Urban expansion and climate change in the Federal District of Brazil

Urban expansion and climate change in the Federal District of Brazil | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Urban expansion and climate change in the Federal District of Brazil Daniela Rocha Werneck, Marta Adriana Bustos Romero, Maria Cristina Celuppi, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4258681/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Brazil has made a voluntary commitment to reduce greenhouse gas emissions as part of the National Policy on Climate Change, but adaptation and mitigation measures for urban areas to promote climate resilience are still lacking. In this context, this article aims to explore the urban thermal environment of Brasília, Brazil. The city was inaugurated in 1960 and its Plano Piloto is a UNESCO World Heritage Site designed by Lucio Costa based on the principles of the modernist movement. In order to evaluate the intra-urban distribution of surface temperature and vegetation, satellite images and remote sensing techniques were used to generate thematic maps. From this information, an exploratory analysis of spatial data was performed to identify clusters where the surface temperature has positive, negative or null autocorrelation. The results of the Moran indices pointed to the spatial dependence of the surface temperature, independent of the variability of the climatic seasons. Observing the urban fabric, the trend towards higher surface temperature values is associated with morphological characteristics such as soil occupation rate, absence of vegetation and shade and predominantly waterproofed surfaces. Urban Climate Land Surface Temperature Urban Greening Intra-urban Heat Vulnerable Neighborhoods Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Urbanization is a constant and growing process that transforms land cover and use and presents concerns of a climatic, ecological, environmental, cultural, historical and socioeconomic nature, considering that the current logic of the economic system and unlimited growth contradicts future predictions of scarcity of resources, energy and spatial limitation. In this context, sustainable cities are essential for the perpetuation and future quality of human life. (Romero et al., 2019 ). Urban development produces several impacts related to the urban climate with implications for emissions of pollutants and anthropogenic heat, reduction of natural land cover and changes in land use and occupation patterns. Added to this are the urban morphology, the thermal and optical characteristics of urban materials and changes in ventilation parameters, which contribute to changes in the local climate. One of the most outstanding phenomena in urban climatology is the urban heat island (UHI), characterized by warmer urban areas in relation to the surrounding rural areas, which can be observed on the surface, underground and in the urban atmosphere (Oke, 1987 ; Lombardo, 1985 ; Gartland, 2010 ). In this context, the scales of analysis are fundamental for the understanding of climate change in the city, integrating from the microscale to the impacts on the regional climate (Gobo; Galvani; Wollmann, 2018 ), that is, when observed in a city, or city fraction, the UHI phenomenon is characterized as a microclimatic condition in which the air temperature is higher, the relative humidity is lower and there is a change in wind speed, rainfall, among others. Thus, the phenomenon of UHI stems from urban densification, characterized by geometries that block the winds and increase the rate of heat absorption, the increase in albedo (given the constant waterproofing of the soil), in addition to the human action of vegetation removal and consequent reduction in evapotranspiration, which in turn represents a significant decrease in relative humidity (ROMERO et al, 2019 , p.13). The whole world has been observing the process of climate change, and initiatives to mitigate the harmful effects on human health, biodiversity and sustainability resulting from these changes are presented in a discreet way, not able to keep up with the urgency of the environmental crisis, as observed in Brazil, which assumed voluntary commitments to reduce emissions, however adaptation measures, especially for Brazilian urban areas, end up being unassisted. In the context of cities they represent and built environments in general, there is a need for a careful look at the spatial configuration, through the urban structure (the dimensions of buildings, open spaces and the size of roads and streets), urban coverage (built, paved, vegetated, water, bare soil), urban fabric (construction and natural materials) and urban metabolism (heat, water, pollution due to human activities). An adequate treatment of the site must include the dimensions of these aspects, considering that the urbanization process is permanent and intense in the country and thus the understanding of the impact of the urban configuration on the urban climate, on the levels of comfort and on the energy demand of buildings acquires significant importance for urban and regional planning. In other words, it is essential to understand the various climate scales and their relationship with the built space, incorporating multidisciplinary knowledge and also analysis and dissemination tools, since the climate is a factor that directly impacts the quality of life. In this article, the connection between the thermal field of the city and vegetation will be presented, analyzing the case of the Federal District of Brazil. The first topic presents a characterization of the urban area of the Federal District (DF). Subsequently, issues related to urban green areas, indicators and differences in their intra-urban distribution will be addressed. Third, discussions on climate change, government efforts to understand future scenarios for the DF will be addressed and, at the City scale, the distribution of surface temperature and vegetation will be analyzed. Next, a discussion about urban thermal comfort is presented and, finally, a conclusion with reflections on the key themes of the article and suggestions for future work. City Characterization The Federal District (DF) of Brazil was planned from its location to the urban design of its Plano Piloto. For a better understanding, the DF is the smallest of the 27 federative units in Brazil and the only one not divided into municipalities. The urban agglomerations that form the DF are called administrative regions (RAs), which are currently 33, in a total area of 5,779,999 km². Located in the Midwest region of Brazil, its territory houses the federal capital, Brasília, which is also the seat of the government of the Federal District (Fig. 1 ). The location and demarcation of the DF relied on surveys and studies carried out in 1892 by the Comissão Exploradora do Planalto Central do Brasil, an exploratory commission headed by geographer Luís Cruls and, in 1954, another commission, headed by General José Pessoa, completed the studies already carried out and defined the area of the future capital. From the promise of advancing 50 years in 5, then President Juscelino Kubitschek was the political leader of the modernist urban project created by architect Lucio Costa, which began construction in 1956 and was inaugurated in 1961. Sixty-one years later, the DF emerges as the third largest urban center in the country with 3,015,268 inhabitants (IBGE, 2019), behind São Paulo, founded in 1554, and Rio de Janeiro, founded in 1565. Most RAs did not exist before the demarcation of the DF, except for Planaltina and Brazlândia. The other RAs originated from different urbanization processes, either from irregular occupations (such as Itapoã and Vicente Pires), or being effectively planned (such as Samambaia and Águas Claras). Others are the product of an urban development project that did not foresee a sustainable future for the large number of migrants who headed to the Brazilian capital. In this way, a large part of the RAs today suffer the consequences of the development model of the previous paradigm: pollution, excess of individual motor vehicles, increased distance between home and work, concentration of uses, environmental degradation, violence, among others. The center periphery model is dominant and the existing model, of dormitory towns, with a high concentration of employment in the protected area, produces strong vehicular growth given the low quality of the public transport service provided in the city. Among the adverse effects generated by the increase in vehicles, two can be mentioned that strongly impact the population: increase in the amount of pollutants in the air and increase in temperature, both due to the emission of heated gases by vehicles, which also interfere with the effect of the urban heat islands. In the DF, as in the rest of the country, the tendency of the socio-economic organization to be reflected in space is confirmed by the differences between the RAs and the Plano Piloto. The Plano Piloto concentrates the best housing, services, job offers, infrastructure, leisure options and health and education services. In Lucio Costa's view, Brasília should remain an eminently political-administrative city, and its transformation into a large metropolis would not be interesting, as, in this case, there would be a risk of distorting its primary function. The new neighborhoods should form a unity with the existing set, ratifying the character of a "park city", as characterized by him, which would be a differentiator between Brasília and other Brazilian metropolises. Lucio Costa tried to ensure in document Brasília Revisitada "that which should be preserved", verifying which areas are suitable for residential occupation within the Lake Paranoá Basin and close to the Plano Piloto. Urban green The Federal District was built in the Cerrado biome, the second largest biome in the country. The predominance of oxisols and 11 main types of vegetation are recorded: forest formations (Mata Ciliar, Mata de Galeria, Mata Seca and Cerradão), savanna (Cerrado stricto sensu , Parque de Cerrado, Palmeiral and Vereda) and grassland (Campo Sujo, Campo Limpo and Campo Rupestre) (Ribeiro and Walter, 2008 ). In the urban area, the scarcity of vegetation is a differentiating factor between the Administrative Regions, which unfortunately negatively affects the living conditions in peripheral areas. For the socioeconomically disadvantaged classes, only the peripheries of poor and deteriorated environments are left. Outside the Plano Piloto, there is a lack of green areas, either in the phase of elaboration of the urban plan, of implantation or in another moment of the establishment of the urban population. Detailing this picture, the Territorial Observatory of the Government of the Federal District (GDF-SEDUH, 2021) published an indicator of urban tree-shrub coverage, consolidating 31.76 m²/inhabitant. The