................................. 6
2.4.3 Causes ............................................................................................................ 7
2.4.4 Effects ............................................................................................................ 8
2.4.5 Geometry over Heat Islands ....................................................................... 9
2.5 Similar Studies ...................................................................................................... 12
Chapter 3 Purpose .......................................................................................................... 14
3.1 Main Purpose ........................................................................................................ 14
3.2 Research Goals ...................................................................................................... 14
3.2.1 Main...................................................................................................................... 14
3.2.2 Specific ................................................................................................................ 14
3.3 Research Questions ............................................................................................... 15
Chapter 4 Methods......................................................................................................... 16
4.1 Urban Heat Islands................................................................................................ 16
4.2 Climatic Analysis ................................................................................................... 18
4.3 Land Use / Land Cover ........................................................................................ 18
4.4 Social Composition................................................................................................ 19
vi
Chapter 5 Results ........................................................................................................... 23
5.1 Urban Heat Islands................................................................................................ 23
5.2 Climatic Analysis ................................................................................................... 30
5.3 Land Use / Land Cover ........................................................................................ 37
5.4 Social Composition................................................................................................ 43
5.3 Spatial Analysis ..................................................................................................... 53
Chapter 6 Discussion..................................................................................................... 59
Chapter 7 Mitigation Strategies ................................................................................... 62
Chapter 8 Conclusions .................................................................................................. 68
References .......................................................................................................................... 69
Vita ...................................................................................................................................... 73
vii
List of Tables
Table 1. Total Population and its relation with municipalities. ................................. 2
Table 2. LST Statistics from satellite images (°C) for Ho Chi Minh City. .................. 12
Table 3. Unit Conversion Coefficients ........................................................................... 16
Table 4. ASTER thermal bands ....................................................................................... 17
Table 5. Land Cover Classification Images ................................................................... 18
Table 6. Variables to calculate urban deprivation index 2005 .................................... 19
Table 7. Synthesis of Variables taken into consideration ........................................... 19
Table 8. ERDAS Statistics for May 15, 2003 ................................................................... 23
Table 9 . ERDAS Statistics for May 07, 2009 ................................................................... 24
Table 10. ERDAS Statistics for May 13, 2011 .................................................................. 25
Table 11. Statistics Comparison ...................................................................................... 26
Table 12. Climatic Conditions for analyzed days .......................................................... 35
Table 13. Climatic Conditions for analyzed months .................................................... 36
Table 14.,Land use M2 pre Municipality ........................................................................ 37
Table 15. Summary of Absence of Green Area .............................................................. 39
Table 16. Analysis of green area available per inhabitant ............................................ 39
Table 17. Synthesis of variables taken into consideration ............................................ 43
Table 18. AGEBs above average per Index ..................................................................... 51
Table 19. AGEBs with Low Well Being Index per municipality ................................. 51
Table 20. Reclassification for Land use Correlation analysis ....................................... 53
Table 21. Reclassification for Land cover Correlation analysis .................................. 54
Table 22. Percentage of precarious AGEBs per municipality and Green Area ......... 58
Table 23. Green area (M2) Deficit for population in the MAM ................................... 58
Table 24. List of Tracts (Railroad and Riverbed) to Propose the Master Plan .......... 65
viii
List of Figures
Figure 1. Urban Heat Island Characteristics ................................................................. 5
Figure 2. Types of Heat Islands........................................................................................ 6
Figure 3. Surface temperature of materials exposed in a day...................................... 7
Figure 4. Outdoor and indoor surface temperatures .................................................... 8
Figure 5. Schematic distribution of impinging solar radiation.................................... 10
Figure 6. Land Surface Temperature Results for Ho Chi Minh City .......................... 12
Figure 7. Brightness distribution temperature in Lanzhou, 1986................................ 13
Figure 8. Brightness distribution temperature in Lanzhou, 2002................................ 13
Figure 9. Methodology Process Diagram ....................................................................... 22
Figure 10. Histogram for May 15, 2003 ........................................................................... 23
Figure 13. UHI and neighborhoods for May 15, 2003 ................................................... 27
Figure 14. UHI and neighborhoods for May 07, 2009 .................................................. 28
Figure 15. UHI and neighborhoods for may 13, 2011 ................................................... 29
Figure 16. Isotherms Map ................................................................................................. 31
Figure 17. Isohyet Map ...................................................................................................... 32
Figure 18. Dominant winds direction for the MAM .................................................... 33
Figure 19. Solar Radiation Diagram ................................................................................ 34
Figure 20. Temperature Measurements for May ........................................................... 35
Figure 21. Land use M2 per Municipality ...................................................................... 37
Figure 22. Land use distribution ...................................................................................... 38
Figure 23. Distribution of Public Green Space ............................................................... 40
Figure 24. Land Cover Map .............................................................................................. 42
Figure 25. Population Density Map................................................................................. 44
Figure 26. Percentage of population 5 to 14 not attending school .............................. 45
Figure 27. Percentage of adult illiterate ......................................................................... 46
Figure 28. Percentage of population without health services ...................................... 47
Figure 29. Percentage of population without piped water .......................................... 48
Figure 30. Percentage of population without sewage systems.................................... 49
Figure 31. Percentage of houses without refrigerator ................................................... 50
Figure 32. Low Well Being AGEBs .................................................................................. 52
Figure 33. Temperature subtraction 2009 minus 2003 .................................................. 55
Figure 34. Temperature 2009 and Low Well Being ...................................................... 56
Figure 35. Environmental Justice Map ............................................................................ 57
Figure 36. Current state of train tracts in the MAM ...................................................... 65
Figure 37. Master plan proposal for public green areas ............................................... 67
ix
Chapter
1
Introduction
Urban Heat Islands (UHI) are defined as the rise overtime of temperature in specific
areas (EPA, Desarrollo Inteligente e Islas Urbanas de Calor, 2010). They have been the
result of unplanned city growth, and the lack of environmental guidelines. In an urban
development, the asphalt and concrete replace the natural land; the hardscape replaces
the landscape; fluvial sewages replace the natural water flows, causing floods because of
the lack of areas for water absorption (Hough, 1998, p. 39). To solve this phenomenon, a
territorial plan should give the basis to create guidelines to build a better city, reducing
environmental damage, but also seeking a better living standard for inhabitants
(Higueras, 2007, pág. 16).
Scientists have analyzed historic registers of 7,200 meteorological stations to find
evidence which could show that temperature near land surface has been increasing, and
found that most of the green house effect gases, which contribute to climate change, are
produced in urban areas (Hansen, 2001). As urbanization increases, the amount of these
gases increases too. It has been said that CO2, increases 4% every 10 years, which raises
Earth‟s temperature (Ortiz, 2010). Main studies about Urban Heat Island defined that
warm air, containing several contaminants, stayed trapped near urban surface. With the
combination of H2O, these contaminants react and cause acid rain, with a pH of 5.6, due
to the strong presence of CO2. Also, contaminants can be carried away to other regions
by rivers, clouds, winds, or underground water, having a negative impact, even from a
long distance. (Ortiz, 2010). Cities should be analyzed as an ecosystem and to
understand their relation with nature. Urban climate should be seen from a higher
perspective, beyond regional limits. Global wind patterns, atmosphere, oceans, and
human activities connect cities around the world (Hough, 1998).
The development of new technologies, such as remote sensing increased possibilities
to collect multispectral, multi resolution, multi temporal and multi spatial data. Now, it
is possible to create a detailed analysis of what is happening in the city (Rose & Devedas,
2009). It is also possible to acquire historic information for land surface temperature, and
be able to document climate changes over the last decades (Hansen, 2001).
This thesis aims to classify areas, infrastructure, and their relationship with social
strata. As a result, we identified areas with thermal stress and their correlation with
socioeconomic composition. Thus, it is possible to analyze environmental justice, which
refers to the degree of suffering because of environmental damage for lower income
population (Amusquibar, 2006). The study UHI of the Metropolitan Area of Monterrrey
(MAM) will stay a basic knowledge of climate behavior over city. This study intends to
help planning authorities to take better decisions that could contribute to sustainable use
of natural resources, for urban development, and to consider the importance of green
areas. Bioclimatic Urban Planning is a term used to define an adequate urban plan,
taking into consideration climate and territorial conditions, for a specific geographic
area. And so, she describes: “To each place, one plan” (Higueras, 2007, p. 15 ).
1
Chapter
2
Literature Review
2.1 Urban Growth
Cities occupy 2% of the total global surface area, but they use 65% of its natural
resources (Girardet, 1992). Latin America is characterized by the large number of
unplanned cities. According to the United Nations (2001), during the last three decades,
the urban population in Latin American cities has increased 240%. They also stated that
the urban rate of the region was of 76% for 1995, and it is expected to be 85% by 2025
(Sanchez, 2002, pág. 321).
In the MAM the population has increased by almost 10 times in the last 50 years. The
city growth came about with almost no planning at all. Now, the inhabitants of the
MAM have a low quality of life due to the traffic, the lack of infrastructure, and green
areas, as a negative consequence of an accelerated unplanned city growth. City growth
comes with environmental degradation of land surface and deforestation. Table 1 shows
the total population for the State of Nuevo León and the municipalities that make up the
Metropolitan Area of Monterrey. The table shows that the municipalities of Monterrey,
San Nicolás, and San Pedro had a decrease in population. On the contrary, Santa
Catarina, Apodaca, Escobedo, Juárez and García, showed an increase. (ITESM, 2008)
Table 1. Total Population of the MAM and its relation with municipalities.
1950
1960
1970
1980
1990
1995
2000
2005
Nuevo León
740,191
1,078,848
1,694,689
2,513,044
3,098,736
3,550,114
3,834,141
4,199,292
MAM
389,629
723,739
1,254,691
2,011,936
2,573,527
2,998,081
3,243,466
3,598,597
52.6
4,915
67.1
6,259
74.0
18,564
80.1
37,181
83.1
115,913
84.5
219,153
84.6
283,497
85.7
418,784
% of MAM
1.3
0.9
1.5
1.8
4.5
7.3
8.7
11.6
Escobedo
% of MAM
2,066
0.5
1,824
0.3
10,515
0.8
37,756
1.9
98,147
3.8
176,869
5.9
233,457
7.2
299,364
8.3
García
4,769
1.2
4,019
0.6
6,477
0.5
10,434
0.5
13,164
0.5
23,981
0.8
28,974
0.9
51,658
1.4
% of MAM
Juárez
% of MAM
12,610
3.2
2,839
0.7
38,233
5.3
3,166
0.4
159,930
12.7
5,656
0.5
370,908
18.4
13,490
0.7
535,560
20.8
28,014
1.1
618,933
20.7
50,009
1.7
670,162
20.7
66,497
2
691,931
19.2
144,380
4.0
Monterrey
% of MAM
339,282
87.1
601,058
83.1
858,107
68.4
1,090.01
54.2
1,069,238
41.5
1,088,143
36.4
1,110,997
34.2
1,133,814
31.5
San Nicolás
10,543
41,243
113,074
280,696
436,603
487,924
496,878
476,761
% of MAM
1.3
2.1
3.7
4.1
4.4
4
3.9
13.2
5,228
14,943
45,983
81,974
113,040
120,913
125,978
122,009
1.3
2.1
3.7
4.1
4.4
4
3.9
3.4
7377
12,895
36,385
89,488
163,848
202,156
227,026
259,896
1.9
1.8
2.9
4.4
6.4
6.8
7
7.2
% of NL
Apodaca
% of MAM
Guadalupe
San Pedro
% of MAM
SantaCatarina
% of MAM
Source: Instituto Nacional de Estadística, Geografía e Informática (INEGI). Made by CESADE y CEDEM, published in
Análisis Estratégico del Área Metropolitana de Monterrey (2002).
2
2.2 Territorial Planning
Territorial planning should be the result of an integrated analysis of social and
physical characteristics of a place during a specific time, to minimize negative
consequences produced by human activities on the environment (Higueras, 2007):
“The object of territorial planning is to consider, during all
the process, the particular properties of each environment,
society and climate, so the arrangement proposal could be
in equilibrium with it surrounding, and that looks forward
for sustainable development.” (Higueras, 2007, p. 175)
To develop an optimum territorial plan it is necessary to know the physical
environment and its climate. Ester Higueras (2007), proposed a method to accomplish it,
as and it is shown in the following graphic (Higueras, 2007, p. 73).
1. Environmental Knowledge
Geomorphology: slopes.
Water Bodies: superficial and underground
Subsoil: capacity, permeability
Vegetation: species, qualities
Solar Incidence: solar movement;
summer and winter situations
Wind: velocity and direction
2. Climate Knowledge
Bioclimatic Climate Chart
Local needs during summer and winter
3. Environmental Planning with Bioclimatic
1. Territorial Zoning
a. Land classification: Urban, protected, etc
b. Land use: Residential, industrial
2. Urban General Systems
3. Environmental ordinance : Good land use,
aesthetics, hygiene
ENVIRONMENTAL
SYNTHESIS
NATURAL POTENTIAL OF
THE TERRITORY
STRATEGIES FOR
SUN
WIND
HUMIDITY
GREEN ZONES
INFRASTRUCTURE
3
2.3 Climate Knowledge
To study urban microclimate, E. Higueras suggests an analysis on the following
points:



