Urban heat islands in Monterrey, México using remote sensing imagery and geographic information systems analysis

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(1)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.

(2) 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 ofSciencein Environmental Systems June 2012.

(3) 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..

(4) 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..

(5) 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..

(6) 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.

(7) 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.

(8) 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.

(9) 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 11. Histogram for May 07, 2009 ........................................................................... 24 Figure 12. Histogram for May 13, 2011 ........................................................................... 25 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.

(10) 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.

(11) 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.

(12) 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.

(13) 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.

(14) 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.

(15) 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.

(16) 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.

(17) 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.

(18) 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.

(19) 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.

(20) 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.

(21) 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.

(22) 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.

(23) 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.

(24) 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.

(25) 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 w i t h a Scene Center Scan Time at 17:28:13.1 The second image was f r o m L A N D S A T T M of May 07, 2009 w i t h a Scene Center Scan Time at 16: 57:28. The last image was dated for May 13, 2011 w i t h a Scene Center Scan Time at 16:59:57. I t 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 U H I , basic preprocess was done. Aster image was obtained i n 1B level, where the radiometric calibration and geometric resampling were already carried out. A l l ASTER thermal bands were resample at 90 m, by the Nearest Neighbor algorithm. L A N D S A T T M images have 1 thermal infrared band and were re sample at 120-m. A l l images were georeferenced to Universal Transverse Mercator projection: U T M Zone 14.. ASTER: 1. Calculate D N to spectral radiance. Equation 1 shows the conversion of D N to spectral radiance for the ASTER image. Eq 1. L. r a d ,. j. =. (DN -1)UCC j. j. Where, Lrad, j is ASTER spectral radiance at the sensor's aperture measured i n a wavelength j ; j is the ASTER band number; DNj is the unitless D N values for an individual band j ; UCCj is the Unit Conversion Coefficient (W m sr um ) f r o m ASTER Users Handbook . -2. -1. -1. Table 3. Unit Conversion Coefficient (W m sr um ) - 2. -1. -1. 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.

(26) 2. Calculate Spectral Radiance to brightness temperature Let K 1 = C1/X5 , and K2 = C2/X, and satellite measured radiant intensity B X (T) = L X, Eq. 2. Therefore, K 1 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). 3. Calculate Units of Temperature Kelvin to Celsius Eq. 3. °C =. K-273. LANDSAT TM: 1. Calculate D N to spectral radiance (L). Eq. 4 Where RTM6 is the Spectral Radiance (mW.cm-2sr-1), D N the grey level, L M I N is Spectral radiance of D N value 1 and L M A X Spectral radiance of D N value 255. L M I N and L M A X 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, K 1 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.

(27) 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.

(28) 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.

(29) The studies f r o m Secretaria General del Consejo Nacional de Poblacion (CONAPO) produce demographic indicators that provide insight into the lives of the population and its distribution i n national territory, i n order to support the design, implementation and evaluation of programs for economic and social development and the environment. Based on the report of Indices 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 i n poor housing and lack of basic necessities. H i g h deprivation index population usually sits unevenly on the outskirts of cities, i n areas not suitable for urban development, and faces a number of risks and vulnerabilities that compromise their quality of life and physical integrity and w i t h negative effects on the environment (environmental degradation and pollution), which i n 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 w i l l be possible to establish an Environmental Justice Map for the M A M .. Population D e n s i t y Population Density refers to the number of people inhabiting a given area. Higher density cities are more sustainable than l o w density cities. Nevertheless, high density can also mean overcrowded spaces. In this case there is an excess on the carrying capacity of the environment.. E d u c a t i o n Index Percentage of population aged 5 to 14 w h o do not attend school (I1). Percentage of population aged 15 to 130 w h o do not k n o w how to read or write (I2). H e a l t h Index Percentage of population w i t h o u t access to health services ((I1). 20.

(30) H o u s i n g Index Percentage of houses w i t h o u t piped water (I5). Percentage of houses w i t h o u t sewage system (I6). Assets Index Percentage of houses w i t h o u t refrigerator (I10). W e l l - B e i n g Index AGEBS w i t h the higher percentage of population and houses w i t h o u t a basic need or service (Education, Health, Basic Housing Services, and Assets) are considered w i t h a high deprivation index. Heat Islands w i l l be characterized using socioeconomic data, climate conditions, and land use/land cover. Using this information, i t w i l l be evident which strata are under severe heat stress and their conditions. H a v i n g a geographical view of the problem it w i l l be easier to establish more effective Mitigation Strategies for the M A M . Figure 9 shows the methodology followed.. 21.

(31) Figure 9. Methodology Process Diagram.. 22.