indicator is based on the area of tree and shrub vegetation in the perimeter of the effective urban occupation, understood by the territorial portion with urban, formal and informal characteristics, considering lots, roads, highways and their domain strips, common areas, open areas, green areas and urban parks. The Plano Piloto has the greatest extension of tree-shrub coverage and RA Varjão has the smallest. Dividing this extension by the number of inhabitants, Park Way reaches the first position with 736.34 m²/inhabitant and Varjão is in the last position with 4.73 m²/inhabitant, both values quite displaced in relation to the DF average (Fig. 2 ). Green areas can be just grassy spaces, without significant photosynthetic activity, but the existence of these areas makes it possible that at some point there is vegetation in the place. When there is no provision for these green areas, the future existence of vegetation is compromised, as there is no place to insert vegetation if the ground is built or paved. An extremely worrying fact, given that one of the consequences generated by the process of occupation and development in the metropolises is the phenomenon of the urban heat island, which occurs precisely in regions with exposed soil. In these places, quantities of hot air are present in greater concentration, as well as in the center of cities. And these are the conditions that make evaporation difficult and reduce the dispersion power of the generated atmospheric pollutants, bringing complications to a good occupation. The rapid process of Brazilian urbanization, which combined determinants of external capitalist expansion with favorable internal conditions, constitutes an overwhelming movement from a social, cultural and environmental point of view. Thinking and working environmentally supposes the construction, development and application of a new rationality, of a whole revision of theory and social praxis to understand the origin, manifestations and implications of the social dynamics of all interrelationships and permanent and indissoluble interactions between the human environment, the natural environment and the built environment. These forms of thinking and working are essential at this moment, when they could be associated with the new categories of mobility, and the development of new centralities. Climate Change Global climate changes are occurring and the initiatives to mitigate the harmful effects on human health resulting from these changes are presented in a discreet way and do not follow the urgency of the environmental crisis. In this sense, special attention should be given to cities, after all, the urban centers currently house more than half of the human life on the planet. Regarding Brazil, climate trends (SEMA, 2016) point to a drier and warmer country by the end of the 21st century, especially in Brazilian cities, where 85% of the country's population live. The IPCC's penultimate report already brought worrying predictions regarding the planet's climate. According to it, the average global temperature should increase between 1.8ºC and 4ºC by 2100 (IPCC, 2014). In this report, four possible greenhouse gas emission and concentration scenarios were presented by 2100, called Representative Concentration Pathways (RCPs), named scenarios RCP2,6, RCP4,5, RCP6.0 and RCP8.5, which are labeled as a possible range of radiative forcing values in the year 2100 (2.6; 4.5; 6.0 and 8.5 W/m², respectively). According to the fifth IPCC report (AR5), the projections up to 2100, in the worst case, indicated that the temperature increase in the inlands of Brazil should be up to 4ºC and, for regions close to the coast, up to 3ºC. The study by Marengo (2014) showed that in all regions of Brazil there will be an increase in temperature and heat waves according to the projections made until 2100. With the increase in the occurrence of heat waves in Brazil, the concern about the health and well-being of the population is evident. Studies show that with these projections, mortality should increase even more in different regions of the world, as well as in Brazil, with capitals such as São Paulo, Rio de Janeiro, Manaus, Recife, Porto Alegre and Brasília already having a high occurrence of heat waves, indicating a tendency to worsen in the coming years (Lopes; Floravanti, 2017). Corroborating these indications, recently Gobo et al. ( 2022 ), in a spatialization of thermal comfort indices for the state of São Paulo, found a significant increase in heat discomfort for the near future (2050–2080) and for the distant future (2070–2100). In comparison with the IPCC AR5 (2013), which reported that it was "extremely likely" that human influence was the preponderant cause of the warming observed since the mid-20th century", the latest IPCC report (IPCC AR6, 2021) states that it is unequivocal that human action, through the emission of greenhouse gases (GHG) originated mainly from the burning of fossil fuels for energy generation and, especially in Brazil, by changes in land use and cover (deforestation), is heating the climate system, causing widespread, rapid and irreversible changes (IPCC AR6, 2021). Numerical simulations from the IPCC AR6 indicate that the northern region of South America will gradually become hotter and drier as the global temperature increases, which would have important impacts on water, energy and food security. The central region of South America, where most of the Brazilian agribusiness is concentrated, should register a greater increase in temperature and an increase in the frequency and intensity of heat waves, in addition to longer dry periods, becoming, in addition to warmer, susceptible to more climatic extremes related to water. Brasília was the place chosen since the end of the 19th century mainly for its climatic conditions (Romero, 2011), and the bioclimatic characteristics of the Plano Piloto developed by urban planner Lucio Costa have a vast number of lessons to be taught to urban planning resilient to extreme heat. However, the disorderly growth has changed the climate of the Federal District (SEMA, 2016). According to the 2016 Inventory of Greenhouse Gas Emissions - GHG, by the Environment Department (SEMA), alongside the goal of reducing deforestation and decisions to strengthen human removals by sinks of greenhouse gases in the territory of the DF, the DF Climate Law also determined the internalization of the climate dimension in the planning of the road network of the different modes of transport. In the period surveyed (2005–2012) most of the emissions were CO2 (carbon dioxide), which represented more than 70%. This correlates with the significant increase in the vehicle fleet in the same period. According to data from Denatran for 2016, in just ten years, from 2005 to 2015, the fleet doubled, and the growth curve is higher than that of the population. The scope aspect mentioned in the previous paragraph stems from the mobilization and use of principles and knowledge not only of architecture, but also of the environment and sustainability. In November 2016, the District Panel on Climate Change of the Environment Department of the Government of the Federal District released the technical note addressed to public policy makers entitled "Climate Changes in the DF and RIDE – Detection and Projections of Climate Change for the Federal District and Integrated Development Region of the DF and Surrounding Area (RIDE)". In this report there are narratives of heat waves that alarmed residents and caused inconvenience in Brasília in 2014, when the thermometers reached 40°C in some parts of the city and relative humidity reached 18%, according to the Environment Department of the Federal District in data from 2016. This report brings climate modeling data (downscale) with a resolution of 30km x 30km. Although considered of low precision, this modeling showed a positive trend of increase in the minimum temperature (TmiN) along the historical data series, computing an increase of 1.85°C. That is, the average minimum temperatures are less cold in the Federal District, showing its warming (SEMA, 2016). The way urban is manufactured is one of the main drivers of this change. The excessive advance in the territory with urban use fragments the landscape, exerts pressure on the ecosystems; in this sense, mitigation policies for the effects of climate change are necessary. Adaptation strategies should include guidelines for the built environment, such as urban coverage elements (built-up, vegetation, water, pavements and free soil, in percentages of soil permeability), urban materials (constructions and natural materials) and the urban metabolism (water, heat and anthropogenic activities). The same SEMA study detected in the last 50 years, confirming the signs of climate projections, an increase in the number of days with relative humidity below 30%, and there was an increase of 0.85°C in the maximum temperature and a decrease in thermal amplitude between the maximum and minimum temperatures. In 2016 there was an extreme rain event and in recent years there have also been heat waves. These successive records of heat and lack of humidity facilitate the combustion of typical cerrado vegetation, intensifying forest fires. The recommendations of the SEMA study include 15 items considered essential, among which we highlight those that recommend mobilizing knowledge-generating centers for the scientific production of climate research aimed at the DF and RIDE; deepening of scientific investigations focused on the local scale, as a way of subsidizing local public policies and promoting strategies for communicating climate risk and dealing with climate change to the entire population of the DF and RIDE and creation of a District Scientific Panel on climate change. Strategic urban plans can incorporate climate risks and vulnerabilities, and for that, assessments need to be carried out, including issues of densification, drainage, wind permeability, water distribution and vegetation within the urban fabric. In order to evaluate the intra-urban distribution of surface temperature and vegetation, satellite images and remote sensing techniques were used to generate thematic maps. The next section will discuss these maps as well as an exploratory analysis of spatial data to identify areas where surface temperature has positive, negative or zero correlation. Land Surface Temperature Distribution and Vegetation Index The surface temperature was computed from Landsat8 satellite images. Google Earth Engine was used to run an open source script (Nill et al., 2019) to retrieve the average LST and Enhanced Vegetation Index EVI for the year 2020. The observation time of each scene from Landsat8 to Brasília was close to 13:00 UTC. For data integration, a regular grid of 100x100 meters was created, delimited by the urban macrozone of the DF. The maps were processed according to the weather seasons (Fig. 3 and Fig. 4). Based on the surface temperature distribution, peripheral urban areas can be observed that are potentially warmer than areas in the process of consolidation, the Plano Piloto and residential areas around Lake Paranoá. In highly impermeable regions, areas with exposed soil, airport and cultivated areas, thermal variations also occur, reaching surface temperatures above 35°C. Lake Paranoá is a highlight, with a milder temperature. In the Plano Piloto, it is possible to identify a contrast between the Asa Sul and the Eixo Monumental, with a surface temperature variation of around 6°C. Asa Sul was the first to be built and has more trees along its perimeters. The tropical landscape of the poor urban peripheries does not offer any shading element (Fig. 5 ). An example is the RA Itapoã, which emerged in the late 1990s as a result of irregular land occupation. The high urban density and land occupation rate make it difficult to implement green infrastructure. The region has practically no trees and vegetated surfaces, with a predominance of waterproofed surfaces. Another example is RA Paranoá, with prevailing temperatures in the range of 31 to 35ºC in the built-up areas, and its location, between two green areas and Lake Paranoá, allows us to observe a thermal variation of approximately 12ºC in relation to its surroundings. Exploratory spatial data analysis Exploratory spatial data analysis is a method in descriptive statistics that seeks to identify patterns and interdependence between variables in a data set. With this technique, the spatial dependence of the surface temperature distribution of the urban area of the Federal District was evaluated, considering the two climatic seasons defined by the rainy season and the dry season. To this end, global and local indicators are used to ascertain the special dependence of an attribute on a region, in this case the surface temperature, and the values of the same attribute in neighboring regions. The global indicator provides a single value as a measure of spatial association for the entire dataset, characterizing the study region as a whole (Anselin, 2020 ). However, due to the large number of grids within the study region, it is assumed that there are different regimes of spatial dependence related to the different locations of the distribution of the study variable (surface temperature). Thus, the local indicator is used, which examines patterns in more detail, allowing the formation of clusters. Both indicators are established considering the values of the nearest neighbors according to a neighborhood matrix (W). As it is a non-parametric sample, the permutation test was applied to verify that the results do not occur by chance. These procedures were performed in the Geoda program using the global and local Moran Index (I), which represents a spatial autocorrelation, with a first-order "queen" neighborhood matrix. The autocorrelation results for the same season (summer or winter) of the year indicate high spatial dependence on surface temperature, with a global Moran index in the range of 0.9 in both climatic seasons. These results can be observed in scatterplots, cluster maps and significance maps (Fig. 6). The HH (high-high) and LL (low-low) quadrants represent clusters that contribute to positive autocorrelation. That is, areas that have a greater presence of vegetation, as well as their surroundings, showed positive spatial autocorrelation (LL). The areas with higher built density and low vegetation index showed positive spatial autocorrelation of the HH type. Areas with heterogeneous urban surfaces (water mosaic, buildings, vegetation – eg residential areas of Plano Piloto) did not present significant results. Public Health The examination of the environmental performance of urban structures and open spaces at their different scales is complex, covering elements, in addition to urban green, that have spatial, temporal and seasonal variability. Performance decisively influences the quality and quantity of use of urban environments, making it necessary, therefore, to know the comfort conditions in these spaces, which will be obtained here through studies on micro-climate, local climate and on human responses to these conditions in the communities selected to participate in the research. Land use and occupation as part of the mitigation strategy in urban areas are still poorly explored. There is a lack of studies and proposals in the built environment, whether on the scale of large urban structures, on the scale of neighborhoods, sectors or areas, on the scale of the place or on the scale of buildings (Romero, 2006 ). Within the social determinants of health (SDH), there are environmental conditions that influence places, populations and the population's health-disease process in different ways. The field of analysis that encompasses the relationship between the atmospheric environment integrated with the surface and human health is human bioclimatology/biometeorology, which increasingly prioritizes cities, given that they were fundamental in raising services and infrastructure for the well-being of the population, as well as the increase in life expectancy. Paradoxically, urban growth was also responsible for the increase in cases of pathologies and the emergence and reemergence of diseases (GOUVEIA, 1999 ). The effects of the physical and chemical components of the atmosphere on human physiology are combined and on biometeorology, according to Jendritzky et al. (1994, p. 247), there are three main fields of action: "the complex conditions of human heat exchange in order to maintain thermal balance, short- and long-wave radiation fluxes, and atmospheric pollution". Knowledge of the physical/natural dimension of climate analysis as a geographic phenomenon in the intertropical zone is important for understanding the scenarios of climate change at the local and microclimatic scale and how the materialization of the production of urban space with dense social inequalities, in most cases, overloads the risk to collective health, especially for social groups in situations of vulnerability. In recent decades, there has been an increase in hospitalizations and mortality due to cardiovascular and respiratory diseases in Brazil and in the world. According to the Unified Health System Database (DATASUS), for the period from 2008 to 2018, in Brazil, the main groups of causes for hospitalizations were: first, pregnancy, childbirth and puerperium; second, respiratory diseases; and third, circulatory diseases. However, mortality data for the same period indicated that the group of circulatory diseases, and then the group of respiratory diseases, are in the first and second position, respectively, for causes of death in the country. Respiratory and cardiovascular diseases are associated with modern life in cities; in this context, the urban climate acts as a risk, due to the occurrence of heat islands, thermal discomfort, atmospheric pollution, as it potentiates, as a result of socio-spatial inequality, heterogeneous conditions in social groups to the occurrence of different health problems. Several studies have shown an increase in hospitalizations and deaths from respiratory and cardiovascular diseases in Brazil, aggravated by thermal discomfort and climatic extremes (Aleixo, 2012; Ikefuti et al., 2017; Murara, 2010; Silva e Ribeiro, 2012; Ribeiro, 2005 ). The classification presented in Fig. 7 shows the South American capitals that will suffer the maximum heat stress in the summer, from 2010 to 2090, with Brasília being first place for the scenarios of 2030, 2050 and 2070, and 2nd place in the scenario projected for 2090. Thermal comfort is measured with the Universal Thermal Climate Index, UTCI, taking into account not only temperature, but also humidity, wind and radiation and all factors that significantly affect the human body. To calculate each classification of Fig. 7, Lobelia Earth created the UTCI Data Projections dataset. To calculate future UTCI fields, climate projections of the different variables involved in the UTCI calculation were used, such as the CMIP5 of the ACCESS1-0 model (RCP8.5) ranging from the year 2005 to 2100. The different classifications are calculated for different months of the year and different times of day when UTCI values can reach maximum or minimum values With growing concern about the harmful effects of air pollution on the health of the population, researchers have also found statistically significant associations between increases in pollution levels (mainly particulate matter, CO and SO₂) and increases in mortality and hospitalization for respiratory and cardiovascular diseases in children and the elderly (Martins et al., 2004; Rodrigues et al., 2017). However, the predominance of the spatial focus of the research are the cities of the South and Southeast regions, so it is important to advance in the analysis in urban areas in the Midwest and North of Brazil, with different climatic types and biomes. Thus, the relationship between the urban climate environment, exposure to air pollution, land use and occupation and the distinct vulnerabilities of the urban population are essential in the analysis of the health-disease process. Final remarks In this article, factors associated with the thermal field of the Federal District of Brazil, which houses the new capital of the country, inaugurated in 1960, were discussed. Architect Lucio Costa's project for his Plano Piloto, based mainly on the principles of the Modern Movement, became a landmark for 20th century urbanism. Its design shows unprecedented solutions in the Brazilian context for housing, leisure and the structure of intra-urban space, in addition to the outstanding characteristic of a city-park, so called by the author of the project. However, with the growing urban expansion, including irregular settlements and gated communities that dictate a new morphology, the city is not identified only by its modernist form and function. It was observed, therefore, that intra-urban thermal differences must be understood in the study of urban climate. In order to evaluate the intra-urban distribution of surface temperature and vegetation, satellite images and remote sensing techniques were used to generate thematic maps. Based on this information, an exploratory analysis of spatial data was carried out. The results of the Moran indices pointed to the spatial dependence of the surface temperature, independent of the variability of the climatic seasons. Observing the urban fabric, the trend towards higher surface temperature values is associated with morphological characteristics such as soil occupation rate, absence of vegetation and shade and predominantly waterproofed surfaces. These conditions were identified mainly in the peripheral areas of the Plano Piloto, with morphological characteristics such as a high rate of soil occupation, absence of vegetation