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Population estimation by remote sensing (POPSATER)

Projet de recherche SR/00/126 (Action de recherche SR)


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Description :

Objective

An accurate knowledge of the state and dynamics of a population is a major prerequisite for a sound management of social and economic development; it is also an important specific tool, essential for the management of critical situations involving huge population displacements (wars, disasters …).
Unfortunately, many countries, especially in Africa, only have at their disposal scarce scattered population data: population censuses are taken every ten year in the best case, and results come late and provide seldom if ever the expected regional detail; very few surveys are designed in a way suitable for the expected kind of data; the scope of most surveys is narrow (reproduction, public health), their regional coverage is often limited and its results are anyway unusable because of sample size; questionnaires and field procedures are often unclear and quite unreliable; finally, administrative data (population registers) are virtually non existing in most countries.

Method

Since the late nineties, VHR images supplement the range of remote sensing data (aerial photographs, satellite images in several resolutions …). They have quickly been felt to be a new opportunity for a better knowledge of population. However, it is obvious that « everything » may not be seen from space (e.g. number of persons living in a house and their characteristics); but we also lack of methods enabling us to infer most of the invisible characteristics from remote sensing data.
The idea of a new partnership came to three actors sharing these issues from several sides: KEYOBS s.a. is a private company supplying geographical products and services in developing countries; SIGTEL is a research unit from the Université Libre de Bruxelles (Free University Brussels), oriented towards geographical information systems and remote sensing; ADRASS is a nonprofit research organisation specialised in population studies, field data collection, analysis and modelling of socio-demographic data.


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