Urban and environmental transformations in poor areas of the metropolitan region of Recife (Brazil)

Anjos, Kainara Lira dos; Lacerda, Norma

doi:10.1590/1809-4422asoc516v1812015en

Cited by 3 publications

(1 citation statement)

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“…The following indicators from the Demographic Census (IBGE, 2011) were considered: water supply, destination of garbage and sewage, as household information; and income, education and longevity, as population information. Each indicator shows an amount of sub-indicators with specific information, the management of these data represents an adaptation of works developed by Anjos and Lacerda (2015), which guided the calculation of averages and the allocation of weights for each sub-indicator.…”

Section: Delimitation Criteriamentioning

confidence: 99%

Automatic detection of deprived urban areas using Google Earth™ images of cities from the Brazilian semi-arid region

Pereira

Filho

Simões

et al. 2022

urbe, Rev. Bras. Gest. Urbana

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Automatic classification of deprived urban areas provides vital information for implementing pro-poor policies. In this paper, an approach for the classification of these areas in Brazilian cities is presented. Satellite images were obtained free of charge from six cities in the Brazilian semi-arid region using Google Earth Engine software. To assess the discriminative power of census data, data made publicly available by Brazilian Institute of Geography and Statistics (IBGE) were used to train SVM classifiers together with features extracted from images. The image features were extracted using the following approaches: color histograms, LBP histograms, and lacunarity. Four evaluation tests were investigated based on two criteria: use of census data and cross-validation method. Two types of cross-validation were used: 10-fold and leave-one-city-out. The use of census data caused a negative impact on the results. This impact is justified by the criteria on which census tracts are mapped in the country, not only morphological and visually perceptible through satellite images, as opposed to adopted extraction approaches. The best results obtained were average accuracy of 91.81% and average F1-score of 92.27%. This research contributes to the recognition of deprived urban areas and urban socio-spatial dynamics, supporting urban-territorial planning.

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Section: Delimitation Criteriamentioning

confidence: 99%

Automatic detection of deprived urban areas using Google Earth™ images of cities from the Brazilian semi-arid region

Pereira

Filho

Simões

et al. 2022

urbe, Rev. Bras. Gest. Urbana

View full text Add to dashboard Cite

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Exploring the connection between spatial justice and land tenure security: insights from inclusive urban (re)development schemes in Recife, Brazil

Uwayezu

Vries

2020

GeoJournal

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Metropolitan Regions: Challenges for Sustainability and Governance of Periurban Areas in Brazil.

Coy¹,

Sandholz²,

Töpfer³

et al. 2018

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Metropolization has become a global phenomenon of urbanization. In a highly urbanized country like Brazil this process is visible in mega cities as well as in regional metropoles, leading to vast urbanized areas stretching from the core cities to formerly distant neighborhood municipalities. Enormous urban agglomerations like the Macrometropole Paulista are the impressive result, however coming with significant challenges in governing such huge but highly fragmented areas. Especially the most populous Brazilian metropolitan areas have to deal with peri-urban development challenges like the lack of infrastructure and public security or new forms of fragmentation that come along with social and ecological problems. Overcoming these challenges is a remarkable task for the municipal, regional and national level. Based on a classification of different phases of peri-urban development that can be distinguished since the 1960s this paper analyses the development of Brazil’s metropolitan areas. Different forms of governance as well as concepts of sustainable approaches to deal with urban challenges are assessed based on the cases of Sao Paulo, Curitiba and Recife.

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Urban and environmental transformations in poor areas of the metropolitan region of Recife (Brazil)

Cited by 3 publications

References 0 publications

Automatic detection of deprived urban areas using Google Earth™ images of cities from the Brazilian semi-arid region

Automatic detection of deprived urban areas using Google Earth™ images of cities from the Brazilian semi-arid region

Exploring the connection between spatial justice and land tenure security: insights from inclusive urban (re)development schemes in Recife, Brazil

Metropolitan Regions: Challenges for Sustainability and Governance of Periurban Areas in Brazil.

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