Revista Brasileira de Estudos de População
versão impressa ISSN 0102-3098
ABREU, Marcos Vinicius Sanches; OLIVEIRA, Julio Cesar de; ANDRADE, Viviane Delfino Albuquerque e MEIRA, Anderson Donizete. Methodological proposal for spatial calculation and analysis of the intra-urban HDI of Viçosa, Brazil. Rev. bras. estud. popul. [online]. 2011, vol.28, n.1, pp.169-186. ISSN 0102-3098. http://dx.doi.org/10.1590/S0102-30982011000100009.
Analyses of socioeconomic indicators allow a way to read reality that can generate information for urban planning and municipal management. The Human Development Index (HDI) is an important measure of the level of development in a municipality, as it calculates income, education and longevity. However, it is unable to indicate social differences within a municipality. To better understand the question of urban socio-spatiality, the construction of local indicators (such as sectorial HDIs) becomes an important analytic tool. The methodology for calculating this index was adapted to data from the Brazilian Census of 2000, which is arranged in an aggregated way per census sector, which constitute the smallest unit of territorial analysis based on census data. In order to better understand the distribution and spatial continuity of the intra-urban HDI, this article proposes that geo-statistic techniques be applied in conjunction with geo-processing. In this way, researchers have at hand an analysis of the spatial continuity of an intra-urban HDI by using an ordinary geo-statistic kriging interpolator. It thus becomes possible to infer regarding the spatial behavior of human development, which always shows continuous variation in space. It should be stressed that such inferences refer not to local levels of the HDI but rather to trends in the variability of the indicator. The results are considered satisfactory since a spatial reading of intra-urban human development can be made on the basis of secondary data generated by the census.
Palavras-chave : Human Development Index (HDI); Census sector; Spatial statistics; Krigage.