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Examining the Spatial Distribution of Urban Indicators in São Paulo, Brazil: Do Spatial Effects Matter?

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In this chapter, we use two urban indicators to examine intra-urban inequalities in the municipality of São Paulo, Brazil: the Human Development Index (HDI), from the United Nations Development Program, and the Economic Concentration Index (ECI), proposed in this study. Using district-level data, we apply Exploratory Spatial Data Analysis (ESDA) methods that account for spatial effects, that is, spatial autocorrelation and spatial heterogeneity. Spatial autocorrelation occurs when value similarity and locational similarity coincide. Spatial heterogeneity exists when structural changes related to location are detected in the data set, and spatial regimes may be present. We show that spatial autocorrelation and spatial heterogeneity are detected in the spatial distribution of HDI and ECI in São Paulo Municipality, and therefore intra-urban inequalities exist with respect to both urban indicators. The development level varies substantially across districts, and center and periphery are the most obvious spatial regimes characterizing this variation. The ESDA methods described in this study can be adopted by planners to examine different variables, leading to more reliable results based on statistical tests and revealing, more precisely, locations that require more/less attention.
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

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M. Joseph Sirgy, Rhonda Phillips and Don Rahtz (eds.), Community Quality-of-Live Indicators: Best Practices III, 102-124.
©2007 International Society for Quality-of-Life Studies
Abstract
In this chapter, we use two urban indicators to examine intra-urban inequalities in the munici-
pality of São Paulo, Brazil: the Human Development Index (HDI), from the United Nations
Development Program, and the Economic Concentration Index (ECI), proposed in this study.
Using district-level data, we apply Exploratory Spatial Data Analysis (ESDA) methods that
account for spatial effects, that is, spatial autocorrelation and spatial heterogeneity. Spatial
autocorrelation occurs when value similarity and locational similarity coincide. Spatial het-
erogeneity exists when structural changes related to location are detected in the data set, and
spatial regimes may be present. We show that spatial autocorrelation and spatial heterogeneity
are detected in the spatial distribution of HDI and ECI in São Paulo Municipality, and therefore
intra-urban inequalities exist with respect to both urban indicators. The development level var-
ies substantially across districts, and center and periphery are the most obvious spatial regimes
characterizing this variation. The ESDA methods described in this study can be adopted by
planners to examine different variables, leading to more reliable results based on statistical
tests and revealing, more precisely, locations that require more/less attention.
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  
 
 

 
 
 
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
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
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
  
 
 
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 
 
 
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






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





EXAMINING THE SPATIAL DISTRIBUTION OF URBAN INDICATORS IN SÃO PAULO, BRAZIL
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


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
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





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MÔNICA HADDAD
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EXAMINING THE SPATIAL DISTRIBUTION OF URBAN INDICATORS IN SÃO PAULO, BRAZIL
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MÔNICA HADDAD
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
EXAMINING THE SPATIAL DISTRIBUTION OF URBAN INDICATORS IN SÃO PAULO, BRAZIL
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

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







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
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
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MÔNICA HADDAD
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








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
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


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











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EXAMINING THE SPATIAL DISTRIBUTION OF URBAN INDICATORS IN SÃO PAULO, BRAZIL
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


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                
         
        
     
MÔNICA HADDAD
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










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




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






                
         
        
     
EXAMINING THE SPATIAL DISTRIBUTION OF URBAN INDICATORS IN SÃO PAULO, BRAZIL
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

FIGURE 5.3: Moran Scatter Plots for HDI and ECI, 2000
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

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


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
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
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







 



    
      
     
      
     
 
 
 
 
 
 
 
 
 
 
 
 
 
 
     
     
    
     
    
    


     
    


MÔNICA HADDAD
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

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
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



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EXAMINING THE SPATIAL DISTRIBUTION OF URBAN INDICATORS IN SÃO PAULO, BRAZIL
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
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
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
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




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
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

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







 
 
 
 




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










MÔNICA HADDAD
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









EXAMINING THE SPATIAL DISTRIBUTION OF URBAN INDICATORS IN SÃO PAULO, BRAZIL
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






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







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



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EXAMINING THE SPATIAL DISTRIBUTION OF URBAN INDICATORS IN SÃO PAULO, BRAZIL
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
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