and shade and predominantly waterproofed surfaces. In addition to the urban form, the relationship between the urban climate environment, exposure to air pollution, land use and occupation and the distinct vulnerabilities of the urban population are essential in the analysis of the health-disease process. In this aspect, the estimated increase in urban thermal discomfort assessed by the UTCI index provides us with further information that enhances socio-spatial inequality. Although urban climate studies have a broad scientific basis, the application of urban climatology knowledge in urban planning decision-making has still been limited. In this sense, this study contributed to forwarding methods for visualizing spatialized information at the city scale, and which, in future works, can aggregate socio-economic data from the Administrative Regions of the Federal District of Brazil. Declarations Author Contribution DW - conception of the work; analysis, or interpretation of data; statistical analysis; writing—original draft.MR - drafted the work and revised it critically for important intellectual content; writing—review and editing.MC - approved the version to be published; statistical analysis; data geocoding; images analysis.JG - Conceptualization; project administration; supervision; validation; methodology; writing—review and editing. Acknowledgement The 4th author would like to thank the National Council for Scientific and Technological Development (CNPq) for the Productivity Scholarship, Process 306521/2022-9. Data Availability Research data will be provided upon request. Competing Interest declaration The authors have no relevant financial or non-financial interests to disclose. The authors have no conflicts of interest to declare that are relevant to the content of this article. All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript. The authors have no financial or proprietary interests in any material discussed in this article. Funding Declaration The authors did not receive support from any organization for the submitted work. No funding was received to assist with the preparation of this manuscript. No funding was received for conducting this study. No funds, grants, or other support was received. References Aleixo, Natacha Cíntia Regina. 2011. Pelas lentes da Climatologia e da Saúde Pública: Doenças hídricas e respiratórias na cidade de Ribeirão Preto/SP. 2011. Tese (Doutorado em Geografia) – Universidade Estadual Paulista Julio de Mesquita Filho, Presidente Prudente. Anselin, L. 2020. Local spatial autocorrelation. University of Chicago, Center for Spatial Data Science. Available: https://geodacenter.github.io/workbook/6a_local_auto/lab6a.html#fn1 Gartland, L. 2010. Ilhas de calor: como mitigar zonas de calor em áreas urbanas. São Paulo, Oficina de Textos. Gobo, João Paulo Assis et al. 2022. The bioclimate present and future in the state of São Paulo/Brazil: space-time analysis of human thermal comfort. Sustainable Cities and Society, v. 78, p. 103611. Gobo, João Paulo Assis; Galvani, Emerson; Wollmann, Cássio Arthur. 2018. Subjective Human Perception of Open Urban Spaces in the Brazilian Subtropical Climate: A First Approach. Climate, v. 6, n. 2, p. 24. Gouveia, Nelson. (1999). Saúde e meio ambiente nas cidades: Os desafios da saúde ambiental. Rev. Saúde e Sociedade, v.8, n.1, p.49-61. Ikefuti, P. V. ; Barrozo, Ligia Vizeu ; Braga, A. L. Mean air temperature as a risk factor for stroke mortality in São Paulo, Brazil. International journal of biometeorology, v. 62, p. 1-8, 2018. Lombardo, Magda A. 1985. Ilha de calor nas metrópoles: o exemplo de São Paulo. São Paulo: Editora Hucitec. Martins, M. C. H. (2004). Influence of socioeconomic conditions on air pollution adverse health effects in elderly people: an analysis of six regions in Sao Paulo, Brazil. Journal of Epidemiology & Community Health, [S.L.], v. 58, n. 1, p. 41-46. BMJ. Available: http://dx.doi.org/10.1136/jech.58.1.41 Murara, Pedro Germano S.; Amorim, Margarete Cristiane de Costa Trindade. 2010. Clima e saúde: variações atmosféricas e óbitos por doenças cardiovasculares. Revista Brasileira de Climatologia, v. 6, p. 79-92. Nill, L., Ullmann, T., Kneisel, C., Sobiech-Wolf, J. & Baumhauer, R. 2019. Assessing Spatiotemporal Variations of Landsat Land Surface Temperature and Multispectral Indices in the Arctic Mackenzie Delta Region between 1985 and 2018. Remote Sensing. 2019, 11, 2329. Oke, T. R. 1987. Boundary Layer climates. 2 ed. London: Methuen. Ribeiro, H. 2005. Heat Island in São Paulo, Brazil: effects on health. Critical Public Health, Londres, v. 15, n. 2, p. 147-156. Ribeiro, J. F.; Walter, B. M. T. (2008). As Principais Fitofisionomias do Bioma Cerrado. In: SANO, S. M.; ALMEIDA, S. P. de; RIBEIRO, J. F. (Ed.). Cerrado: ecologia e flora. v. 2. Brasília: EMBRAPA-CERRADOS, 2008. 876 p. Rodrigues, Cristina Guimarães et al. (2015). Projeção da mortalidade e internações hospitalares na rede pública de saúde atribuíveis à poluição atmosférica no Estado de São Paulo entre 2012 e 2030. Revista Brasileira de Estudos de Populacao, [S. l.], v. 32, n. 3, p. 489– 509, 2015. Available: https://doi.org/10.1590/S0102-3098201500000029. Romero, M. 2006. O desafio da construção de cidades, Revista Arquitetura e Urbanismo - AU, Ano 21 No 142, Editora PINI, ISSN 0102-8979, pág. 55 – 58, São Paulo. Romero, M. A. B.; Baptista, G. M. de M.; Lima, E. A. de; Werneck, D. R.; Vianna, E. O.; Sales, G. de L. 2019. Mudanças climáticas e ilhas de calor urbanas. 1. ed. Brasília: Universidade de Brasília. Available: http://repositorio.unb.br/handle/10482/34661 SEMA-DF. Secretaria do Meio Ambiente do Governo do Distrito Federal. 2016. Mudanças Climáticas no DF e RIDE. Available: https://www.sema.df.gov.br/wp-conteudo/uploads/2017/09/Nota-T%C3%A9cnica-Mudan%C3%A7as-Clim%C3%A1ticas-no-DF-e-RIDE.pdf Silva, E. N. & Ribeiro, H. (2012). Impact of urban atmospheric environment on hospital admissions in the elderly. Revista de Saúde Pública, v. 46, n. 4, pp. 694-701. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4258681","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":292178314,"identity":"cdca9822-88a1-44ac-89e3-99f15964485a","order_by":0,"name":"Daniela Rocha Werneck","email":"","orcid":"","institution":"University of Brasília","correspondingAuthor":false,"prefix":"","firstName":"Daniela","middleName":"Rocha","lastName":"Werneck","suffix":""},{"id":292178315,"identity":"392603e0-b77e-4756-af99-1742e7d36322","order_by":1,"name":"Marta Adriana Bustos Romero","email":"","orcid":"","institution":"University of Brasília","correspondingAuthor":false,"prefix":"","firstName":"Marta","middleName":"Adriana Bustos","lastName":"Romero","suffix":""},{"id":292178316,"identity":"3fc9c696-0d2d-47d2-a346-dfd6da214107","order_by":2,"name":"Maria Cristina Celuppi","email":"","orcid":"","institution":"Presbiterian University","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"Cristina","lastName":"Celuppi","suffix":""},{"id":292178318,"identity":"bd61f248-5151-4d1a-9fe7-f10f9d0a3d1b","order_by":3,"name":"João Paulo Assis GOBO","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwklEQVRIiWNgGAWjYBACxgYIncDA3gAiQYhoLTwHiNQCAwkMEglQBiHA3N788AHDL5s8fsk3Zg8e7mHIM28g5LCeY8YGjH1pxZKzc8wNEp4xFMscIKRlRoKZBGPP4cQNt3PMJBIOMCTOIOQwxhnp3yBabp4hWgvQcIYfQC03eIjV0nOm2CCxAeiXnrQyoBaJYglCWgzb2zc++PAHGGLsh7dJ/jhgk0dYSwOQSGyD8wlqYGCQB5N/CCscBaNgFIyCEQwAVbZBBuVR4KsAAAAASUVORK5CYII=","orcid":"","institution":"Federal University of Rondônia","correspondingAuthor":true,"prefix":"","firstName":"João","middleName":"Paulo Assis","lastName":"GOBO","suffix":""}],"badges":[],"createdAt":"2024-04-12 15:31:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4258681/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4258681/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":55318222,"identity":"ff7cd0ba-641c-4095-b706-121efc69c17e","added_by":"auto","created_at":"2024-04-25 15:55:00","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":22351,"visible":true,"origin":"","legend":"\u003cp\u003eMap of Federal District of Brazil and the zonal classification of the study area.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-4258681/v1/21157ab81e65b2a518a8aa22.png"},{"id":55318225,"identity":"6826a7b0-5cc7-400d-9a29-82181c64eadd","added_by":"auto","created_at":"2024-04-25 15:55:00","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":830357,"visible":true,"origin":"","legend":"\u003cp\u003eExample of residential areas: Parkway (A), and Varjão (B). Photo: Valmor Filho.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-4258681/v1/b25694cac59f4c18aaef1d7f.png"},{"id":55319952,"identity":"8e871d9e-129c-4d32-9119-4249a0f3e1e9","added_by":"auto","created_at":"2024-04-25 16:03:00","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1266821,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial distribution of LST: (1) Plano Piloto; (2) Guará; (3) Itapuã and Paranoá, and (4) urban area in process of consolidation.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4258681/v1/e4f8b672c533ad79f062574a.png"},{"id":55318227,"identity":"1f8f2656-aabc-4759-9057-14e64338d3b4","added_by":"auto","created_at":"2024-04-25 15:55:00","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":194088,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial distribution of EVI.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-4258681/v1/56fb9609918260d1ff7561d2.png"},{"id":55318228,"identity":"59d069e4-3284-4291-a9c9-b525864efdc8","added_by":"auto","created_at":"2024-04-25 15:55:00","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":683568,"visible":true,"origin":"","legend":"\u003cp\u003eExample of residential areas and the presence of greenery: Plano Piloto – Asa Sul (A), and Itapuã (B). Source: Google Street View, consulted online on the 15\u003csup\u003eth\u003c/sup\u003e of March 2022.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-4258681/v1/dd03b5839b3b0ee847541bc1.png"},{"id":55319951,"identity":"579536ba-31bd-4f8a-9dc8-ca4615399c02","added_by":"auto","created_at":"2024-04-25 16:03:00","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1545275,"visible":true,"origin":"","legend":"\u003cp\u003eLISA map and significance map for the study area.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-4258681/v1/233413a97a67b9a82ec9abd3.png"},{"id":55318224,"identity":"e7dff243-db20-4609-bcd7-e2dae7765b54","added_by":"auto","created_at":"2024-04-25 15:55:00","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":126711,"visible":true,"origin":"","legend":"\u003cp\u003eUTCI graphic. Source: Lobelia Earth.