O entendimento do fenômeno da segregação é essencial ao planejamento urbano. Os índices espaciais de segregação são métricas que permitem identificar os padrões espaciais de segregação de diferentes grupos populacionais e sua variação espacial dentro da cidade. Neste artigo, índices espaciais globais e locais de segregação espacial foram aplicados à cidade de Marília-SP. A análise dos índices locais revelou que a segregação de Marília não pode mais ser classificada com padrão clássico centro-periferia. Ainda que grupos de baixa renda se concentrem nas periferias (zonas sul e nordeste), Marília apresenta um padrão de macro segregação diferenciado, com a consolidação do setor que vai do centro histórico à zona leste, no qual população de alta renda está agrupada. O estudo também revelou um alto grau de segregação (isolamento) da população de alta renda na zona leste (condomínios fechados) e de baixa renda na zona sul (favelas e conjuntos habitacionais), reforçados pelo índice insignificante de exposição entre os grupos opostos na zona sul da cidade.

Urban segregation represents a significant barrier to achieving social inclusion in cities. Its cartographic representation is important to measure the evolution of this serious urban phenomenon. This paper aims to map the susceptibility to socio-spatial segregation in Marília/SP (Brazil). The method of calculating the informative value and susceptibility was adapted to measure the segregation of the urban area of the city. As per the final map validation, the success rate was 93%; this methodological adaptation presented great potential and can contribute to the urban planning activities.

The understanding of intraurban space in cities requires the observation and identification of the relationship between spatial patterns for the unveiling of its contents to understand the processes involved in the production and reproduction of these spaces. Thematic land cover/land use maps and social indicators maps are commonly used to acquire information on the existing spatial patterns, they are an important data source for land planning and management, and hence, are crucial in zoning projects. This research aims to correlate intraurban land cover classification maps from the city of Marília/SP developed from high resolution satellite images using the image analysis based on objects (GEOBIA) method with the indices and social indicators of quality of life, environmental quality, education and socioeconomic level for inferences about the quality of life and socio spatial segregation in the city of Marília/SP. For the spatial distribution and processing of the quantitative and qualitative data, geoprocessing techniques were applied, through the use of a Geographic Information System, statistical techniques and remote sensing, which allowed spatial analysis of data created. The results were presented and the proposed method was demonstrated promising to be applied in updating intraurban space information to support urban planning and land management and, consequently, contribute to improving the population's quality of life.