Heat Islands: This occurs when the temperature of an area is higher than its
surroundings.
Wind Pattern: Refers to the un-natural changes on wind patterns due to the
morphology of buildings: turbulence or gusts.
Moisture: Altered by the change of natural water runoffs.
“The result for climate analysis is an isothermal map, which evaluates the presence
of Urban Heat Islands. In addition, there is an integrated map considering wind patterns
and water vapor also known as a Climate Chart, which locates thermal comfort zones”
(Higueras, 2007, p. 120).
The method to elaborate environmental plans, gives the basis to achieve territorial
planning with sustainable guidelines. The goals to be achieved, by any territorial plan
should be: 1) Economic Development; 2) Improvement of living standards; 3)
Responsible use of natural resources and environmental protection; 4) Rational use of
space (Higueras, 2007).
It is urgent to elaborate sustainable territorial development plans which seek
environmental protection, less harmful human practices, and improve to living
standards for the population. The analysis of climate conditions is extremely necessary
to take strong planning decisions and formulate design guidelines; every place is unique
and should have its own statements. It is also necessary to consider that cities are not
independent regions, but that they are inside an ecosystem, so their environmental
problems have a relation on a bigger scale, such as global warming.
4
2.4 Heat Islands
2.4.1 Definition
An Urban Heat Island is an air layer over a city or any developed area, with a higher
temperature than its surroundings (EPA, 2010). “The isotherms, or lines of equal
temperature, form a pattern that resembles an “island” loosely following the shape of
the urbanized region, surrounded by cooler areas” (Voogt, 2008). Figure 1 shows a plan
view of the island pattern formed by the isotherms. The strongest temperature is
recorded on the nucleus of the city, and degrades towards the suburban zones, and then
to rural areas. Its cross section is drawn as a dome, with warmer air transported
downwind of the city (Voogt, 2008).In other words, a warm air layer stays trapped
under a cool air layer, and because of this, dust and heat stay near the urban surface and
its population (Salvador, 2003, p. 113). This can be in status quo until wind or rain
disperses it. Therefore, cities act as a thermal storage, produced by human activities. It is
proven that Urban Heat Islands are proportional in size to the amount of people living
in the city (Oke, 2006).
Figure 1. Urban Heat Island Characteristics. Plan view of spatial patterns of air temperature.
Source: James Voogt. 2008.
To measure the intensity of an island, a study made by the Universidad de Chile,
proposes the equation:
where
is the maximum
temperature in an urban zone and
is the maximum temperature on a rural zone
(Romero & Banzhaf, 2009).
5
2.4.2 Classification
A research on Urban Heat Islands and land cover using thermal remote sensing have
classified 3 types of Heat Islands (Voogt, 2008) (Figure 2):

Canopy Layer Heat Island (CLHI): the air layer closest to the city surface, and
extends upwards above to the mean building height. The heat island intensity
increases with time from sunset to a maximum between few hours after sunset
and predawn hours. During the day the CLHI intensity is typically fairly weak or
sometimes negative (a cool island) in some parts of the city where there is
extensive shading by tall buildings or other structures.

Boundary Layer Heat Island (BLHI): the layer that lies over the canopy layers
and may be of 1 km or more in thickness during the day, and shrinks to
hundreds of meters or less at night.