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-4258681/v1/eae6f62319220916da0ef0fb.png"},{"id":55773504,"identity":"e6b6a29b-cc66-470e-ac92-a004b248fd70","added_by":"auto","created_at":"2024-05-02 22:48:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3268443,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4258681/v1/a516437c-2693-4510-bcff-6522731acd9b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Urban expansion and climate change in the Federal District of Brazil","fulltext":[{"header":"Introduction","content":"\u003cp\u003eUrbanization is a constant and growing process that transforms land cover and use and presents concerns of a climatic, ecological, environmental, cultural, historical and socioeconomic nature, considering that the current logic of the economic system and unlimited growth contradicts future predictions of scarcity of resources, energy and spatial limitation. In this context, sustainable cities are essential for the perpetuation and future quality of human life. (Romero et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUrban development produces several impacts related to the urban climate with implications for emissions of pollutants and anthropogenic heat, reduction of natural land cover and changes in land use and occupation patterns. Added to this are the urban morphology, the thermal and optical characteristics of urban materials and changes in ventilation parameters, which contribute to changes in the local climate.\u003c/p\u003e \u003cp\u003eOne of the most outstanding phenomena in urban climatology is the urban heat island (UHI), characterized by warmer urban areas in relation to the surrounding rural areas, which can be observed on the surface, underground and in the urban atmosphere (Oke, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1987\u003c/span\u003e; Lombardo, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1985\u003c/span\u003e; Gartland, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). In this context, the scales of analysis are fundamental for the understanding of climate change in the city, integrating from the microscale to the impacts on the regional climate (Gobo; Galvani; Wollmann, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), that is, when observed in a city, or city fraction, the UHI phenomenon is characterized as a microclimatic condition in which the air temperature is higher, the relative humidity is lower and there is a change in wind speed, rainfall, among others. Thus, the phenomenon of UHI stems from urban densification, characterized by geometries that block the winds and increase the rate of heat absorption, the increase in albedo (given the constant waterproofing of the soil), in addition to the human action of vegetation removal and consequent reduction in evapotranspiration, which in turn represents a significant decrease in relative humidity (ROMERO et al, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, p.13).\u003c/p\u003e \u003cp\u003eThe whole world has been observing the process of climate change, and initiatives to mitigate the harmful effects on human health, biodiversity and sustainability resulting from these changes are presented in a discreet way, not able to keep up with the urgency of the environmental crisis, as observed in Brazil, which assumed voluntary commitments to reduce emissions, however adaptation measures, especially for Brazilian urban areas, end up being unassisted.\u003c/p\u003e \u003cp\u003eIn the context of cities they represent and built environments in general, there is a need for a careful look at the spatial configuration, through the urban structure (the dimensions of buildings, open spaces and the size of roads and streets), urban coverage (built, paved, vegetated, water, bare soil), urban fabric (construction and natural materials) and urban metabolism (heat, water, pollution due to human activities). An adequate treatment of the site must include the dimensions of these aspects, considering that the urbanization process is permanent and intense in the country and thus the understanding of the impact of the urban configuration on the urban climate, on the levels of comfort and on the energy demand of buildings acquires significant importance for urban and regional planning.\u003c/p\u003e \u003cp\u003eIn other words, it is essential to understand the various climate scales and their relationship with the built space, incorporating multidisciplinary knowledge and also analysis and dissemination tools, since the climate is a factor that directly impacts the quality of life. In this article, the connection between the thermal field of the city and vegetation will be presented, analyzing the case of the Federal District of Brazil.\u003c/p\u003e \u003cp\u003eThe first topic presents a characterization of the urban area of the Federal District (DF). Subsequently, issues related to urban green areas, indicators and differences in their intra-urban distribution will be addressed. Third, discussions on climate change, government efforts to understand future scenarios for the DF will be addressed and, at the City scale, the distribution of surface temperature and vegetation will be analyzed. Next, a discussion about urban thermal comfort is presented and, finally, a conclusion with reflections on the key themes of the article and suggestions for future work.\u003c/p\u003e"},{"header":"City Characterization","content":"\u003cp\u003eThe Federal District (DF) of Brazil was planned from its location to the urban design of its Plano Piloto. For a better understanding, the DF is the smallest of the 27 federative units in Brazil and the only one not divided into municipalities. The urban agglomerations that form the DF are called administrative regions (RAs), which are currently 33, in a total area of 5,779,999 km\u0026sup2;. Located in the Midwest region of Brazil, its territory houses the federal capital, Bras\u0026iacute;lia, which is also the seat of the government of the Federal District (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). The location and demarcation of the DF relied on surveys and studies carried out in 1892 by the Comiss\u0026atilde;o Exploradora do Planalto Central do Brasil, an exploratory commission headed by geographer Lu\u0026iacute;s Cruls and, in 1954, another commission, headed by General Jos\u0026eacute; Pessoa, completed the studies already carried out and defined the area of the future capital. From the promise of advancing 50 years in 5, then President Juscelino Kubitschek was the political leader of the modernist urban project created by architect Lucio Costa, which began construction in 1956 and was inaugurated in 1961.\u003c/p\u003e\n\u003cp\u003eSixty-one years later, the DF emerges as the third largest urban center in the country with 3,015,268 inhabitants (IBGE, 2019), behind S\u0026atilde;o Paulo, founded in 1554, and Rio de Janeiro, founded in 1565. Most RAs did not exist before the demarcation of the DF, except for Planaltina and Brazl\u0026acirc;ndia. The other RAs originated from different urbanization processes, either from irregular occupations (such as Itapo\u0026atilde; and Vicente Pires), or being effectively planned (such as Samambaia and \u0026Aacute;guas Claras). Others are the product of an urban development project that did not foresee a sustainable future for the large number of migrants who headed to the Brazilian capital. In this way, a large part of the RAs today suffer the consequences of the development model of the previous paradigm: pollution, excess of individual motor vehicles, increased distance between home and work, concentration of uses, environmental degradation, violence, among others.\u003c/p\u003e\n\u003cp\u003eThe center periphery model is dominant and the existing model, of dormitory towns, with a high concentration of employment in the protected area, produces strong vehicular growth given the low quality of the public transport service provided in the city. Among the adverse effects generated by the increase in vehicles, two can be mentioned that strongly impact the population: increase in the amount of pollutants in the air and increase in temperature, both due to the emission of heated gases by vehicles, which also interfere with the effect of the urban heat islands.\u003c/p\u003e\n\u003cp\u003eIn the DF, as in the rest of the country, the tendency of the socio-economic organization to be reflected in space is confirmed by the differences between the RAs and the Plano Piloto. The Plano Piloto concentrates the best housing, services, job offers, infrastructure, leisure options and health and education services. In Lucio Costa's view, Bras\u0026iacute;lia should remain an eminently political-administrative city, and its transformation into a large metropolis would not be interesting, as, in this case, there would be a risk of distorting its primary function. The new neighborhoods should form a unity with the existing set, ratifying the character of a \"park city\", as characterized by him, which would be a differentiator between Bras\u0026iacute;lia and other Brazilian metropolises. Lucio Costa tried to ensure in document \u003cem\u003eBras\u0026iacute;lia Revisitada\u003c/em\u003e \"that which should be preserved\", verifying which areas are suitable for residential occupation within the Lake Parano\u0026aacute; Basin and close to the Plano Piloto.\u003c/p\u003e"},{"header":"Urban green","content":"\u003cp\u003eThe Federal District was built in the Cerrado biome, the second largest biome in the country. The predominance of oxisols and 11 main types of vegetation are recorded: forest formations (Mata Ciliar, Mata de Galeria, Mata Seca and Cerrad\u0026atilde;o), savanna (Cerrado \u003cem\u003estricto sensu\u003c/em\u003e, Parque de Cerrado, Palmeiral and Vereda) and grassland (Campo Sujo, Campo Limpo and Campo Rupestre) (Ribeiro and Walter, \u003cspan class=\"CitationRef\"\u003e2008\u003c/span\u003e). In the urban area, the scarcity of vegetation is a differentiating factor between the Administrative Regions, which unfortunately negatively affects the living conditions in peripheral areas. For the socioeconomically disadvantaged classes, only the peripheries of poor and deteriorated environments are left. Outside the Plano Piloto, there is a lack of green areas, either in the phase of elaboration of the urban plan, of implantation or in another moment of the establishment of the urban population.\u003c/p\u003e\n\u003cp\u003eDetailing this picture, the Territorial Observatory of the Government of the Federal District (GDF-SEDUH, 2021) published an indicator of urban tree-shrub coverage, consolidating 31.76 m\u0026sup2;/inhabitant. The indicator is based on the area of tree and shrub vegetation in the perimeter of the effective urban occupation, understood by the territorial portion with urban, formal and informal characteristics, considering lots, roads, highways and their domain strips, common areas, open areas, green areas and urban parks. The Plano Piloto has the greatest extension of tree-shrub coverage and RA Varj\u0026atilde;o has the smallest. Dividing this extension by the number of inhabitants, Park Way reaches the first position with 736.34 m\u0026sup2;/inhabitant and Varj\u0026atilde;o is in the last position with 4.73 m\u0026sup2;/inhabitant, both values quite displaced in relation to the DF average (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eGreen areas can be just grassy spaces, without significant photosynthetic activity, but the existence of these areas makes it possible that at some point there is vegetation in the place. When there is no provision for these green areas, the future existence of vegetation is compromised, as there is no place to insert vegetation if the ground is built or paved.