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

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EXAMINING THE SPATIAL DISTRIBUTION OF URBAN INDICATORS IN SÃO PAULO, BRAZIL
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
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
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
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MÔNICA HADDAD
... It can be assumed that in line with other studies outlined in Section 2, areal units characterized by high levels of population size and income are likely to more accurately reflect rainfall events in Twitter data. In addition, these variables explain a significant proportion of the intra-urban inequalities in São Paulo (Haddad andNedovićBudić 2006, Haddad 2009). Nonetheless, the structure of spatial dependence among the areal units cannot be modelled or represented directly by population and income, since these variables only address the question of where people live in the sense of a night-time census but do not show the spatial interaction between the units used. ...
... In this manner, we were able to show that the response of social media to rainfall events is not homogeneous across urban space; rather, its spatial heterogeneity is strongly and significantly linked to the problem of intra-urban inequalities. Our results show that the strength of the rainfall-related Twitter activity follows a radial socio-spatial segregation pattern found in related works about the city of São Paulo (Haddad andNedovićBudić 2006, Haddad 2009), thus providing evidence of the fact that there is a persistent 'digital divide' between wealthy people living in central urban areas -with access to information and communication technologiesand poor people living in peripheral areas with more limited access to technology. ...
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Although it is acknowledged that urban inequalities can lead to biases in the production of social media data, there is a lack of studies which make an assessment of the effects of intra-urban movements in real-world urban analytics applications, based on social media. This study investigates the spatial heterogeneity of social media with regard to the regular intra-urban movements of residents by means of a case study of rainfall-related Twitter activity in São Paulo, Brazil. We apply a spatial autoregressive model that uses population and income as covariates and intra-urban mobility flows as spatial weights to explain the spatial distribution of the social response to rainfall events in Twitter vis-à-vis rainfall radar data. Results show high spatial heterogeneity in the response of social media to rainfall events, which is linked to intra-urban inequalities. Our model performance (R2 = 0.80) provides evidence that urban mobility flows and socio-economic indicators are significant factors to explain the spatial heterogeneity of thematic spatiotemporal patterns extracted from social media. Therefore, urban analytics research and practice should consider not only the influence of socio-economic profile of neighborhoods but also the spatial interaction introduced by intra-urban mobility flows to account for spatial heterogeneity when using social media data.
... De igual manera, esta investigación aporta evidencia empírica que se suma a la existente para otros países y regiones que analizan los efectos espaciales en la distribución del IDH, entre ellos los realizados para el estado de Assiut en Egipto (Abdel-Samad, 2010) y el municipio de São Paulo en Brasil (Haddad y Nedović-Budić, 2006;Haddad, 2009). En esta línea, algunos trabajos recientes han realizado aportes en el análisis de la desigualdad regional e interregional del ingreso para las entidades federativas mexicanas (Aroca, Bosh y Maloney, 2005;Rey y Sastré, 2010;Sastré y Rey, 2013); sin embargo, son necesarios los estudios en regiones específi cas y a escalas menores como la municipal. ...
... En realidad tal fenómeno va mucho más allá, sin embargo, la matriz de pesos espaciales a través de la cual se capturó el efecto de dependencia espacial es restrictiva debido a que considera la contigüidad física como único determinante de las interdependencias entre los municipios y deja de lado las posibles infl uencias mutuas entre aquellos que no son físicamente adyacentes, y que pudieran estar estrechamente relacionados. A pesar de esta limitante y en coincidencia con otros autores (Abdel-Samad, 2010;Haddad y Nedović-Budić, 2006;Haddad, 2009), la presente investigación aporta evidencia empírica sobre la relevancia de la dimensión espacial del proceso de desarrollo humano. Por tanto, se sugiere que el nivel de desarrollo humano de algunos municipios oaxaqueños está, en buena medida, determinado por factores internos y de otras condiciones socioeconómicas, culturales, políticas o de otra naturaleza de los municipios vecinos, tal y como lo predice la Ley de la Geografía de Tobler. ...
Article
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El objetivo de este artículo es estudiar la dimensión espacial de las desigualdades intermunicipales del estado de Oaxaca, México, mediante el uso de las técnicas de análisis exploratorio de datos espaciales. A través del estadístico I de Moran global y los indicadores locales de asociación espacial (LISA) se encontró evidencia de autocorrelación espacial significativa así como de heterogeneidad espacial en la distribución municipal del Índice de Desarrollo Humano (IDH) para los años 2000 y 2010. Los resultados sugieren que existen patrones espaciales definidos de desarrollo humano, esto es, la presencia de un esquema de polarización, reflejando que los agrupamientos municipales de alto IDH tienden a concentrar las oportunidades de desarrollo humano; en cambio, los agrupamientos municipales de bajo IDH pueden ser interpretados como trampas espaciales al permanecer rezagados durante el periodo analizado.