Surface Heat Island (SHI): Forms a warm air dome that extends downwind far
from the city. Wind often changes the dome to a plume shape. Daytime SHI is
usually largest because solar radiation affects surface temperatures.
SHI
BLHI
CLHI
RURAL AREA
URBAN AREA
RURAL AREA
Figure 2. Represents the 3 types of Heat Islands described by Voogt. Graphic without scale.
6
2.4.3 Causes
Heat Islands are produced by artificial and natural causes. Some of the natural causes
are: wind, cloudiness, precipitation, topography, atmospheric pressure, radiation,
moisture. For example, if wind and cloudiness increase, heat islands decrease. Among
artificial causes are building dimensions, construction materials like asphalt, concrete
and glass, which absorb a great amount of thermal heat during the day and radiate it
during the night, the amount of green area, heat produced by the burning of fossil fuels,
energy and water used for irrigation (Voogt, 2008). Causes are attributed mainly to 3
factors:
“First, roof surface, like stone, concrete asphalt, storage
Suns‟ thermal energy and irradiates it during the night.
Second, cities consume most of the energy produced;
developed countries consume between 5 and 10 kilowatts
of energy, per person, per day. Vehicles, electro domestics
and lamps radiate heat, and air conditioners cool inside
air, but heat up outside air. Third, cities emit pollutants
and dust, discharged from carbon and petroleum
combustion, act as Greenhouse Gases, which are then
stored in air layers above the cities”. (Girardet, 1992)
Any surface on Earth gains heat from solar radiation (short-wave) and loses heat by
outgoing (long-wave) radiation. The incoming solar radiation, when absorbed by any
„dry‟ surface during the daytime hours is converted into heat and elevates the surface‟s
temperature. The solar energy absorbed by plants‟ leaves and in moist surfaces is partly
converted into latent heat by the process of evaporation and thus results in a smaller
temperature elevation. (Givoni, 1998, p. 266)
For example, asphalt surfaces reach up 51°C when the atmospheric temperature is
37°C (Olgyay, 2002, p. 51). Figure 3 shows the temperature behavior of several materials
exposed, during a day. Hour
C°
Asphalt
Vegetation
Water Surface
Hour
Figure 3. Surface temperature of materials exposed in a day. Source: Michael Meiss, 1979
7
The amount of energy reflected by an outdoor surface depends not only on the type of
surface but also on the color of it. Figure 4 shows the temperature behavior for two
different color surfaces during a day.
Figure 4. Outdoor and indoor surface temperatures of two colored roofs comparison with
outdoor dry bulb temperature (DBT). Source: Baruch Givoni, 1998.
2.4.4 Effects
The World Meteorological Organization stated guidelines and defined seven types
of urban development regions and their effects on a local scale temperature, showing
that centers with high densities have intense Heat Islands (Oke, 2006). While cities grow,
they become warmer and humid during the summers, making them less comfortable for
living. The effects are worse during summer nights, when winds are not as strong to
cool the city temperature. A research about Urban Heat Islands in Valencia, Spain,
showed that there was a static heat island located in the center of the city; a second in the
maritime zone. This last one, against scientific speculations, did not dissipate with sea
winds at noon, because breeze loses velocity 300 meters inside the coastline due to the
presence of buildings, which act as a barrier. “To dissipate heat concentration, wind
speed must be 3-5 m/sec (10.8 - 18 km/hr) for cities with 50,000 inhabitants, 4-7 m/sec
(14.4-25.2 km/hr) for cities of 100,000 inhabitants and 8 m/sec (28.8 km/hr) for cities of
more than 400,000in habitants” (Salvador, 2003, p. 116).
It is important to know wind
patterns for specific seasons and dates. High wind velocity can mitigate the
uncomfortable effects of Heat Islands during the summer, but can be harmful during
winter. Still, it is necessary to consider the geometry of buildings and the amount of
green area because they can form upwind effects and increase wind velocities creating
turbulence, which harms vegetation and wildlife.
8
Children, the elderly and people with pre-existing respiration conditions are most
vulnerable to the negative effects of heat islands. Polluted air worsen conditions; when it
cools down, condenses dust particles, and produces acid rains, which in the long term
causes serious health problems (Girardet, 1992). A raise of 3°C can increase the amount
of organic pollutants and cause irritating gases. These negative effects represent big
medical expenses for the population (Padilla, 1997).
Heat Islands can raise energy demand for air conditioners during the summers,
which emit more heat and by consequence degrades local air quality (Rosenfeld &
Akbari, 1995). Most of this heat is produced in high density centers, where most of the
office buildings, industries or overcrowded housing developments are located, and
demand a greater amount of energy for cooling. It is said that, from 3 to 8% of the
energy demanded for air conditioners in the United Sates, is used to mitigate the effect
of Heat Islands. There has been a rise in global temperature between 1 to 2 °C since the
1950‟s (Hough, 1998, p. 247). It is estimated that, a sixth of the total energy consumed in
the United States is used to cool down buildings, and equals to 40 billion dollars per
year (Guhathakurta & Gober, 2007). In other resource, rise in temperature increase the
demand on water supply. Research done in Phoenix showed that the rise in daily
temperature is directly related with the increase of water use to 290 gallons per family,
which also implies negative effects on economics and rational use (Guhathakurta &
Gober, 2007).
2.4.5 Geometry over Heat Islands
Urban Heat Islands decrease human thermal comfort, which is defined as the ideal
temperature where body feels well enough to make its normal activities. Several
scientists stated that the ideal atmospheric temperature to produce comfort is 19°C
during the summer and 17°C during the winter, with slow wind. Other scientists range
the ideal temperature between 15.6 to 24.4 °C with a relative humidity between 40 –
70%. There is a direct relation between climate elements and human comfort. (Olgyay,
2002)
Geographic conditions create microclimate. One of these conditions is topography,
because temperature decreases at a given altitude by 0.56°C every 100.6 m. during the
summer and 122 m during the winter (Olgyay, 2002, p. 44). “The presence of mountains
or hills in a land surface stops air diffusion and alters the normal temperature
distribution at night” (Olgyay, 2002, p. 44). UHI phenomenon gets worse if the city is
surrounded by mountains or hills (Olgyay, 2002, p. 45).
The amount of solar of radiation an area receives depends on topography. For
example, the amount of solar radiation a down side of a mountain receives depends on
the inclination and orientation of its slopes. Equally, a hill causes an effect on wind and
rain distribution, creating greater wind acceleration at the top and less turbulence below.
At the side of the hill facing wind, gusts push rainfalls downward, perpendicular to the
base, where air movement is slow and irregular. High mountains produce the opposite
effect. At the side of the mountain facing wind, the ascendant air originates a rain
deposit. Compressed warm air descends on the other side absorbing moisture instead of
releasing it (Olgyay, 2002, p. 50).
9
The impact of solar radiation depends on the urban geometry, which is defined by a
ratio named H/W ratio, where H is the height of the buildings and W is the width of the
spacing between them. Ludwing (1970) presents an analysis of the effect of this ration on
the radiation and the air temperature near the ground. Figure 5 illustrates different solar
distribution of radiation.
In a flat area, most of the impinging solar radiation is reflected away
or emitted, after absorption. In a medium density area (H/W ratio
of about 1), much of the reflected radiation strikes other buildings or
the ground and is eventually absorbed at and near the ground level.
In the high-density area, (H/W ratio of about 4 or more), most of
the absorption takes place high above the ground level.
Consequently, the amount of radiation reaching the ground, and
heating the air near the ground, is smaller than in the case of
medium density (Givoni, 1998, p. 247).
a)
b)
c)
Figure 5. Schematic distribution of impinging solar radiation in a) Open – flat country; b)
Built up area with H/W of about 1, and c) High-density urban area with H/W ratio of
about 4. Source: Givoni, 1998.
10
This effect is also known by the term “Urban Canyon” named by Oke (1981. The
study was made for Vancouver, which has an H/W ratio of 0.9. It was found that about
60 % of the heat was transferred as sensible heat to the air contained in the volume of the
canyon, about 30% was stored in the canyon materials (to be release during the night),
and about 10% was consumed by evaporation from the canyon surfaces. (Givoni, 1998,
p. 247).
The presence of water bodies moderates extreme temperatures. They raise the
minimum temperatures during the winter and decrease maximum during the summer.
Evaporation reduces the dry effect, which is important for regions where slow wind
does not diminish the uncomfortable sense produced by high temperatures. Vegetation
tends to decrease temperature, because it absorbs a great amount of radiation. Also,
vegetation in higher lands creates shaded areas, which are 3°C less than sun exposed
surfaces. Commonly used surface materials in the cities tend to raise temperatures,
because most of them absorb thermal heat (Olgyay, 2002, p. 51).
11
2.5 Similar Studies
2.5.1 Application of Thermal Remote Sensing in Study of Surface Temperature
Distribution of Ho Chi Minh City (Van, Trung, & Lan, Octubre 2009)
This analysis shows the results of research into a methodology to determine the
surface temperature of urban areas in Ho Chi Minh City. The experiment was carried
out on Landsat an Aster satellite images, which are suitable for studies on heat processes
in urban areas. The results showed that the average bias of Land Surface Temperature
(LST) calculation is about 2°C compared with the in situ measurements.
a) LANDSAT 13-02-2002
b) ASTER 25-12-2006
Figure 6. Land Surface Temperature Results for Ho Chi Minh City.
Table 2. LST Statistics from satellite images (°C) for Ho Chi Minh City.
SATELLITE IMAGE
Landsat data in 13 Feb. 2002
Aster data in 25 Dic. 2006
MIN
23.20
17.40
MAX
45.90
49.40
MEAN ST DEV
31.0
2.40
33.30
2.80
12
2.5.2 Study on Spatial Thermal Environment in Lanzhou City Based on Remote
Sensing and GIS (Wangnaiang, 2006)
The research concerns urban spatial thermal environment, the changes over the
spatial structure, and how urban planning should favor sustainable urban development
and improve the quality of human habitation environment. The methodology starts with
the thermal map generation. The surface temperature was obtained by calculating the
radiation value, from data acquired from Landsat TM thermal data. After a
normalization process, the radiant temperature of the land was divided into 5 levels.
Figure 7. Brightness distribution temperature in Lanzhou, 1986
Figure 8. Brightness distribution temperature in Lanzhou, 2002
13
Chapter
3
Purpose of Research
3.1 Main Purpose
The purpose of this study is to learn about the relationship between Urban Heat Islands
formed over the Metropolitan Area of Monterrey and land use/land cover and social
strata
3.2 Research Goals
The goals of this study are:
3.2.1 Main
Analyze Urban Heat Islands formed over the Metropolitan Area of Monterrey, and its
relationship with land use/land cover, and social strata to determine the degree of
Environmental Justice.
3.2.2 Specific
Analyze the MAM in terms of:

Climate: Precipitation: Temperature, Solar Radiation, Wind, Precipitation

Urban Environment: Land Cover, Land Use

Social Composition: Accessibility to green spaces, general well-being of
individuals
Characterize the behavior of Urban Heat Island based on a historical analysis.
Propose mitigation strategies.
14
3.3 Research Questions
The next questions are established as a guide to answer the problem and to achieve the
proposed goals:

Where are the UHI located in the Metropolitan Area of Monterrey?

What are the physical characteristics of such places?

What is the relation between urban expansion and UHI frequency?

What is the land cover of the MAM?

What is the relation between land cover and UHI?

What is the relation between land use and UHI?

Which land cover radiates most of the thermal heat?

What are the socio-economic characteristics of the population where UHI are
located?

How have UHI changed over time?

How do UHI behave during the present day?

