Abstract
Abstract: This paper aimed to use the dasymetric mapping methods proposed by Mennis and Hultgreen (2006) and Strauch and Ajara (2015) to estimate the variation of the distribution in the population in the Jacarepaguá Watershed. For this, population data from the census tracts of 2010 and, as auxiliary data, the map of land use and land cover obtained from the supervised classification, were used - the auxiliary data were obtained using a maximum likelihood method with high resolution images. The method proposed by Mennis and Hultgreen (2006) preserved the pycnophylactic capacity of the dasymetric mapping; however, it resulted in a dasymetric map that distributes the population among the pixels, in accordance with the population variables, and in a more homogeneous way, since it considers only two classes of urban use and occupation. In the Strauch and Ajara (2015) method, there was a loss of 0.04% of the original population, but it emphasized the density differences, by distributing the population heterogeneously, because it allows the specialist to include other classes of land use and land cover and attribute different types of weights to these classes.
Highlights
Knowledge of urban growth and, the spatial distribution of a population and its density, is relevant for the management and ordering of a territory
The aim of this paper was to develop a demographic density model that serves as a support for the conducting of analyses of organized spaces, and the ordering of issues related to urban planning in the Jacarepaguá Watershed
The Jacarepaguá Watershed was obtained from the CEPERJ Foundation of Rio de Janeiro, while the administrative regions of the municipality of Rio de Janeiro was obtained from the Pereira Passos Institute (IPP, 2015)
Summary
Knowledge of urban growth and, the spatial distribution of a population and its density, is relevant for the management and ordering of a territory. Confidentiality being one of them, population data are represented by choropleth maps that assume a constant value for the whole operational area of the census; that is, the census tract. This type of representation generates two kinds of distortions (Sleeter and Gould, 2007). Knowing the population density in risk areas, or understanding the population in order to plan public health, education, and public safety strategies. Population density mapping is an important tool for public managers in the decision-making process
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