4.6 Article

Population Estimates from Orbital Data of Medium Spatial Resolution: Applications for a Brazilian Municipality

Journal

SUSTAINABILITY
Volume 12, Issue 9, Pages -

Publisher

MDPI
DOI: 10.3390/su12093565

Keywords

remote sensing; dasymetric mapping; population estimates; small areas; Brazil; sustainable development

Funding

  1. National Council for Scientific and Technological Development(CNPq/Ph.D. Scholarship Program)
  2. National Institute for Space Research (INPE)
  3. Graduate Program in Demography/UFMG/PROEX/Coordination for the Improvement of Higher Education Personnel (CAPES)

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In recent decades, there has been an increase in the search for more detailed information on population dynamics, given the growing demand for more sustainable economic, social, and environmental planning. The dissemination of Geographic Information Systems (GIS) has contributed to the development of methodologies for the field of population estimates for small areas. To support more sustainable policies, this study aims to evaluate the capacity and contribution of the orbital images (Landsat ETM+) for the production of post-census population estimates for the municipality of Contagem, Minas Gerais, Brazil. Firstly, models were built using the average of the reflectance of the spectral bands of the Landsat 7 ETM+ for each special intra-municipal unit, called the census sector, as explanatory variables for the population density. Secondly, this study constructed models that use the reflectance and the distributed population at the level of the pixels of the images. All models were tested through internal validation procedures, external validation, and comparative analyses with post-census estimates. Internal validation presented excellent results (below 7%), while in external validation, the method at the level of the pixels presented consistent results, below 1% relative error. These results provide useful clues and can help policymakers in the development of more sustainable and effective public policies, insofar as population estimates are extremely important for the planning of any society.

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