What are possible actions to reduce UHI formations?
15
Chapter
4
Methods
4.1 Urban Heat Islands
The historical analyses of the distribution of temperature over the study area lead to
the quantification of thermal conditions. The first image used was an ASTER image of
May 15, 2003 with a Scene Center Scan Time at 17:28:13.1 The second image was from
LANDSAT TM of May 07, 2009 with a Scene Center Scan Time at 16: 57:28. The last
image was dated for May 13, 2011 with a Scene Center Scan Time at 16:59:57. It is
important to consider excessive cloudiness periods for May 2010, and due to this
situation imagery of this year was not processed.
Pre Process
To obtain UHI, basic preprocess was done. Aster image was obtained in 1B level,
where the radiometric calibration and geometric resampling were already carried out.
All ASTER thermal bands were resample at 90 m, by the Nearest Neighbor algorithm.
LANDSAT TM images have 1 thermal infrared band and were re sample at 120-m. All
images were georeferenced to Universal Transverse Mercator projection: UTM Zone 14.
ASTER:
1. Calculate DN to spectral radiance.
Equation 1 shows the conversion of DN to spectral radiance for the ASTER image.
Eq 1
Where, Lrad, j is ASTER spectral radiance at the sensor‟s aperture measured in a
wavelength j; j is the ASTER band number; DNj is the unitless DN values for an
individual band j; UCCj is the Unit Conversion Coefficient (W m-2 sr-1 µm-1) from ASTER
Users Handbook .
Table 3. Unit Conversion Coefficient (W m-2 sr-1 µm-1)
BAND #
10
11
12
13
14
NORMAL GAIN
0.006822
0.006780
0.006590
0.005693
0.005225
Source: Abduwasit Ghulam in “Calculate reflectance and temperature using ASTER data from ASTER Users
Handbook. September, 2009.
1
ASTER IMAGERY is not longer available for a recent period of time so instead LANDSAT TM imagery will be used.
16
2. Calculate Spectral Radiance to brightness temperature
Let K1 = C1/λ5 , and K2 = C2/λ, and satellite measured radiant intensity B λ (T) = L λ,
Eq. 2
Therefore, K1 and K2 become a coefficient determined by effective wavelength of a
satellite sensor. The next table shows coefficients for each thermal band. The method
may be extended to the rest of the ASTER thermal bands. (Equation 2)
Table 4. ASTER thermal bands
BANDS BANDPASS EFFECTIVE
(µM)
WAVELENGTH
(µM)
10
8.125-8.475
8.291
11
8.475-8.825
8.634
12
8.925-9.275
9.075
13
10.25-10.95
10.657
14
10.95-11.65
11.318
UCC
0.006882
0.006780
0.006590
0.005693
0.005225
K1
(W M-2 µM -1)
K2 (K)
3040.136402
2482.375199
1935.060183
866.468575
641.326517
1735.337945
1666.398761
1585.420044
1350.069147
1271.221673
Source: Abduwasit Ghulam in “Calculate reflectance and temperature using ASTER data from referenced ASTER L1B
Manual Ver.3. September, 2009
3. Calculate Units of Temperature Kelvin to Celsius
Eq. 3
LANDSAT TM:
1. Calculate DN to spectral radiance (L).
Eq. 4
Where RTM6 is the Spectral Radiance (mW·cm-2sr-1), DN the grey level, LMIN is
Spectral radiance of DN value 1 and LMAX Spectral radiance of DN value 255. LMIN
and LMAX need to be changed for each thermal scene.
2. Conversion of Spectral Radiance to Temperature in Kelvin
Use Equation 2. Where T is Surface Temperature, K1 is Calibration Constant 1 (607.76),
K2 is Calibration Constant 2 (1260.56)
3. Calculate Units of Temperature Kelvin to Celsius
Use Equation 3.
17
4.2 Climatic Analysis
Climatic Evaluations of a region can help to give a better description of urban
microclimate, and takes into consideration the next points (Olgyay, 2002):
1)
2)
3)
4)
5)
Thermal Evaluation: Includes the daily temperature.
Solar: Indicates the daylight hours and specifies if there were cloudy or clear days.
Wind Patterns: Velocity and direction
Precipitation: Quantity (mm)
Humidity: The percentages are specified.
The conditions that were taken into consideration are: Temperature (max & min),
Precipitation (mm), Wind Patterns, and Solar Radiation Temperature was first described
by the Isotherms, according to data provided by Labsig extracted from INEGI. The
Isohyet map helped to determine the driest areas in the MAM. Temperature and rainfall
data was acquired from Comisión Nacional del Agua (CNA) to produce a climograph2 to
identify weather trends for each year. Finally, wind patterns helped to determine
temperature dissipation over the MAM. The final product of this analysis will be a
Climate Characterization. With this information, the conditions of UHI were evaluated.
4.3 Land Use / Land Cover
Remote sensing data was used to perform a Land Cover classification. In addition,
official Land Use shape will be analyzed using Geographical Information Systems (GIS).
Images from SPOT satellite were classified using ERDAS IMAGINE software to obtain
the land cover for the MAM. The classification was done first by using Unsupervised
Classification, then Supervised Classification, with the maximum likelihood algorithm.
The classes will include: 1) Asphalt, 2) Concrete Roofs, 3) Vegetation, 4) Water Bodies
and 5) Barren Land. The main data source for land use was the 2000 cadastral data set,
provided by Centro de Desarrollo Metropolitano (CEDEM). It contains information on
13 land use categories for the MAM. Comparing the surface temperature images and the
land use and land cover classification image with the temperature image proved that the
reduction in green cover for dark colored surfaces, heat generating vehicles and
industries increase the intensity and formation of UHI.
Table 5. Land cover Classification Images
Image
Date
Pixel X
Pixel Y
Center Scan Time
E55822981006182J2A03002
June 06, 2010
10
10
17: 35: 16
E55822991006182J2A00001
June 18, 2010
10
10
17: 35: 25
2
Climograph (Almorox, 2010): A graphic representation of the twelve months in the X axis and in double Y axis monthly
rainfalls (mm) and the median monthly temperature (°C). The area between the curves will determine the duration and
intensity of the dry season.
18
4.4 Social Composition
The census data from INEGI 2005 was interpreted to characterize the social strata of
the study area. Table 6 describes which variables were considered in this study. The
Secretaría General del Consejo Nacional de Población (CONAPO) report of Índices de
Marginación Urbana 2005, the urban deprivation index, measured by Área de
Geoestadística Básica (AGEB), takes into consideration variables listed on Table 6. These
variables are derived from the Mexican Constitution and are described on Table 7.
Table 6. Variables to calculate urban deprivation index 2005
DIMENSION
DESCRIPTION
Education
Percentage of population age 6 to 14 who do not attend school (I1)
Percentage of population age 15 or more without secondary level
completed (I2)
Health
Percentage of population without access to health services (I3)
Percentage of child mortality (I4)
Housing
Percentage of houses without piped water (I5)
Percentage of houses without sewage systems (I6)
Percentage of houses without toilet connected to a sewage system (I7)
Percentage of houses with floors without pavement (I8)
Percentage of houses with a crowding level (I9)
Percentage of houses without a refrigerator (I10)
Assets
Source: CONAPO 2009
Table 7. Synthesis of Variables taken into consideration
INDEX
DESCRIPTION
Education
Health
Housing
Assets
Mexican Constitution declares in its 3rd amendment that Education
is a basic right. Nevertheless, the first desertion made by a low
income family is education.
Mexican Constitution declares in its 4th amendment that access to
public health programs is considered a basic right.
Evaluates the access to main services such as drinkable water,
sewage which helps to prevent diseases and environmental
degradation
Due to the lack of information of amount of income per family, the
lack of refrigerator was taken into consideration. The lack of a
refrigerator is considered to have negative implications on hygiene
because of the low possibility of conserving food.
Source: SEDESOL, SEMARNAT, INE, UNAM. Indicadores para la caracterización y ordenamiento del
territorio. 2004
19
The studies from Secretaría General del Consejo Nacional de Población (CONAPO)
produce demographic indicators that provide insight into the lives of the population
and its distribution in national territory, in order to support the design, implementation
and evaluation of programs for economic and social development and the environment.
Based on the report of Índices de Marginación Urbana 2005 the urban deprivation index
is measured by AGEBS, and takes into consideration the lack of access to education and
health care, residence in poor housing and lack of basic necessities. High deprivation
index population usually sits unevenly on the outskirts of cities, in areas not suitable for
urban development, and faces a number of risks and vulnerabilities that compromise
their quality of life and physical integrity and with negative effects on the environment
(environmental degradation and pollution), which in turn affect the health and safety of
the population (Anzaldo & Prado, 2009). Using some of the variables to calculate
deprivation index and the lack of urban green area it will be possible to establish an
Environmental Justice Map for the MAM.
Population Density
Population Density refers to the number of people inhabiting a given area. Higher
density cities are more sustainable than low density cities. Nevertheless, high density
can also mean overcrowded spaces. In this case there is an excess on the carrying
capacity of the environment.
Education Index
Percentage of population aged 5 to 14 who do not attend school (I1)
Percentage of population aged 15 to 130 who do not know how to read or write (I2)
Health Index
Percentage of population without access to health services ((I1)
20
Housing Index
Percentage of houses without piped water (I5)
Percentage of houses without sewage system (I6)
Assets Index
Percentage of houses without refrigerator (I10)
Well-Being Index
AGEBS with the higher percentage of population and houses without a basic need or
service (Education, Health, Basic Housing Services, and Assets) are considered with a
high deprivation index.
Heat Islands will be characterized using socioeconomic data, climate conditions, and
land use/land cover. Using this information, it will be evident which strata are under
severe heat stress and their conditions. Having a geographical view of the problem it
will be easier to establish more effective Mitigation Strategies for the MAM. Figure 9
shows the methodology followed.
21
Figure 9. Methodology Process Diagram.
22
Chapter
5
Results
5.1 Urban Heat Islands
Date: May 15, 2003
Satellite: ASTER
Projection: UTM, Zone 14
Pixel X Size: 90.000 ; Pixel Y Size: 90.00
Scene Center Scan Time: 17:28:13
Table 8. ERDAS Statistics for May 15, 2003
Statistics
Minimum
Maximum
Mean
Median
Mode
Standard Deviation
Value
15.2654
48.4988
33.2195
32.1727
33.4286
4.0617
50000
45000
40000
35000
25000
20000
15000
10000
5000
0
14.6
15.8
17.1
18.4
19.6
20.9
22.1
23.4
24.6
25.9
27.1
28.4
29.7
30.9
32.2
33.4
34.7
35.9
37.2
38.5
39.7
41
42.2
43.5
44.7
46
47.2
Pixels
30000
Temperature °C