(32) Chapter 5. Results 5.1 Urban Heat Islands Date: May 15, 2003 Satellite: ASTER Projection: U T M , 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 Value. 6 4 1. .. .. 8 1 4 6 5 7 8 9 1 1 11. .. .. .. 9 1 4 6 9 1 4 7 9 2 4 7 9 2 5 7 1 2 0 2 3 4 5 7 8 9 0 2 3 4 5 7 8 9 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 Temperature °C. ... .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 5 7 6 2 3 4 7 4 4 4. .. .. 4. .. .. .. .. .. .. 4. .. 4. Figure 10. Histogram for May 15, 2003.. 23.

(33) Date: May 07, 2009. Satellite: Landsat Projection: U T M , Zone 14 Pixel X Size: 30.00 ; Pixel Y Size: 30.00 Scene Center Scan Time: 16: 57:59. Table 9. ERDAS Statistics for May 07, 2009. Temperature °C. Figure 11. Histogram for May 07, 2009. 24.

(34) Date: May 13, 2011. Satellite: Landsat Projection: U T M , Zone 14 Pixel X Size: 120.00; Pixel Y Size: 120.00 Scene Center Scan Time: 16: 59:57. Table 10. ERDAS Statistics for May 13, 2011. Figure 12. Histogram for May 13, 2011. 25.

(35) The next table shows a comparison of the three images. M i n i m u m was not taken into consideration due to the negative m i n i m u m temperatures that are registered on the original statistics.. Table 11. Statistics comparison. 26.

(36) Figure 13. Urban Heat Islands and Neighborhoods for May 15, 2003. 27.

(37) Figure 14. Urban Heat Islands and Neighborhoods for may 07, 2009. 28.

(38) Figure 15. Urban Heat Islands and Neighborhoods for May 13, 2011 29.

(39) 5.2 Climatic Analysis Climatic Analysis is composed by: 1) Isotherms and Isohyets, to show the m e d i u m temperature and rainfall 2) W i n d Patterns 3) Solar Radiation 4) Temperature for. The isotherm map, extracted f r o m INEGI, shows that the highest temperature is located north of the M A M and extends east to Guadalupe and Juarez municipalities. The lowest temperature is registered south u p the Sierra Madre. Isohyets map, extracted f r o m INEGI, shows the highest rainfall south the M A M , and northwest areas are the driest, west Monterrey to Garcia. Months w i t h 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 i n dry years the vapor pressure of the air is very low, w h i c h 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 i n 1977 was 2,931.19 m m against 446.6 m m of annual rainfall. The months of highest evaporation are between A p r i l and August, w i t h July which shows the highest values. One consequence of evaporation on agricultural activities is that they require higher amounts of water.. 30.

(40) Figure 16: Isotherms Map. Source: INEGI 31.

(41) Figure 17: Isohyet Map. Source: INEGI 32.

(42) The w i n d patterns analysis (Figure 18), also included i n the CEDEM publication of Análisis Estratégico del Área Metropolitana de Monterrey, states that the w i n d speed decreases during the winter (December and January, mainly) to an average of 0.3 m/s, w h i c h 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 m i x i n g and dispersion of pollutants. I n general, there are no high w i n d speeds i n the area, since the average fluctuates between 4 and 15 k m / h. It is considered that the o p t i m u m velocity for easy pollute dispersion is 25 k m / h. The prevailing w i n d direction i n the area is f r o m 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 M A M . Source: Análisis Estratégico del A M M , CEDEM.. 33.

(43) The amount of solar energy captured (W/m2) during the day for each month of the year is useful for building design. I n the case of Monterrey, solar radiation data for the year 1998 provided by SIMA (Sistema de Monitoreo Ambiental) was drawn i n graph for the Análisis Estratégico published by ITESM (Figure 19). It can be seen that the highest value of radiation (W/h) is given i n July at 12 noon.. Figure 19. Solar Radiation over an horizontal surface in Monterrey, 1998. Source: Sistema Integral de Monitoreo Ambiental (SIMA), 1998 for CEDEM.. As a complement i t is necessary to k n o w the climate behavior of the M A M 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 ( C O N A G U A ) , f r o m the Monterrey Meteorological Station. 34.

(44) Table 12. Climatic Conditions for analyzed dates. Source: Comisión Nacional del A g u a (2011).. Figure 20 shows a temperature comparison between the different analyzed years but only taking into consideration the month of May.. Figure 20. Temperature measurements for May. Ibid.. Table 13 shows a summary of the climatic conditions for May of the different years analyzed.. 35.

(45) Table 13. Climatic Conditions for analyzed months. 36.

(46) 5.3 Land Use / Land Cover 5.3.1 Land Use. Figure 21. Land Use (M2) per Municipality. Source: CEDEM and LABSIG (2000).. 37.