\u003c/p\u003e\n\u003cp\u003eAn extremely worrying fact, given that one of the consequences generated by the process of occupation and development in the metropolises is the phenomenon of the urban heat island, which occurs precisely in regions with exposed soil. In these places, quantities of hot air are present in greater concentration, as well as in the center of cities. And these are the conditions that make evaporation difficult and reduce the dispersion power of the generated atmospheric pollutants, bringing complications to a good occupation.\u003c/p\u003e\n\u003cp\u003eThe rapid process of Brazilian urbanization, which combined determinants of external capitalist expansion with favorable internal conditions, constitutes an overwhelming movement from a social, cultural and environmental point of view. Thinking and working environmentally supposes the construction, development and application of a new rationality, of a whole revision of theory and social praxis to understand the origin, manifestations and implications of the social dynamics of all interrelationships and permanent and indissoluble interactions between the human environment, the natural environment and the built environment. These forms of thinking and working are essential at this moment, when they could be associated with the new categories of mobility, and the development of new centralities.\u003c/p\u003e"},{"header":"Climate Change ","content":"\u003cp\u003eGlobal climate changes are occurring and the initiatives to mitigate the harmful effects on human health resulting from these changes are presented in a discreet way and do not follow the urgency of the environmental crisis. In this sense, special attention should be given to cities, after all, the urban centers currently house more than half of the human life on the planet. Regarding Brazil, climate trends (SEMA, 2016) point to a drier and warmer country by the end of the 21st century, especially in Brazilian cities, where 85% of the country's population live.\u003c/p\u003e\n\u003cp\u003eThe IPCC's penultimate report already brought worrying predictions regarding the planet's climate. According to it, the average global temperature should increase between 1.8\u0026ordm;C and 4\u0026ordm;C by 2100 (IPCC, 2014). In this report, four possible greenhouse gas emission and concentration scenarios were presented by 2100, called Representative Concentration Pathways (RCPs), named scenarios RCP2,6, RCP4,5, RCP6.0 and RCP8.5, which are labeled as a possible range of radiative forcing values in the year 2100 (2.6; 4.5; 6.0 and 8.5 W/m\u0026sup2;, respectively).\u003c/p\u003e\n\u003cp\u003eAccording to the fifth IPCC report (AR5), the projections up to 2100, in the worst case, indicated that the temperature increase in the inlands of Brazil should be up to 4\u0026ordm;C and, for regions close to the coast, up to 3\u0026ordm;C. The study by Marengo (2014) showed that in all regions of Brazil there will be an increase in temperature and heat waves according to the projections made until 2100.\u003c/p\u003e\n\u003cp\u003eWith the increase in the occurrence of heat waves in Brazil, the concern about the health and well-being of the population is evident. Studies show that with these projections, mortality should increase even more in different regions of the world, as well as in Brazil, with capitals such as S\u0026atilde;o Paulo, Rio de Janeiro, Manaus, Recife, Porto Alegre and Bras\u0026iacute;lia already having a high occurrence of heat waves, indicating a tendency to worsen in the coming years (Lopes; Floravanti, 2017). Corroborating these indications, recently Gobo et al. (\u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e), in a spatialization of thermal comfort indices for the state of S\u0026atilde;o Paulo, found a significant increase in heat discomfort for the near future (2050\u0026ndash;2080) and for the distant future (2070\u0026ndash;2100). In comparison with the IPCC AR5 (2013), which reported that it was \"extremely likely\" that human influence was the preponderant cause of the warming observed since the mid-20th century\", the latest IPCC report (IPCC AR6, 2021) states that it is unequivocal that human action, through the emission of greenhouse gases (GHG) originated mainly from the burning of fossil fuels for energy generation and, especially in Brazil, by changes in land use and cover (deforestation), is heating the climate system, causing widespread, rapid and irreversible changes (IPCC AR6, 2021).\u003c/p\u003e\n\u003cp\u003eNumerical simulations from the IPCC AR6 indicate that the northern region of South America will gradually become hotter and drier as the global temperature increases, which would have important impacts on water, energy and food security. The central region of South America, where most of the Brazilian agribusiness is concentrated, should register a greater increase in temperature and an increase in the frequency and intensity of heat waves, in addition to longer dry periods, becoming, in addition to warmer, susceptible to more climatic extremes related to water.\u003c/p\u003e\n\u003cp\u003eBras\u0026iacute;lia was the place chosen since the end of the 19th century mainly for its climatic conditions (Romero, 2011), and the bioclimatic characteristics of the Plano Piloto developed by urban planner Lucio Costa have a vast number of lessons to be taught to urban planning resilient to extreme heat. However, the disorderly growth has changed the climate of the Federal District (SEMA, 2016).\u003c/p\u003e\n\u003cp\u003eAccording to the 2016 Inventory of Greenhouse Gas Emissions - GHG, by the Environment Department (SEMA), alongside the goal of reducing deforestation and decisions to strengthen human removals by sinks of greenhouse gases in the territory of the DF, the DF Climate Law also determined the internalization of the climate dimension in the planning of the road network of the different modes of transport. In the period surveyed (2005\u0026ndash;2012) most of the emissions were CO2 (carbon dioxide), which represented more than 70%. This correlates with the significant increase in the vehicle fleet in the same period. According to data from Denatran for 2016, in just ten years, from 2005 to 2015, the fleet doubled, and the growth curve is higher than that of the population.\u003c/p\u003e\n\u003cp\u003eThe scope aspect mentioned in the previous paragraph stems from the mobilization and use of principles and knowledge not only of architecture, but also of the environment and sustainability. In November 2016, the District Panel on Climate Change of the Environment Department of the Government of the Federal District released the technical note addressed to public policy makers entitled \"Climate Changes in the DF and RIDE \u0026ndash; Detection and Projections of Climate Change for the Federal District and Integrated Development Region of the DF and Surrounding Area (RIDE)\". In this report there are narratives of heat waves that alarmed residents and caused inconvenience in Bras\u0026iacute;lia in 2014, when the thermometers reached 40\u0026deg;C in some parts of the city and relative humidity reached 18%, according to the Environment Department of the Federal District in data from 2016.\u003c/p\u003e\n\u003cp\u003eThis report brings climate modeling data (downscale) with a resolution of 30km x 30km. Although considered of low precision, this modeling showed a positive trend of increase in the minimum temperature (TmiN) along the historical data series, computing an increase of 1.85\u0026deg;C. That is, the average minimum temperatures are less cold in the Federal District, showing its warming (SEMA, 2016). The way urban is manufactured is one of the main drivers of this change. The excessive advance in the territory with urban use fragments the landscape, exerts pressure on the ecosystems; in this sense, mitigation policies for the effects of climate change are necessary.\u003c/p\u003e\n\u003cp\u003eAdaptation strategies should include guidelines for the built environment, such as urban coverage elements (built-up, vegetation, water, pavements and free soil, in percentages of soil permeability), urban materials (constructions and natural materials) and the urban metabolism (water, heat and anthropogenic activities). The same SEMA study detected in the last 50 years, confirming the signs of climate projections, an increase in the number of days with relative humidity below 30%, and there was an increase of 0.85\u0026deg;C in the maximum temperature and a decrease in thermal amplitude between the maximum and minimum temperatures.\u003c/p\u003e\n\u003cp\u003eIn 2016 there was an extreme rain event and in recent years there have also been heat waves. These successive records of heat and lack of humidity facilitate the combustion of typical cerrado vegetation, intensifying forest fires. The recommendations of the SEMA study include 15 items considered essential, among which we highlight those that recommend mobilizing knowledge-generating centers for the scientific production of climate research aimed at the DF and RIDE; deepening of scientific investigations focused on the local scale, as a way of subsidizing local public policies and promoting strategies for communicating climate risk and dealing with climate change to the entire population of the DF and RIDE and creation of a District Scientific Panel on climate change. Strategic urban plans can incorporate climate risks and vulnerabilities, and for that, assessments need to be carried out, including issues of densification, drainage, wind permeability, water distribution and vegetation within the urban fabric.\u003c/p\u003e\n\u003cp\u003eIn order to evaluate the intra-urban distribution of surface temperature and vegetation, satellite images and remote sensing techniques were used to generate thematic maps. The next section will discuss these maps as well as an exploratory analysis of spatial data to identify areas where surface temperature has positive, negative or zero correlation.\u003c/p\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n\u003ch3\u003eLand Surface Temperature Distribution and Vegetation Index\u003c/h3\u003e\n\u003cp\u003eThe surface temperature was computed from Landsat8 satellite images. Google Earth Engine was used to run an open source script (Nill et al., 2019) to retrieve the average LST and Enhanced Vegetation Index EVI for the year 2020. The observation time of each scene from Landsat8 to Bras\u0026iacute;lia was close to 13:00 UTC. For data integration, a regular grid of 100x100 meters was created, delimited by the urban macrozone of the DF. The maps were processed according to the weather seasons (Fig. 3 and Fig. 4).