Figure 10. Histogram for May 15, 2003.
23
Date: May 07, 2009.
Satellite: Landsat
Pixel X Size: 30.00 ; Pixel Y Size: 30.00
Scene Center Scan Time: 16: 57:59
Statistics
Value
Minimum
-28.1016
Maximum
50.1478
Mean
34.6184
Median
35.7935
Mode
35.4892
Standard Deviation
8.8994
700000
600000
400000
300000
200000
100000
48
48.9
46.7
45.5
44.6
43.4
42.2
41.3
40.1
38.8
37.6
36.7
35.5
34.3
33.1
31.8
30.6
29.4
28.2
27
25.4
24.2
23
0
21.8
Pixels
500000
Temperature °C
24
Date: May 13, 2011.
Satellite: Landsat
Pixel X Size: 120.00; Pixel Y Size: 120.00
Scene Center Scan Time: 16: 59:57
Statistics
Value
Minimum
-4.6245
Maximum
52.2745
Mean
32.9117
Median
32.7155
Mode
32.7155
Standard Deviation
4.8056
45000
40000
35000
25000
20000
15000
10000
5000
50.7
49.6
48.5
47.6
46.5
45.4
44.3
43.2
42.1
40.9
39.6
38.5
37.4
36.3
34.9
33.8
32.7
31.4
30.3
28.9
27.8
26.5
25.2
23.8
22.7
21.4
0
20
Pixels
30000
Temperature °C
25
The next table shows a comparison of the three images. Minimum was not taken into
consideration due to the negative minimum temperatures that are registered on the
original statistics.
Table 11. Statistics comparison
Maximum Mean
Median
Mode
2003
48.4988
33.2195
32.1727
33.4286
St.
Dev.
4.06
2009
50.1478
34.6184
35.7935
35.4892
8.89
2011
52.2745
32.9117
32.7155
32.7155
4.80
26
Figure 13. Urban Heat Islands and Neighborhoods for May 15, 2003.
27
Figure 14. Urban Heat Islands and Neighborhoods for may 07, 2009.
28
Figure 15. Urban Heat Islands and Neighborhoods for May 13, 2011
29
5.2 Climatic Analysis
Climatic Analysis is composed by:
1) Isotherms and Isohyets, to show the medium temperature and
rainfall
2) Wind Patterns
3) Solar Radiation
4) Temperature for
The isotherm map, extracted from INEGI, shows that the highest temperature is
located north of the MAM and extends east to Guadalupe and Juarez municipalities. The
lowest temperature is registered south up the Sierra Madre.
Isohyets map, extracted from INEGI, shows the highest rainfall south the MAM, and
northwest areas are the driest, west Monterrey to García. Months with high precipitation
are the months of June and September. The Centro de Desarrollo Metropolitano
(CEDEM) examined rainfall data and showed that evaporation values are much higher
than those of precipitation and they are inversely proportional: the less precipitation,
more evaporation. This is because in dry years the vapor pressure of the air is very low,
which promotes evaporation.. There is also a decreasing trend of evaporation. Like
Santa Catarina, Monterrey shows a trend towards decreased evaporation. The highest
recorded value occurred in 1977 was 2,931.19 mm against 446.6 mm of annual rainfall.
The months of highest evaporation are between April and August, with July which
shows the highest values. One consequence of evaporation on agricultural activities is
that they require higher amounts of water.
30
Figure 16: Isotherms Map. Source: INEGI
31
Figure 17: Isohyet Map. Source: INEGI
32
The wind patterns analysis (Figure 18), also included in the CEDEM publication of
Análisis Estratégico del Área Metropolitana de Monterrey, states that the wind speed
decreases during the winter (December and January, mainly) to an average of 0.3 m/s,
which means a poorer dispersion of pollutants during this time of year. In summer (June
and July) the average values reach up to 4 m / s. This facilitates the mixing and
dispersion of pollutants. In general, there are no high wind speeds in the area, since the
average fluctuates between 4 and 15 km / h. It is considered that the optimum velocity
for easy pollute dispersion is 25 km / h. The prevailing wind direction in the area is
from east and west, or 90 ° and 135 ° degrees azimuth. There is a change during the
winter to the north and northeast direction. (ITESM, 2008, p. 75)
Figure 18. Dominant winds direction for the MAM. Source: Análisis Estratégico del AMM,
CEDEM.
33
Average Radiation
The amount of solar energy captured (W/m2) during the day for each month of the
year is useful for building design. In the case of Monterrey, solar radiation data for the
year 1998 provided by SIMA (Sistema de Monitoreo Ambiental) was drawn in graph for
the Análisis Estratégico published by ITESM (Figure 19). It can be seen that the highest
value of radiation (W/h) is given in July at 12 noon.
Hour
Jan
Jul
Feb
Aug
Mar
Sept
Apr
Oct
May
Nov
Jun
Dic
Figure 19. Solar Radiation over an horizontal surface in Monterrey, 1998. Source: Sistema
Integral de Monitoreo Ambiental (SIMA), 1998 for CEDEM.
As a complement it is necessary to know the climate behavior of the MAM is
necessary to establish the number of clear, partly cloudy and cloudy days. Data obtained
for the period of 1967 to 1992, shows 46% of the time were clear skies, partly cloudy 31%
and 21% cloudy.
The next table shows climatic conditions for each day analyzed (CONAGUA), from
the Monterrey Meteorological Station.
34
Table 12. Climatic Conditions for analyzed dates
Date
Room
Temperature
(°C)
Maximum
(°C)
Minimum
(°C)
Rain
(mm)
Micrometer
(mm)
Evaporation
(mm)
May 15, 2003
23.0
34.0
22.0
0.0
51.81
9.66
May 9, 2009
25.0
40.5
25.0
0.0
93.05
8.42
May 13, 2011
23.5
36.5
22.5
0.0
21.41
6.59
Source: Comisión Nacional del Agua (2011).
Figure 20 shows a temperature comparison between the different analyzed years but
only taking into consideration the month of May.
50.0
45.0
40.0
35.0
°C
30.0
25.0
2011
20.0
2009
2003
15.0
10.0
5.0
30
28
26
24
22
20
18
16
14
12
10
8
6
4
2
0.0
Date
Figure 20. Temperature measurements for May. Ibid.
Table 13 shows a summary of the climatic conditions for May of the different years
analyzed.
35
Table 13. Climatic Conditions for analyzed months
Monthly Summary
May
2003
Temperature (°C)
2009
Day
2011
Day
Day
Maximum
43
7
40.50
Var
42.00
Var
Minimum
19.00
Var
17.50
21
15.00
4
Medium
28.66
28.21
28.38
Rainfall (mm)
Maximum (24 hrs)
67.00
28
5.50
31
5.80
14
Minimum (24 hrs)
0.00
29
0.30
28
0.70
16
Montly Medium
4.37
0.38
0.21
131.20
11.70
6.50
Total of the Month
Evaporation (mm)
Maximum
11.83
6
10.36
7
11.87
1
Minimum
1.33
12
1.73
17
1.00
16
Medium
7.20
6.80
7.74
223.16
210.72
240.09
Total of the Month
Number of days:
With Rain over 0.1 mm
With Unapreciate rain
5
4
2
1
0
1
31
12
10
Medium Pressence of Cloudiness
0
15
15
Cloudiness
0
4
6
Clear
Ibid.
36
5.3 Land Use / Land Cover
5.3.1 Land Use
Table 14. Land Use (M2) per Municipality
San Pedro
Agriculture
Extensive
Vegetated Area
Santa
Catarina
Monterrey
Apodaca
Escobedo
San
Nicolas
19,170
91,916
225,919
22,213,493
1,678,446
1,752
2,492,605
8,827,946
534,692
556,720
26,279,385
4,927,858
-
10,460,493
54,145
67,187
-
3,400,884
2,873
Small Vegetated
Area
Urban Green
Areas
Unused Land
2,471,637
412,217
5,443,070
453,541
6,978,704
5,095,811
21,797,427
Commerce
3,289,484
2,029,125
14,784,011
Equipment
1,027,349
809,865
643,774
Light Industry
Medium Industry
Guadalupe
2,291,172
486,492
1,569,057
2,206,132
13,934,942
12,149,628
6,392,476
9,610,138
4,640,871
1,439,872
5,972,165
5,417,581
7,355,873
891,515
1,063,646
2,005,180
2,762,724
509,305
973,750
613,386
476,750
617,591
626,474
83,930
1,848,186
1,589,206
3,941,011
890,532
2,672,969
1,475,801
Heavy industry
998,614
1,272,144
4,216,526
2,501,057
10,948
3,104,494
682,763
Not Specified
636,945
462,701
7,081,019
4,666,437
1,170,247
1,127,300
7,796,146
Mixed Use
433,176
335,959
2,821,684
1,024,139
1,093,585
809,645
1,435,922
14,279,473
6,333,910
49,253,579
11,573,073
9,228,247
16,429,002
22,765,601
Housing
Source: CEDEM(2000).
100.00%
Housing
Mixed Use
80.00%
Not Specified
Heavy industry
60.00%
Medium Industry
Light Industry
40.00%
Equipment
Shops and Services
20.00%
Unused Land
Urban Green Areas
Guadalupe
San Nicolas
Escobedo
Apodaca
Monterrey
Santa Catarina
San Pedro
0.00%
Small Vegetated Area
Extensive Vegetated Area
Agriculture
Figure 21. Land Use (M2) per Municipality. Source: CEDEM and LABSIG (2000).
37
Figure 22. Land Use Distribution. Ibid.
38
Table 15. Summary of Absence of Green Area
AGEBS
without
Green
Area
% of
AGEBS
% of the
Population
Area AGEBs
without
green area
% of Area
76
Population in
AGEBs
without
Green Area
(2000)
285,081
Apodaca
121
69
52,714,046
75
Escobedo
76
76
207,307
70
38,648,940
76
Guadalupe
96
46
297,036
43
35,846,683
42
Monterrey
234
52
560,345
49
111,071,856
53
San Nicolás
35
28
109,068
23
17,393,095
29
San Pedro
14
25
18,840
15
9,195,158
20
Santa
Catarina
55
63
144,919
56
21,657,048
60
631
53
1,622,596
48
286,526,826
51
TOTAL
Table 16 shows the extent of urban green area (m2) per inhabitant. Results showed
that only the municipality of San Pedro had the amount of green area suggested by the
World Health Organization (WHO), of 9 m2/ inh. WHO recommends locating green
areas within a distance of no more than 15 min walk (Sorensen, 1998). NJ Transit‟ (1994)
Planning for Transit-Friendly Land Use A Handbook for New Jersey Communities
defines reasonable walking distance by general understanding of willingness to walk 515 minutes to get to or from a transit stop, corresponding to ¼ to ½ mile, without taking
into consideration the topography, sense of safety and security, and presence of
interesting activity.
Table 16. Analysis of green area available per inhabitant on the MAM
Municipality
Inhabitants
Green Area(M2)
Available Green Area
(M2/Inhabitant)
San Pedro
121,977
3,296,961
27.0293
Monterrey
1,133,070
5,290,630
4.6692
San Nicolás
476,761
1,775,946
3.7250
Guadalupe
691,434
2,237,222
3.2356
Santa Catarina
259,202
503,987
1.9443
Escobedo
295,131
486,495
1.6484
Apodaca
Total
410,381
3,387,956
535,886
14,127,128.44
1.3058
4.1698
Source: Data provided by Labsig (ITESM) from INEGI census 2000 and Land Use Layer
39
Figure 23. Distribution of Public Green Space and AGEBs without these areas.
40
5.3.2 Land Cover
The final classes are: 1) Vegetation (green areas), 2) Low amount of vegetation,
3)Agricultural Land, 4) Roofs, 5) Road, and 6) Industrial Land. Final Overall Accuracy
resulted in 92 and 95% (Figure 24).
There is a high percentage of impervious material High density can be observed
North West Monterrey. Taking out of consideration the natural in the surrounding,
there are few urban vegetated areas. Also, agricultural land represents a small portion of
the MAM. It is important to notice the Industrial Land, which had a different spectral
response, which can correspond to a contaminated soil. Isolated roof classification inside
the Huajuco and Chipinque can explain how the urban expansion is now over high
slopes, and how impervious materials replace natural vegetation.
41
Green Areas
Roads (Asphalt)
Agricultural Land
Low amount of Vegetation
Industrial Land
Roofs (Concrete)
Figure 24. Land Cover Classification.
42
5.4 Social Composition
The social analysis localized the areas with low human welfare for the Urban Area of
Monterrey, to establish the degree of Environmental Justice (Amusquibar, 2006), which
is defined as “the right of all people to enjoy a healthy balanced and fit environment for
better human development and for future activities without harming resources for the
next generations” (Amusquibar, 2006, p. 4).
The unit area of analysis was an Area Geoestadística Básica (AGEB). The goal was