... Inequalities in health are a persistent challenge worldwide, as there are considerable variations associated with socioeconomic factors across and within countries [1][2][3], as well as within cities [4,5]. However, most studies focus on country-to-country comparisons, which may not be appropriate for informing local policymaking because data can mask intra-urban differences [6]. ...
Article
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There is considerable evidence pointing to the existence of a socioeconomic gradient in mortality, which tends to be steeper in urban areas. Similar to other European cities, Lisbon is far from homogeneous since considerable geographical inequalities exist between the more advantaged and the more deprived neighborhoods. The main goals of this study are to describe the geographical pattern of premature deaths (before 65 years old), avoidable deaths (preventable and amenable to healthcare) and cause-specific mortality (HIV/AIDS and suicide) in Lisbon, at the lower administrative level (civil parish, in Portuguese: Freguesia), and analyze the statistical association between mortality risk and deprivation, before (1999-2003) and during the economic crisis (2008-2012).Smoothed Standardized Mortality Ratios (sSMR) and Relative Risk (RR) with 95% credible intervals were calculated to identify the association between mortality and deprivation. The analysis of the geographical distribution of cause-specific mortality reveals that civil parishes with high sSMR in the first period continued to present higher mortality rates in the second. Moreover, a significant statistical association was found between all the causes of death and deprivation, except suicide. These findings contribute to understanding how social conditions influence health outcomes and can offer insights about potential policy directions for local government.
... There are papers about indexes of human development and indexes of economic development or even about the distribution of services and facilities and the relation with incomes and poverty. Most of them are interested in analyzing the asymmetry in the distribution of opportunities [43][44][45][46][47]. ...
Article
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From the mapping of urban vegetation cover by high-resolution orthoimages, using IR band and NDVI classification (Normalized Difference Vegetation Index), added to three-dimensional representation obtained by LiDAR capture (Light Detection and Ranging), the volumetric values of vegetal cover are obtained as a base to construct spatial analysis in the district of Pampulha, in Belo Horizonte, investigating the role it plays in the neighborhood. The article aims to analyze the relationship between vegetation cover, income distribution and population density, as a support to urban environmental quality management. It applies Exploratory Spatial Data Analysis (ESDA) to identify the presence of clusters and patterns of spatial distribution and to examine spatial autocorrelation. The results confirm the concentration of vegetation cover in areas of high income and lower population density but the main contribution of the study is the use of a method to analyze the spatial behavior of this distribution. Calculating Moran global index and local index (LISA), these spatial combinations are mainly used to identify transformation pressures, which may result in the definition of priorities for public actions and the construction of proposals for parameterization of vegetation cover to support plans related to green infrastructure in urban areas.
... In the present article, we discuss aspects of one outreach program in Brazil, the Science Stand, which is managed by a pool of public universities 1 and seeks to integrate science and technology activism by promoting educational "practices that aim to be more ethically and politically engaged and socially and environmentally responsive" (Alsop & Bencze, 2014, p. 2) in schools as well as poor (marginalized) communities and public spaces in the São Paulo Macrometropolitan region. This area (also known as "Macrometropole Paulista" [MMP] in Portuguese) 2 corresponds to a radius of about 100 km from São Paulo city and is characterized by a population of approximately 33 million people living in intense socioeconomic inequality (Haddad, 2009). It is the largest urban cluster in the Western hemisphere. ...
Article
Full-text available
This article presents the theoretical and methodological aspects of the activist science and technology education practices of a Brazilian outreach initiative known as Science Stand. This learn-by-doing program is designed to connect science and technology to current global socio-ecological issues – such as animal rights, gender (in)equality, and climate change – through interactive activities created and performed by university students in public spaces located in marginalized communities in the Greater São Paulo Area (Brazil). In addition, we introduce several testimonies from project volunteers that support our argument concerning the role of science activism in advocating gender equity in science, fostering hope in the possibility of socio-ecological change, and promoting the democratization of science through widespread knowledge dissemination.