(47) Figure 22. Land Use Distribution. Ibid.. 38.

(48) Table 15. Summary of Absence of Green Area. 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 W o r l d Health Organization (WHO), of 9 m2/ inh. W H O recommends locating green areas w i t h i n a distance of no more than 15 m i n w a l k (Sorensen, 1998). NJ Transit' (1994) Planning for Transit-Friendly Land Use A Handbook for New Jersey Communities defines reasonable w a l k i n g distance by general understanding of willingness to w a l k 5¬ 15 minutes to get to or f r o m a transit stop, corresponding to 1/4 1/2 mile, w i t h o u t 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 M A M. Source: Data provided by Labsig (ITESM) f r o m I N E G I census 2000 and Land Use Layer. 39.

(49) Figure 23. Distribution of Public Green Space and AGEBs without these areas. 40.

(50) 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 i n 92 and 95% (Figure 24). There is a high percentage of impervious material H i g h density can be observed N o r t h West Monterrey. Taking out of consideration the natural i n the surrounding, there are few urban vegetated areas. Also, agricultural land represents a small portion of the M A M . It is important to notice the Industrial Land, w h i c h had a different spectral response, which can correspond to a contaminated soil. Isolated roof classification inside the Huajuco and Chipinque can explain h o w the urban expansion is n o w over high slopes, and h o w impervious materials replace natural vegetation.. 41.

(51) Figure 24. Land Cover Classification.. 42.

(52) 5.4 Social Composition The social analysis localized the areas w i t h l o w 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 w i t h o u t 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 w i t h high poverty concentration, and be able to identify susceptible population groups to have a better geographic reference of where and w h i c h public policies should be taken i n place. The data was based on I N E G I 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 w i t h o u t health service. Table 17. Synthesis of Variables taken into consideration. Source: SEDESOL, S E M A R N A T , I N E , U N A M . Indicadores para la caracterización y ordenamiento del territorio. 2004. 43.

(53) Figure 25. Population Density Map.. 44.

(54) Figure 26. Percentage of population ages 5 to 14 not attending to elementary education per AGEB. 45.

(55) Figure 27. Percentage of adult illiterate population per AGEB. 46.

(56) Figure 28. Percentage of the population w i t h o u t health services.. 47.

(57) Figure 29. Percentage of houses without piped water.. 48.

(58) Figure 30. Percentage of houses without sewage systems. 49.

(59) Figure 31. Percentage of the houses w i t h o u t refrigerator 50.

(60) Table 18 shows the number of AGEBs per Municipality that are above average for each Index, and the percentage that they represent f r o m the total amount of AGEBs. Average was taken to have a quantitative parameter. Table 18. AGEBs above average per Index. The AGEBS w i t h 100% of houses w i t h o u t a refrigerator, access to piped water and sewage system, and the greatest amount of population w i t h o u t health and education services were considered the most precarious. It is important to notice that San Pedro and San Nicolas municipalities have no AGEBS considered precarious. Monterrey is the municipality w i t h the highest number of AGEBs classified as precarious (Table 19), most of them concentrated i n 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. 51.

(61) Figure 32. Spatial distribution of AGEBs considered being the most precarious. 52.

(62) 5.5 Spatial Analysis Data was reclassified to f i n d 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 w i t h Extensive Vegetation (1), and so on to Heavy Industry (14). Table 20. Reclassification for Land use Correlation analysis. A layer to layer correlation resulted i n the following equation: Eq. 5. Y = -0.011339 + 0.010376 * X Residual Error: 98.319152%. Correlation Coefficient: 0.129648. 53.

(63) Reclassified data for Land Cover resulted i n 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. Regression equation land cover and U H I : 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 f r o m 2003 where subtracted f r o m 2009. Figure 34 shows temperature f r o m 2009 and AGEBs considered to be precarious. W i t h this figure it is possible to visualize w h i c h strata are under heat stress. Finally, Figure 35 shows the distribution of Low Well Being AGEBs, the ones w i t h o u t public green space, and the Crime Rate (CEDEM).. 54.

(64) Figure 33. Temperature subtraction 2009 minus 2003. 55.

(65) Figure 34. Temperature 2009 and Low Well Being AGEBs 56.

(66) Figure 35. Environmental Justice Map. 57.

(67) Table 22 describes the percentage of low w e l l being AGEBs and the availability of green area per inhabitant.. Table 22. Percentage of AGEBS per municipality w i t h deficient characteristics. Table 23 shows the ideal public green area and the deficit according to the recommendations of the W o r l d Health Organization, w h i c h considers a m i n i m u m of 10 M2 of green area per inhabitant.. Table 23. Green Area (M2) deficit for Population 2005. 58.

(68) 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.

(69) 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.