the definition of an indicator, which could localized areas with high poverty
concentration, and be able to identify susceptible population groups to have a better
geographic reference of where and which public policies should be taken in place. The
data was based on INEGI census for 2000. A map was generated for each variable, and
at the end there was an integrated map. Variables were: 1) Population density; 2) House
Quality based on infrastructure; 3) Population without health service.
Table 17. Synthesis of Variables taken into consideration
Factor
What is it?
Required Data
Population
Density
Relations the number of inhabitants,
for a given municipality per unit of
area. It shows the demographic
pressure over a surface
Total Population per AGEB
AGEBs Surface m2
House Quality
based on
Infrastructure
Evaluates the access to main services
such as drinkable water, electricity,
sewage.
Total Housing per AGEB
Amount of houses without
access to main services per
AGEB
Population
without access to
health services
Refers to the amount of inhabitants
without access to health programs.
Total Population per AGEB
Population without access to
health programs.
Source: SEDESOL, SEMARNAT, INE, UNAM. Indicadores para la caracterización y ordenamiento del
territorio. 2004
43
Figure 25. Population Density Map.
44
Figure 26. Percentage of population ages 5 to 14 not attending to elementary education per
AGEB.
45
Figure 27. Percentage of adult illiterate population per AGEB.
46
Figure 28. Percentage of the population without health services.
47
Figure 29. Percentage of houses without piped water.
48
Figure 30. Percentage of houses without sewage systems
49
Figure 31. Percentage of the houses without refrigerator
50
Table 18 shows the number of AGEBs per Municipality that are above average for
each Index, and the percentage that they represent from the total amount of AGEBs.
Average was taken to have a quantitative parameter.
Table 18. AGEBs above average per Index
Municipality
Health
Assets
AGEBs above
Average
AGEBs above
average:
Population
aged 5 to 14
who do not
attend school
AGEBs
above
average:
Illiterate
Adults
AGEBs above
average:
Population
without
access to
health
services
AGEBs:
above
average:
Houses
without
refrigerator
AGEBs:
above
average:
Houses
without
piped
water
AGEBs:
above
average:
Houses
without
sewage
system
76
47.80
2
1.26
11
6.92
30
18.87
26
16.35
0
0.00
1
0.63
50
50.00
10
10.00
36
36.00
45
45.00
28
28.00
13
13.00
9
9.00
125
60.39
3
1.45
41
19.81
100
48.31
24
11.59
4
1.93
6
2.90
200
44.25
18
3.98
107
23.67
210
46.46
168
37.17
25
5.53
8
1.77
82
65.08
0
0.00
16
12.70
30
23.81
4
3.17
0
0.00
0
0.00
8
14.55
0
0.00
6
10.91
8
14.55
12
21.82
0
0.00
0
0.00
% Municipality
54
62.07
1
1.15
27
31.03
28
32.18
20
22.99
7
8.05
4
4.60
TOTAL AGEBs
% of MAM
595
50.17
34
2.87
244
20.57
451
38.03
282
23.78
49
4.13
28
2.36
Apodaca
% Municipality
Escobedo
% Municipality
Guadalupe
% Municipality
Monterrey
% Municipality
San Nicolás
% Municipality
San Pedro
% Municipality
Santa Catarina
Density
Education
Housing
The AGEBS with 100% of houses without a refrigerator, access to piped water and
sewage system, and the greatest amount of population without health and education
services were considered the most precarious. It is important to notice that San Pedro
and San Nicolás municipalities have no AGEBS considered precarious. Monterrey is the
municipality with the highest number of AGEBs classified as precarious (Table 19), most
of them concentrated in Ciudad Solidaridad, which is located northwest of the
Metropolitan Area. Figure 32 shows the geographic distribution.
Table 19. AGEBS with Low Well-Being Index per Municipality
Municipality
Apodaca
Escobedo
Guadalupe
Monterrey
San Nicolás
San Pedro
Santa Catarina
Total MAM
Count of
AGEBs with
Low-Well
2
27
15
51
0
0
9
104
% of the
Total
AGEBs
1
27
7
11
0
0
10
9
Population in low
well-being
AGEBs
1,605
86,720
62,627
177,330
0
0
38,834
367,116
% of the
total
population
0
29
9
16
0
0
15
11
Area of low
well being
AGEBs
1,366,797
14,525,585
7,312,238
25,887,076
0
0
2,619,038
51,710,735
% of the
total area
2
29
9
12
0
0
7
9
51
Figure 32. Spatial distribution of AGEBs considered being the most precarious.
52
5.5 Spatial Analysis
Data was reclassified to find the relationship between Temperature and Land Use /
Land Cover. Each Land Use received a non arbitrary number. The land use supposed to
irradiate less heat, received the smallest value: Area with Extensive Vegetation (1), and
so on to Heavy Industry (14).
Table 20. Reclassification for Land use Correlation analysis
GRIDCODE
LAND USE
0
No data
1
Extensive vegetated area
2
Small vegetated area
3
Urban green area
4
Equipment and public spaces
5
Agrigulture
6
Unused land
7
Housing
8
Mixed use
9
Commerce and services
10
Equipment
11
Not specified
12
Light industry
13
Medium industry
14
Heavy industry
A layer to layer correlation resulted in the following equation:
Eq. 5
Y = -0.011339 + 0.010376 * X
Residual Error: 98.319152%
Correlation Coefficient: 0.129648
53
Reclassified data for Land Cover resulted in the next list. Again, each Land Cover
received non arbitrary number, depending on the amount of heat irradiated by artificial
materials such as concrete, asphalt. Dark and Industrial Covers are given the highest
number according to the albedo value.
Table 21. Reclassification for land cover correlation analysis
GRIDCODE
LAND COVER
0
Clouds and no data
1
Green vegetated area
2
Los amount of vegetation
3
Agriculture
4
Roofs (concrete)
5
Roads (asphalt)
6
Industrial land
Regression equation land cover and UHI :
Eq. 6
Y = 32.351077 + -0.034098 * X
Residual Error: 95.818996%
Correlation Coefficient: 0.204475
Figure 33 shows and approximate value of where has temperature increased the
most. To perform this, temperatures from 2003 where subtracted from 2009. Figure 34
shows temperature from 2009 and AGEBs considered to be precarious. With this figure
it is possible to visualize which strata are under heat stress. Finally, Figure 35 shows the
distribution of Low Well Being AGEBs, the ones without public green space, and the
Crime Rate (CEDEM).
54
Figure 33. Temperature subtraction 2009 minus 2003.
55
Figure 34. Temperature 2009 and Low Well Being AGEBs
56
Figure 35. Environmental Justice Map.
57
Table 22 describes the percentage of low well being AGEBs and the availability of
green area per inhabitant.
Table 22. Percentage of AGEBS per municipality with deficient characteristics
MUNICIPALITY
% OF DEFICIENT AGEBS
AVAILABLE GREEN AREA
(M2/INH)
1.9443
Santa Catarina
59.77%
San Nicolás
58.73 %
3.7250
Guadalupe
54.60 %
3.2356
Escobedo
45.00%
1.6484
Apodaca
44.65%
1.3058
Monterrey
39.60%
4.6692
San Pedro
Total
12.72%
45.61%
27.0293
4.1698
Table 23 shows the ideal public green area and the deficit according to the
recommendations of the World Health Organization, which considers a minimum of 10
M2 of green area per inhabitant.
Table 23. Green Area (M2) deficit for Population 2005
Municipio
San Pedro
Area Ideal
Total
1,219,770
Deficit
2,077,191
Monterrey
11,330,700
-6,040,070
San Nicolás
4,767,610
-2,991,664
Guadalupe
6,914,340
-4,677,118
Santa Catarina
2,592,020
-2,088,033
Escobedo
2,951,310
-2,464,815
Apodaca
4,103,810
-3,567,924
Total
33,879,560
-19,752,432
58
Chapter
6
Discussion
Areas of heat stress were identified. To investigate the relationship between Urban
Heat Islands and social strata, census data 2000 was analyzed. Images show not only the
distribution and intensity of UHI but also give a more descriptive knowledge about the
inhabitants and establish a correlation of land use/land cover and UHI. Spatial
relationships between land use, land cover and air temperatures in the city are relevant.
However, urban heat islands develop over industrial zones, reaching the hottest
temperatures. Also, topographical variations inside the MAM generate urban heat sink
formation, especially in Santa Catarina. Thus, this study aims to contribute to the
analysis of environmental justice, intends to establish a relation between low well-being
families, lack of green public area and suffering from heat stress. It is then to be said that
there is a high socio-spatial segregation, differences among the inhabitants of the MAM.
The final images selected to perform the analysis were from the year 2009, since this
is the most recent one that can be compared with 2003, according to the climatic
analysis, 2011 was a year of extreme events (Alex hurricane). The month of May was
chosen to perform the analysis, according to the solar radiation graph, which indicates
that May, July and August are the months with the highest radiation. Since July and
August are already rainy months it is difficult to obtain a cloud clear image. Results
show the localization of heat islands. One heat island is located in a lineal form along
Colón and Madero avenues, and it extends north around Parque Niños Héroes. Another
lineal formation is along Lincoln and Ruiz Cortinez avenues. Also, heat concentrates
north the Metropolitan Area of Monterrey, along Río Pesquería. Finally, there is another
heat island west Santa Catarina, and through the Huasteca. It is important to mention
that there are isolated heat points, mostly in parking lots of commercial zones.
The heat island formation Lincoln – Parque Niños Héroes phenomena can be
explained by the isotherm map which defines that the highest medium temperature
(22°C) is set along Cumbres and extends north Monterrey municipality through
Guadalupe. The isohyets map can explain the heat island formation west Santa Catarina,
due to the lowest rainfall value. In the same way wind patterns can help determine the
heat island formation north the MAM, along Río Pesquería. Heat is driven north by
south winds. On the other hand, it is a fact that temperatures are getting extremer
(cooler winters, warmer summers), drier months with rain in unusual months. Maybe it
is not a strong datum, but an operation to determine where temperature has risen shows
that areas like Cumbres in its way to García, south Santa Catarina, Guadalupe in its way
to Juarez, and Cañón del Huajuco had an increase in temperature. There is no surprise in
this statement because land cover has been changed dramatically by real estate
developers.
The natural situation of the MAM also alters the way in which contaminants are
dispersed, because of the dominant wind patterns. Atmospheric contaminants are
carried away to the west side of the study area, which topographically acts as a dam and
contains them, causing health damages in the population. Global Warming is a fact, and
for the MAM is also true. According to climatic stations located by Comisión Nacional
del Agua (CAN), the Centro de Desarrollo Metropolitano (CEDEM) analysis was
published by the year 2000 and first results showed a rise in temperature of 0.5°C (1959 –
59
1996) in Cerro del Topo Chico to 1.5°C (1954 – 1999) in Santa Catarina. Monterrey
Climatic Station, which has the longer historical period of temperature registration,
shows a rise of 0.8 °C (1921-1999). Historical registers show that Santa Catarina
