Abstract
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.
Highlights
Information on the size, composition, and pace of population change has been the subject of increasing interest in the public sector, for economic policy and for policy-making in other areas, including health, education, sustainability, and the environment
One of the biggest problems in producing population estimates in urban areas is industrial complexes. Their occupation profile is marked by scattered residences, but they are normally classified as having a high degree of urbanization due to the dense road networks and extensive impermeable areas, which result in spectral behaviors consistent with areas of intense occupation [29]
The results showed that the application of the models to the Geelong district reached R2 = 0.84 and the linear correlation coefficient was equal to 0.92 between the estimated and actual values of the population density, while the median error was 17.4% in the training sample and 18.4% in the external validation
Summary
Information on the size, composition, and pace of population change has been the subject of increasing interest in the public sector, for economic policy and for policy-making in other areas, including health, education, sustainability, and the environment. The most complete and reliable type of source for data on the population of countries and their geographical subdivisions has been a census based on household interviews. Census information is limited due to high costs, despite the growing demand for more detailed information, as the social and economic demands on governments become increasingly complex [1,2,3,4,5]. Alternative sources of information are used, such as sample surveys ( expensive), civil records (especially for the enumeration of vital statistics), school censuses, and various government registries, this information is not available for most countries (or its administrative subdivisions). There are problems with underreporting and the quality of information is sometimes lacking [1,2,3]
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