... In the present article, we discuss aspects of one outreach program in Brazil, the Science Stand, which is managed by a pool of public universities 1 and seeks to integrate science and technology activism by promoting educational "practices that aim to be more ethically and politically engaged and socially and environmentally responsive" (Alsop & Bencze, 2014, p. 2) in schools as well as poor (marginalized) communities and public spaces in the São Paulo Macrometropolitan region. This area (also known as "Macrometropole Paulista" [MMP] in Portuguese) 2 corresponds to a radius of about 100 km from São Paulo city and is characterized by a population of approximately 33 million people living in intense socioeconomic inequality (Haddad, 2009). It is the largest urban cluster in the Western hemisphere. ...
Article
Full-text available
This special issue on topologies of activism was intended to re-centre justice education and activism as central themes of JASTE by inviting a diversity of views from the wider community.
... In the present article, we discuss aspects of one outreach program in Brazil, the Science Stand, which is managed by a pool of public universities 1 and seeks to integrate science and technology activism by promoting educational "practices that aim to be more ethically and politically engaged and socially and environmentally responsive" (Alsop & Bencze, 2014, p. 2) in schools as well as poor (marginalized) communities and public spaces in the São Paulo Macrometropolitan region. This area (also known as "Macrometropole Paulista" [MMP] in Portuguese) 2 corresponds to a radius of about 100 km from São Paulo city and is characterized by a population of approximately 33 million people living in intense socioeconomic inequality (Haddad, 2009). It is the largest urban cluster in the Western hemisphere. ...
Article
Full-text available
This article presents the theoretical and methodological aspects of the activist science and technology education practices of a Brazilian outreach initiative known as Science Stand. This learn-by-doing program is designed to connect science and technology to current global socio-ecological issues-such as animal rights, gender (in)equality, and climate change-through interactive activities created and performed by university students in public spaces located in marginalized communities in the Greater São Paulo Area (Brazil). In addition, we introduce several testimonies from project volunteers that support our argument concerning the role of science activism in advocating gender equity in science, fostering hope in the possibility of socio-ecological change, and promoting the democratization of science through widespread knowledge dissemination.
... Spatial heterogeneity exists when structural changes related to location are detected in the data set, implying unstable relationships between values of observations, and detectable spatial regimes (Haddad, 2009). These relationships are described by a multiplicity of functional forms and parameters that vary across the data set (Anselin, 1988). ...
Chapter
In this chapter the reader will learn how to answer the following questions:
Thesis
Full-text available
ANÁLISE ESPACIAL DE ESTRUTURAS INTRA-URBANAS: O CASO DE SÃO PAULO
Book
1: Introduction.- 2: The Scope of Spatial Econometrics.- 3: The Formal Expression of Spatial Effects.- 4: A Typology of Spatial Econometric Models.- 5: Spatial Stochastic Processes: Terminology and General Properties.- 6: The Maximum Likelihood Approach to Spatial Process Models.- 7: Alternative Approaches to Inference in Spatial Process Models.- 8: Spatial Dependence in Regression Error Terms.- 9: Spatial Heterogeneity.- 10: Models in Space and Time.- 11: Problem Areas in Estimation and Testing for Spatial Process Models.- 12: Operational Issues and Empirical Applications.- 13: Model Validation and Specification Tests in Spatial Econometric Models.- 14: Model Selection in Spatial Econometric Models.- 15: Conclusions.- References.
Chapter
In this first chapter in Part I, I outline the scope of the book in more detail, and describe the meaning of some important terms in an informal manner.
Article
European integration has stimulated numerous studies of regional economic convergence within the European Union in recent macroeconomic and regional science literature (e.g. Abraham and Von Rompuy 1995; Armstrong 1995a; Neven and Gouyette 1995; Martin 2001). Most of the time, the empirical methods that have been used are identical to the methods employed in international studies. However, spatial effects, particularly spatial autocorrelation and spatial heterogeneity, must be taken into account when analyzing the convergence process at regional scale. There are number of factors — trade between regions, technology, knowledge diffusion and more generally regional spillovers — that lead to geographically dependent regions. Because of spatial interactions between regions, geographical location is important in accounting for the economic performances of regions. Yet for all its importance, the role of spatial effects in convergence processes has only been recently examined using the appropriate spatial statistic and econometric methods (Armstrong 1995b; Fingleton 1999; López-Bazo et al. 1999, for European regions; Rey and Montouri 1999; Rey 2001, for US states).
Article
Spatial analysis is statistically and substantively important for macrolevel criminological inquiry. Using county-level data for the decennial years in the 1960 to 1990 time period, we reexamine the impact of conventional structural covariates on homicide rates and explicitly model spatial effects. Important findings are: (1) homicide is strongly clustered in space; (2) this clustering cannot be completely explained by common measures of the structural similarity of neighboring counties; (3) noteworthy regional differences are observed in the effects of structural covariates on homicide rates; and (4) evidence consistent with a diffusion process for homicide is observed in the South throughout the 1960-1990 period.