municipality has the lower temperatures, due to the high situation above sea level,
which reduces the medium temperature. The climatic station called El Cerrito registers
cooler springs, due to the proximity of Huajuco Canyon, which protects the zone from
the daily sun light and forms a natural wind flow (ITESM, 2008, p. 67). It is then
concluded that there is a direct relationship between temperature and land use. The
result expresses that artificial land cover and industrial lands have a direct effect over
the formation and intensity of Heat Islands. UHIs in the MAM not only respond to a
natural topographical situation and wind pattern but also to human alterations over
land cover.
The results show that the geographical aspects of the MAM conditions the climatic
behavior. Remote Sensing analysis for Urban Heat Islands shows that, in a historical
comparison, maximum temperatures had risen almost 3.8°C. According to the
Intergovernmental Panel on Climate Change (IPCC, 1996) Climate Change models
established a rise in temperature of 1.5°C to 3.5°C in global temperature. Image shows
that not only has increase in °C but also in area due to land use and land cover change.
It is important to notice that housing uses from 12 to 42% of the total territory of the
MAM, but unused land occupies from 13 to 35%, almost the same as housing.
Unfortunately, green urban area occupies from 0.47 to 6.22% of the MAM. A result is a
catastrophic urban model of few green areas, plus a lot of houses and unused land
which equals to low densities and bad living qualities.
Land cover analysis leads to the conclusion that without the mountains and hills, the
city would not have green vegetated areas. Still, deforestation is extensive. WHO
suggests 10 m2 of green park per inhabitant, so the MAM requires 33, 879, 560 m2 to
attend to this statement. To eradicate the deficit this area represents 6 times Central Park
in New York, which has a dimension of 3,200,000 m2. Land use shows that there are
several square meters that are not being used or are uncovered with vegetation or other
artificial material, which could be used for reforestation and UHI mitigation.
The results show that there is a high percentage per municipality of unused land.
Also, the primary land use is for housing. Taking into consideration Table 1, population
growth in new municipalities and a decrease in the others, could show a tendency of
how unused land will continue increasing per municipality. Municipalities on actual
expansion will have to consider more housing land, and less new green areas.
Nevertheless, few new green areas are being created to increase the current percentage.
In the social analysis, results show that there are 130 AGEBs considered as “LOW
WELL-BEING”, meaning lack of house services and public health, representing 435, 721
inhabitants of the MAM. Of the total AGEBs, 849 do not consider Public Green Area,
according to official records, which contains 1, 923, 839 inhabitants. Finally, without
public green area and living in a precarious, unsanitary situation 111 AGEBS containing
366, 573 inhabitants.
For density, the lowest percentage is for San Pedro. This states that it is a disperse
municipality. On the contrary, San Nicolas, Santa Catarina and Guadalupe and
Escobedo are overcrowded. For education index, the highest percentage is in Escobedo
on both evaluations (population not attending school and illiterate adults); San Pedro
has the lowest percentages. For Health Index, Guadalupe, Monterrey and Escobedo
60
have the highest percentage of AGEBs with population without access to health services;
San Pedro has the lowest. AGEBs with high amount of houses without refrigerator
correspond to Monterrey, and Escobedo; San Nicolás has the lowest. Finally, housing
index shows that highest amount of houses without piped water and sewage systems
correspond to Escobedo and Santa Catarina; the lowest percentages correspond to San
Nicolas and San Pedro.
AGEBs northwest and north center Monterrey municipality, and west Santa Catarina
have a high density population, lack of primary services, and suffer of high heat stress.
State Constitutions declare that all inhabitants have the right to enjoy an adequate
environment and it is a State obligation to provide it. So, education should be a number
one social priority for the State, and social projects especially in zones with criminal
incidence. This social analysis also leads to the conclusion that poverty is being
criminalized. Finally, social analysis of this document might look obsolete, since the
census information is from the year 2000; however, if the authorities had paid attention
in these areas, they would not have became in crime nests.
Social and land use results show a relationship between the amount of green area
available per inhabitant and the percentage of deficient AGEBS per municipality.
Environmental Justice for the Metropolitan Area of Monterrey shows that areas with
high poverty concentration also have a deficit of green urban area. The lack of green
areas in the Metropolitan Area of Monterrey not only has negative effects on population,
but also in the formation of heat islands and so on the deterioration of the urban
landscape.
Green areas have not been taken into consideration in the metropolitan growth.
House land has been a priority. This is not a negative policy but it is important to
rethink the way in which they are been develop, with a lack of green areas. Real estate
developers should say that their developments are localized in zones of heat stress, as
important information to the buyer. Other negatively prioritized land use is the
industrial. Industries should adapt into their buildings, green roofs, if this is not possible
compensate their surroundings, or take advantage of the heat into their processes.
It is strongly difficult to propose neighborhood parks for AGEBs who lack of green
areas, but it is possible to use current railroads, used by industries, and riverbeds to
create vegetated areas. There is an urgent need of urban green areas, not only with
benches or playgrounds, but community centers which could provide culture,
education, sports and that offer real environmental services. With this, it will be possible
to impulse local economies and have a true sustainable development. Although public
policies to improve health services have been implemented since the year 2000, when
the Census was made, there are specific AGEBs with population without this service. It
is not surprising that these areas are also lacking of a piped water, sewage systems and
basic assets like a refrigerator to have a healthy living. It is a must to consider that
without these factors, health problems and environmental degradation are more
common, and without a public health service this population is very vulnerable. Linking
them to climate change, a rise in rainfall and the high slopes and overflowed areas will
raise the risks of landslides. People will lose the few assets they owned, living them in a
more precarious situation. All this would have disastrous economic and social
consequences.
61
Chapter
7
Mitigation Strategies
This section examines some potential strategies to reduce temperature gain from the
urban heat island effect. Generally, measures are closely related to social and economic
activities. Since intensity and distribution vary locally, different mitigation strategies
should be taken into consideration. In any level, it is important to always involve state
government, municipalities, industrial owners and residents. The government should
stipulate the magnitude and time implementation of the actions to be taken.
In order to mitigate UHI phenomena, it is important to carry out effective measures,
analyzing multidimensional and multi temporal factors and cost-benefit. Urban heat
island phenomenon is deeply embedded with urbanization which has been built up
over a long period, so resolution inevitably needs long term programs. Monitoring of
the UHI situation and review of state-of-art scientific knowledge and technologies shall
be carried out. UHI phenomenon reflects a wide range of social and economic activities.
Therefore partnership between the central government, local governments, business and
residents is important in implementing measures. Also, linkage with policies on global
warming, urban, traffic and energy and so on shall be promoted (InterMinistry
Coordination Committee, 2004).
Japan
The “Outline of the Policy Framework to Reduce Urban Heat Island Effects”, which
was laid down in March 2004, by the Japanese government, stipulates that lifestyles
must be reformed as part of any measure to mitigate urban heat islands. When the
Ministry of the Environmental defined “the urban heat island effect as polluted air” in
August 2011, mitigation measures suddenly emerge as a political issue (Yamamoto,
2005). Subsequently, an Inter-Ministry Coordination Committee to Mitigate Urban Heat
Islands was established. Strategies focus on :
1. Reduction of anthropogenic heat emission
 Improve efficiency of energy consuming equipments by subsidizing new
technology development and installation of its outcome.
 Diffuse high energy efficient houses and buildings by policy-based finance, model
projects developing environment friendly houses and urban areas
 Technology development and the diffusion of low emission vehicles
 Traffic control measures, facilitation of rationalization of the distribution and
encouraging use of public transportation
 Encouragement of the use of new energy
2. Improvement of Urban Surface in order to mitigate decrease of evapotranspiration
 Tree-planting in private houses, buildings and their sites
 Promotion of tree-planting in public facilities such as government buildings
 Construction of urban parks and promotion of tree-planting in public spaces such
as ports, airports and sewage plants
62
3. Improvement of urban structure in order to ensure wind flow through green spaces
and water,
 Development of network with green and water in the region across the prefectures
by construction of large green spaces and making up the linkage between parks,
rivers and roads
 Feasibility study on the urban heat emission treatment system which carry heat
from the densely build-up area to rivers and sea through under-ground pipes with
circulating water
 Facilitation to utilize the city planning system to develop “less environmental
burden cities”.
4. Improvement of Life-style
 Promotion of actions taken by business and families to utilize new energy and to
save energy such as utilizing sunshine and air heat energy and to collect and
utilize rainwater
 Promotion of light clothes in summer
 Facilitation of summer vacation to reduce anthropogenic heat emission in the
cities
 Facilitation of efficient use of cars by eco-driving and so on
Particular campaigns for individuals encourage them to wear light clothing in
summer, called “Cool Biz” dress code. This enabled the temperature of its air