\u003c/p\u003e\n\u003cp\u003eBased on the surface temperature distribution, peripheral urban areas can be observed that are potentially warmer than areas in the process of consolidation, the Plano Piloto and residential areas around Lake Parano\u0026aacute;. In highly impermeable regions, areas with exposed soil, airport and cultivated areas, thermal variations also occur, reaching surface temperatures above 35\u0026deg;C. Lake Parano\u0026aacute; is a highlight, with a milder temperature.\u003c/p\u003e\n\u003cp\u003eIn the Plano Piloto, it is possible to identify a contrast between the Asa Sul and the Eixo Monumental, with a surface temperature variation of around 6\u0026deg;C. Asa Sul was the first to be built and has more trees along its perimeters. The tropical landscape of the poor urban peripheries does not offer any shading element (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eAn example is the RA Itapo\u0026atilde;, which emerged in the late 1990s as a result of irregular land occupation. The high urban density and land occupation rate make it difficult to implement green infrastructure. The region has practically no trees and vegetated surfaces, with a predominance of waterproofed surfaces. Another example is RA Parano\u0026aacute;, with prevailing temperatures in the range of 31 to 35\u0026ordm;C in the built-up areas, and its location, between two green areas and Lake Parano\u0026aacute;, allows us to observe a thermal variation of approximately 12\u0026ordm;C in relation to its surroundings.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eExploratory spatial data analysis\u003c/h3\u003e\n\u003cp\u003eExploratory spatial data analysis is a method in descriptive statistics that seeks to identify patterns and interdependence between variables in a data set. With this technique, the spatial dependence of the surface temperature distribution of the urban area of the Federal District was evaluated, considering the two climatic seasons defined by the rainy season and the dry season. To this end, global and local indicators are used to ascertain the special dependence of an attribute on a region, in this case the surface temperature, and the values of the same attribute in neighboring regions.\u003c/p\u003e\n\u003cp\u003eThe global indicator provides a single value as a measure of spatial association for the entire dataset, characterizing the study region as a whole (Anselin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, due to the large number of grids within the study region, it is assumed that there are different regimes of spatial dependence related to the different locations of the distribution of the study variable (surface temperature). Thus, the local indicator is used, which examines patterns in more detail, allowing the formation of clusters.\u003c/p\u003e\n\u003cp\u003eBoth indicators are established considering the values of the nearest neighbors according to a neighborhood matrix (W). As it is a non-parametric sample, the permutation test was applied to verify that the results do not occur by chance. These procedures were performed in the Geoda program using the global and local Moran Index (I), which represents a spatial autocorrelation, with a first-order \"queen\" neighborhood matrix.\u003c/p\u003e\n\u003cp\u003eThe autocorrelation results for the same season (summer or winter) of the year indicate high spatial dependence on surface temperature, with a global Moran index in the range of 0.9 in both climatic seasons. These results can be observed in scatterplots, cluster maps and significance maps (Fig.\u0026nbsp;6). The HH (high-high) and LL (low-low) quadrants represent clusters that contribute to positive autocorrelation. That is, areas that have a greater presence of vegetation, as well as their surroundings, showed positive spatial autocorrelation (LL). The areas with higher built density and low vegetation index showed positive spatial autocorrelation of the HH type. Areas with heterogeneous urban surfaces (water mosaic, buildings, vegetation \u0026ndash; eg residential areas of Plano Piloto) did not present significant results.\u003c/p\u003e\n\u003ch3\u003ePublic Health\u003c/h3\u003e\n\u003cp\u003eThe examination of the environmental performance of urban structures and open spaces at their different scales is complex, covering elements, in addition to urban green, that have spatial, temporal and seasonal variability. Performance decisively influences the quality and quantity of use of urban environments, making it necessary, therefore, to know the comfort conditions in these spaces, which will be obtained here through studies on micro-climate, local climate and on human responses to these conditions in the communities selected to participate in the research.\u003c/p\u003e\n\u003cp\u003eLand use and occupation as part of the mitigation strategy in urban areas are still poorly explored. There is a lack of studies and proposals in the built environment, whether on the scale of large urban structures, on the scale of neighborhoods, sectors or areas, on the scale of the place or on the scale of buildings (Romero, \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eWithin the social determinants of health (SDH), there are environmental conditions that influence places, populations and the population's health-disease process in different ways. The field of analysis that encompasses the relationship between the atmospheric environment integrated with the surface and human health is human bioclimatology/biometeorology, which increasingly prioritizes cities, given that they were fundamental in raising services and infrastructure for the well-being of the population, as well as the increase in life expectancy. Paradoxically, urban growth was also responsible for the increase in cases of pathologies and the emergence and reemergence of diseases (GOUVEIA, \u003cspan class=\"CitationRef\"\u003e1999\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eThe effects of the physical and chemical components of the atmosphere on human physiology are combined and on biometeorology, according to Jendritzky et al. (1994, p. 247), there are three main fields of action: \"the complex conditions of human heat exchange in order to maintain thermal balance, short- and long-wave radiation fluxes, and atmospheric pollution\".\u003c/p\u003e\n\u003cp\u003eKnowledge of the physical/natural dimension of climate analysis as a geographic phenomenon in the intertropical zone is important for understanding the scenarios of climate change at the local and microclimatic scale and how the materialization of the production of urban space with dense social inequalities, in most cases, overloads the risk to collective health, especially for social groups in situations of vulnerability.\u003c/p\u003e\n\u003cp\u003eIn recent decades, there has been an increase in hospitalizations and mortality due to cardiovascular and respiratory diseases in Brazil and in the world. According to the Unified Health System Database (DATASUS), for the period from 2008 to 2018, in Brazil, the main groups of causes for hospitalizations were: first, pregnancy, childbirth and puerperium; second, respiratory diseases; and third, circulatory diseases. However, mortality data for the same period indicated that the group of circulatory diseases, and then the group of respiratory diseases, are in the first and second position, respectively, for causes of death in the country.\u003c/p\u003e\n\u003cp\u003eRespiratory and cardiovascular diseases are associated with modern life in cities; in this context, the urban climate acts as a risk, due to the occurrence of heat islands, thermal discomfort, atmospheric pollution, as it potentiates, as a result of socio-spatial inequality, heterogeneous conditions in social groups to the occurrence of different health problems.\u003c/p\u003e\n\u003cp\u003eSeveral studies have shown an increase in hospitalizations and deaths from respiratory and cardiovascular diseases in Brazil, aggravated by thermal discomfort and climatic extremes (Aleixo, 2012; Ikefuti et al., 2017; Murara, 2010; Silva e Ribeiro, 2012; Ribeiro, \u003cspan class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eThe classification presented in Fig.\u0026nbsp;7 shows the South American capitals that will suffer the maximum heat stress in the summer, from 2010 to 2090, with Bras\u0026iacute;lia being first place for the scenarios of 2030, 2050 and 2070, and 2nd place in the scenario projected for 2090. Thermal comfort is measured with the Universal Thermal Climate Index, UTCI, taking into account not only temperature, but also humidity, wind and radiation and all factors that significantly affect the human body.\u003c/p\u003e\n\u003cp\u003eTo calculate each classification of Fig.\u0026nbsp;7, Lobelia Earth created the UTCI Data Projections dataset. To calculate future UTCI fields, climate projections of the different variables involved in the UTCI calculation were used, such as the CMIP5 of the ACCESS1-0 model (RCP8.5) ranging from the year 2005 to 2100. The different classifications are calculated for different months of the year and different times of day when UTCI values can reach maximum or minimum values\u003c/p\u003e\n\u003cp\u003eWith growing concern about the harmful effects of air pollution on the health of the population, researchers have also found statistically significant associations between increases in pollution levels (mainly particulate matter, CO and SO₂) and increases in mortality and hospitalization for respiratory and cardiovascular diseases in children and the elderly (Martins et al., 2004; Rodrigues et al., 2017). However, the predominance of the spatial focus of the research are the cities of the South and Southeast regions, so it is important to advance in the analysis in urban areas in the Midwest and North of Brazil, with different climatic types and biomes.\u003c/p\u003e\n\u003cp\u003eThus, the relationship between the urban climate environment, exposure to air pollution, land use and occupation and the distinct vulnerabilities of the urban population are essential in the analysis of the health-disease process.\u003c/p\u003e"},{"header":"Final remarks","content":"\u003cp\u003eIn this article, factors associated with the thermal field of the Federal District of Brazil, which houses the new capital of the country, inaugurated in 1960, were discussed. Architect Lucio Costa's project for his Plano Piloto, based mainly on the principles of the Modern Movement, became a landmark for 20th century urbanism. Its design shows unprecedented solutions in the Brazilian context for housing, leisure and the structure of intra-urban space, in addition to the outstanding characteristic of a city-park, so called by the author of the project. However, with the growing urban expansion, including irregular settlements and gated communities that dictate a new morphology, the city is not identified only by its modernist form and function.