conditioned workplaces to be kept at 28°C. Major urban mitigation included application
of light colored paint to exterior walls, use of reflective roofing materials, maintenance
and improvement of parks and green spaces, construction of large scale greenbelts,
green roofs, photovoltaic cells, water- retentive pavement, wind paths, open water
spaces, and introduction of traffic- control measures (low emission vehicles and
bicycles).
In July 2005, the Tokyo Metropolitan Government developed the “Guidelines for
Urban Heat Island Mitigation Measures” to encourage private businesses and public to
develop mitigation measures according to the thermal environment in which they
operate or live. Shade guideline considers the creation of shade trees, particularly on the
southern and western sides of the buildings where solar radiation is most intense and
reduces the heat buildup in pedestrian spaces (canopies, pergolas). Surface cover refers
to reduce the temperature by planting grass and constructing ponds, anything natural
that minimizes pavement surface, if placed, they should be permeable materials.
Exterior construction materials seek to reduce the heat input into the building by using
highly reflective roofing materials. Another guideline to be considered is the open and
airy space by constructing vegetated walkways and giving careful consideration to the
height a space around the building. Finally, heat release form the building should be
considered when designing it (proportions, energy saving measures).
63
Other countries
Freiburg located east end of the Rhine River Valley, lacks of wind days which often
leads to thermal stress, and air pollution. Their mitigation strategy was the alteration of
the street patterns to create a wind path.
Another big mitigation act was “the Cheonggyecheon restoration project” in Korea.
During the 1950‟s the 11 km long section that joins the Han River was converted into an
elevated road. Seoul Metropolitan Government demolished and restored the river to its
natural state. The project alleviates the city of the air pollution and decreased summer
temperatures in the area alongside the river.
In 1997, the Environmental Production Agency (EPA) instituted the “Heat Island
Reduction Initiative” (HIRI) after the heat wave that struck Chicago in July 1995,
resulting in over 700 people death. Cities selected for the Urban Heat Island Pilot
Projected launched to investigate the phenomenon are: Baton Rouge, Louisiana;
Chicago, Illinois; Houston, Texas; Sacramento, California; and Salt Lake City, Utah.
Other general ideas are:
 Reduce parking lots and use of porous pavement. Parking lots should be in the
streets and compact development plan aimed at pedestrians, promote
transportation options and minimize the size and number of lots.
 Preserve and maintain trees and vegetation: Natural urban spaces, surrounding
private properties, sidewalks, green roofs.
Observation and Monitoring
Observation and monitoring systems to get the actual condition of UHI shall be
strengthened as basis for the evaluation of measures. Until now, there are few studies
carried out by academics. Governments should get involved to reinforce mitigation
strategies. Maps should be made in order to accumulate data and evaluate actions. A
design guideline must be developed to add efforts to reduce UHI phenomenon.
Multilateral programs must be enforced to exchange information with other countries
about UHI phenomenon.
Mitigation Strategies for the MAM
Even though the international community is studying ways to mitigate the urban
thermal environment, these strategies should be tailor-made for each city. The next list
contains series of recommendations for the MAM.
1. Consider Urban Heat Island Mitigation Project as a public policy. With the
combination of multiple technical analyses and the work of various
organizations and private sector, establish a pilot project to reduce the adverse
impacts of heat.
2. Consider the Río Santa Catarina and Río Pesquería as open spaces which should
be integrated to the urban structure.
3. Change the way of living. Create multiple green corridors that should be
pedestrian, for bike use, and other forms of urban transportation (subway, Buss
of Rapid Transit, buses). Connect Colón and Madero with Fundidora; B. Reyes
through V. Carranza up to Río Santa Catarina; and J.I Ramón with Paseo Santa
Lucía. For Ruíz Cortines a Juárez there is already a proposal.
64
4. Realize that in order to achieve sustainable urban development it is necessary to
create programs which provide a minimum quality of life to the citizens.
5. Reuse abandoned land and infrastructure (old railroads). Railroads in the MAM
are being used as dumpsters. Figure 36 shows the current state of a train tract.
Figure 36. Current State of Train Tracts in the MAM.
6.
Create a Park System for the Metropolitan Area of Monterrey. Nowadays, it is difficult
to create green urban areas due to the lack of free space. The Diagnostic of the Urban
Park System of the Greater Monterrey Area elaborated by Labsig, ITESM gives possible
tracts to perform this action. These projects will allow, not only a green open space, but
they will also provide a protection against overflows.
Table 24 . List of Tracts (Railroad and Riverbed) to Propose the Master Plan
Railroad
Tract
Lenght
Way Matamoros
From Parque Niños Héroes to Av. Miguel Alemán
13.0 kms
Way Tampico Nueva
From Av. Diego Díaz to Av. Félix Galván
1.3 kms
TOTAL
14.3 kms
Riverbed
Tract
Area
Pesquería
From Parque Nacataz to Av. H. Castillo
From Av. Parque Industrial to Carretera Colombia
154 ha
36 ha
Santa Catarina
From La Huasteca to Av. Constituyentes de NL
310 ha
La Silla
From Parque La Pastora to Las Margaritas
270 ha
Topo Chico
From Camino Sta Rosa to Río Pesquería
120 ha
TOTAL
890 ha
Source: Labsig, ITESM.
65
To reduce radiation, it is necessary to surround buildings with less reflective
surfaces. Vegetation absorbs most of the radiation and cools down by evaporation, so it
can reduce thermal temperatures, which allows an accumulation of 4200 kcal/m2 per
season.
Presented strategies are effective in the short term to decrease urban heat
temperatures, but they do not provide long lasting solutions to urban heat island effects.
To do so, a long term public policy must proceed. Also, UHI are regional, so they require
regional mitigation measures done simultaneously to produce satisfactory results. The
most effective mitigation strategy is without doubt a change in the way we are making
cities.
Figure 37 shows the Master Plan proposal, taking into consideration the diagnosis
made by LABSIG in their document. The intend is that tracts not only are used for
transportation, but also used, in low-well being zones as community centers.
66
Figure 37.Master Plan Proposal for Public Green Areas
67
Chapter
8
Conclusions
Changes in land cover and urbanization affect local temperatures and climate.
Moreover, urban marginalization highlights the importance of strengthening social
development programs to improve the habitat of the urban population in areas with
high and very high levels of poverty. Orderly and sustainable cities can to contribute to
equitable growth.
Information shows that there is a lot of unused land in the MAM which can be
employed to stop de urban expansion over vegetated areas and reduce the increment of
heat islands. Also, these lands can have a use of green public space recreational area,
which will not only mitigated the heat stress effect but also socially include poor
population. It is extremely necessary to update the cadastre information to give a
properly approach of the abandoned land. This will also allow local authorities to
update the cadastre payment, which is very obsolete. With this, municipalities will have
more income money and could done more social projects, community centers,
recreational parks.
Urban Heat Island is a complex problem that can be mitigated with different
approaches, depending on the multidisciplinary team formation that could give
different proposals. As the method proposed, UHI must be mitigated using a
sustainable analysis identifying high and adverse human health and environmental
effects and its impact on the economy and population. Mapping the low income
population areas, with adverse temperatures and social problems represents an effective
mechanism to evaluate government decision impacts. For the creation and
implementation of public policies, it is necessary to have analytical tools to synthesize
the complexity of urban problems in an AGEB scale measure to sort and differentiate
between each other priority problems affecting population.
Urban heat island mitigation measures must be adopted when planning further
development in the cities. Mitigation measures should not involve individual measures
but a change in the way of making city. The use of technology and software should be
employed to study the natural and social characteristics of the concerned area to carry
out effective measures. Updated data (census, cadastre, risk analysis, meteorological
data acquisition) is fundamental to carry out any technical study, which could allow a
simulation as a window to the future, evaluating the possibilities of a mitigation
strategy. And the most important, already considered, go from research to policy
implementation. Decision-makers must find a way to utilize the scientific knowledge
and ask policy-relevant questions about potential impacts, without demanding
particular answers (Andersen, 2000)
68
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72
VITA
Ana Lucrecia Rivera nació el 23 de abril de 1985 en Torreón, Coahuila, lugar donde
residió hasta julio de 2003. Posteriormente vivió en la ciudad de Monterrey donde
realizó estudios de Arquitectura con especialidad en “Arquitectura Sustentable” En la
Universidad de Monterrey (UDEM). Su proyecto de evaluación profesional fue titulado
“Regeneración de la Antigua Estación de Ferrocarril en Monterrey” en donde se abordan
temas de regeneración urbana, áreas verdes y desarrollo social.
En enero del 2010 ingresó al programa de Maestría en Sistemas Ambientales del
Instituto Tecnológico y de Estudios Superiores de Monterrey (ITESM). Durante los
estudios de maestría colaboró como asistente de investigación en el Laboratorio de
Sistemas de Información Georreferenciada del Centro de Calidad Ambiental en el
edificio CEDES.
Su tema de interés principal es el desarrollo urbano sustentable que se derivan en los
siguientes temas particulares: impacto ambiental de las ciudades, crecimiento regional,
ordenamiento territorial, políticas públicas para la planificación, riesgos en
asentamientos humanos, pobreza en las ciudades, justicia urbana, inclusión social
urbana de la población.
Domicilio permanente:
Chiapas 612 A
Col. Nuevo Repueblo
Monterrey, N.L
CP 64700
México
Correo de contacto:
[email protected]
*TESIS IMPRESA EN PAPEL PROVENIENTE DEL RECICLAJE DE POLIENVASES DE
1 LITRO, LIBRE DE CLORO.
73

instituto tecnológico y de estudios superiores de - LabSIG

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