\u003c/p\u003e\n\u003cp\u003eIt was observed, therefore, that intra-urban thermal differences must be understood in the study of urban climate. In order to evaluate the intra-urban distribution of surface temperature and vegetation, satellite images and remote sensing techniques were used to generate thematic maps. Based on this information, an exploratory analysis of spatial data was carried out. The results of the Moran indices pointed to the spatial dependence of the surface temperature, independent of the variability of the climatic seasons.\u003c/p\u003e\n\u003cp\u003eObserving the urban fabric, the trend towards higher surface temperature values is associated with morphological characteristics such as soil occupation rate, absence of vegetation and shade and predominantly waterproofed surfaces. These conditions were identified mainly in the peripheral areas of the Plano Piloto, with morphological characteristics such as a high rate of soil occupation, absence of vegetation and shade and predominantly waterproofed surfaces. In addition to the urban form, the relationship between the urban climate environment, exposure to air pollution, land use and occupation and the distinct vulnerabilities of the urban population are essential in the analysis of the health-disease process. In this aspect, the estimated increase in urban thermal discomfort assessed by the UTCI index provides us with further information that enhances socio-spatial inequality.\u003c/p\u003e\n\u003cp\u003eAlthough urban climate studies have a broad scientific basis, the application of urban climatology knowledge in urban planning decision-making has still been limited. In this sense, this study contributed to forwarding methods for visualizing spatialized information at the city scale, and which, in future works, can aggregate socio-economic data from the Administrative Regions of the Federal District of Brazil.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eDW - conception of the work; analysis, or interpretation of data; statistical analysis; writing\u0026mdash;original draft.MR - drafted the work and revised it critically for important intellectual content; writing\u0026mdash;review and editing.MC - approved the version to be published; statistical analysis; data geocoding; images analysis.JG - Conceptualization; project administration; supervision; validation; methodology; writing\u0026mdash;review and editing.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe 4th author would like to thank the National Council for Scientific and Technological Development (CNPq) for the Productivity Scholarship, Process 306521/2022-9.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eResearch data will be provided upon request.\u003c/p\u003e\n\u003ch2\u003eCompeting Interest declaration\u003c/h2\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose. The authors have no conflicts of interest to declare that are relevant to the content of this article. All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript. The authors have no financial or proprietary interests in any material discussed in this article.\u003c/p\u003e\n\u003ch2\u003eFunding Declaration\u003c/h2\u003e\n\u003cp\u003eThe authors did not receive support from any organization for the submitted work. No funding was received to assist with the preparation of this manuscript. No funding was received for conducting this study. No funds, grants, or other support was received.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAleixo, Natacha C\u0026iacute;ntia Regina. 2011. Pelas lentes da Climatologia e da Sa\u0026uacute;de P\u0026uacute;blica: Doen\u0026ccedil;as h\u0026iacute;dricas e respirat\u0026oacute;rias na cidade de Ribeir\u0026atilde;o Preto/SP. 2011. Tese (Doutorado em Geografia) \u0026ndash; Universidade Estadual Paulista Julio de Mesquita Filho, Presidente Prudente.\u003c/li\u003e\n\u003cli\u003eAnselin, L. 2020. Local spatial autocorrelation. University of Chicago, Center for Spatial Data Science. Available: https://geodacenter.github.io/workbook/6a_local_auto/lab6a.html#fn1\u003c/li\u003e\n\u003cli\u003eGartland, L. 2010. Ilhas de calor: como mitigar zonas de calor em \u0026aacute;reas urbanas. S\u0026atilde;o Paulo, Oficina de Textos.\u003c/li\u003e\n\u003cli\u003eGobo, Jo\u0026atilde;o Paulo Assis et al. 2022. The bioclimate present and future in the state of S\u0026atilde;o Paulo/Brazil: space-time analysis of human thermal comfort. Sustainable Cities and Society, v. 78, p. 103611.\u003c/li\u003e\n\u003cli\u003eGobo, Jo\u0026atilde;o Paulo Assis; Galvani, Emerson; Wollmann, C\u0026aacute;ssio Arthur. 2018. Subjective Human Perception of Open Urban Spaces in the Brazilian Subtropical Climate: A First Approach. Climate, v. 6, n. 2, p. 24.\u003c/li\u003e\n\u003cli\u003eGouveia, Nelson. (1999). Sa\u0026uacute;de e meio ambiente nas cidades: Os desafios da sa\u0026uacute;de ambiental. Rev. Sa\u0026uacute;de e Sociedade, v.8, n.1, p.49-61.\u003c/li\u003e\n\u003cli\u003eIkefuti, P. V. ; Barrozo, Ligia Vizeu ; Braga, A. L. Mean air temperature as a risk factor for stroke mortality in S\u0026atilde;o Paulo, Brazil. International journal of biometeorology, v. 62, p. 1-8, 2018.\u003c/li\u003e\n\u003cli\u003eLombardo, Magda A. 1985. Ilha de calor nas metr\u0026oacute;poles: o exemplo de S\u0026atilde;o Paulo. S\u0026atilde;o Paulo: Editora Hucitec.\u003c/li\u003e\n\u003cli\u003eMartins, M. C. H. (2004). Influence of socioeconomic conditions on air pollution adverse health effects in elderly people: an analysis of six regions in Sao Paulo, Brazil. Journal of Epidemiology \u0026amp; Community Health, [S.L.], v. 58, n. 1, p. 41-46. BMJ. Available: http://dx.doi.org/10.1136/jech.58.1.41\u003c/li\u003e\n\u003cli\u003eMurara, Pedro Germano S.; Amorim, Margarete Cristiane de Costa Trindade. 2010. Clima e sa\u0026uacute;de: varia\u0026ccedil;\u0026otilde;es atmosf\u0026eacute;ricas e \u0026oacute;bitos por doen\u0026ccedil;as cardiovasculares. Revista Brasileira de Climatologia, v. 6, p. 79-92.\u003c/li\u003e\n\u003cli\u003eNill, L., Ullmann, T., Kneisel, C., Sobiech-Wolf, J. \u0026amp; Baumhauer, R. 2019. Assessing Spatiotemporal Variations of Landsat Land Surface Temperature and Multispectral Indices in the Arctic Mackenzie Delta Region between 1985 and 2018. Remote Sensing. 2019, 11, 2329. \u003c/li\u003e\n\u003cli\u003eOke, T. R. 1987. Boundary Layer climates. 2 ed. London: Methuen.\u003c/li\u003e\n\u003cli\u003eRibeiro, H. 2005. Heat Island in S\u0026atilde;o Paulo, Brazil: effects on health. Critical Public Health, Londres, v. 15, n. 2, p. 147-156.\u003c/li\u003e\n\u003cli\u003eRibeiro, J. F.; Walter, B. M. T. (2008). As Principais Fitofisionomias do Bioma Cerrado. In: SANO, S. M.; ALMEIDA, S. P. de; RIBEIRO, J. F. (Ed.). Cerrado: ecologia e flora. v. 2. Bras\u0026iacute;lia: EMBRAPA-CERRADOS, 2008. 876 p.\u003c/li\u003e\n\u003cli\u003eRodrigues, Cristina Guimar\u0026atilde;es et al. (2015). Proje\u0026ccedil;\u0026atilde;o da mortalidade e interna\u0026ccedil;\u0026otilde;es hospitalares na rede p\u0026uacute;blica de sa\u0026uacute;de atribu\u0026iacute;veis \u0026agrave; polui\u0026ccedil;\u0026atilde;o atmosf\u0026eacute;rica no Estado de S\u0026atilde;o Paulo entre 2012 e 2030. Revista Brasileira de Estudos de Populacao, [S. l.], v. 32, n. 3, p. 489\u0026ndash; 509, 2015. Available: https://doi.org/10.1590/S0102-3098201500000029.\u003c/li\u003e\n\u003cli\u003eRomero, M. 2006. O desafio da constru\u0026ccedil;\u0026atilde;o de cidades, Revista Arquitetura e Urbanismo - AU, Ano 21 No 142, Editora PINI, ISSN 0102-8979, p\u0026aacute;g. 55 \u0026ndash; 58, S\u0026atilde;o Paulo. \u003c/li\u003e\n\u003cli\u003eRomero, M. A. B.; Baptista, G. M. de M.; Lima, E. A. de; Werneck, D. R.; Vianna, E. O.; Sales, G. de L. 2019. Mudan\u0026ccedil;as clim\u0026aacute;ticas e ilhas de calor urbanas. 1. ed. Bras\u0026iacute;lia: Universidade de Bras\u0026iacute;lia. Available: http://repositorio.unb.br/handle/10482/34661\u003c/li\u003e\n\u003cli\u003eSEMA-DF. Secretaria do Meio Ambiente do Governo do Distrito Federal. 2016. Mudan\u0026ccedil;as Clim\u0026aacute;ticas no DF e RIDE. Available: https://www.sema.df.gov.br/wp-conteudo/uploads/2017/09/Nota-T%C3%A9cnica-Mudan%C3%A7as-Clim%C3%A1ticas-no-DF-e-RIDE.pdf\u003c/li\u003e\n\u003cli\u003eSilva, E. N. \u0026amp; Ribeiro, H. (2012). Impact of urban atmospheric environment on hospital admissions in the elderly. Revista de Sa\u0026uacute;de P\u0026uacute;blica, v. 46, n. 4, pp. 694-701.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Urban Climate, Land Surface Temperature, Urban Greening, Intra-urban Heat, Vulnerable Neighborhoods","lastPublishedDoi":"10.21203/rs.3.rs-4258681/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4258681/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBrazil has made a voluntary commitment to reduce greenhouse gas emissions as part of the National Policy on Climate Change, but adaptation and mitigation measures for urban areas to promote climate resilience are still lacking. In this context, this article aims to explore the urban thermal environment of Bras\u0026iacute;lia, Brazil. The city was inaugurated in 1960 and its Plano Piloto is a UNESCO World Heritage Site designed by Lucio Costa based on the principles of the modernist movement. In order to evaluate the intra-urban distribution of surface temperature and vegetation, satellite images and remote sensing techniques were used to generate thematic maps. From this information, an exploratory analysis of spatial data was performed to identify clusters where the surface temperature has positive, negative or null autocorrelation. The results of the Moran indices pointed to the spatial dependence of the surface temperature, independent of the variability of the climatic seasons. Observing the urban fabric, the trend towards higher surface temperature values is associated with morphological characteristics such as soil occupation rate, absence of vegetation and shade and predominantly waterproofed surfaces.\u003c/p\u003e","manuscriptTitle":"Urban expansion and climate change in the Federal District of Brazil","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-25 15:54:55","doi":"10.21203/rs.3.rs-4258681/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"669f16d8-04a0-490c-b187-c8d148c2d236","owner":[],"postedDate":"April 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-05-02T22:39:36+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-25 15:54:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4258681","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4258681","identity":"rs-4258681","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}