Abstract
The collection of census data is an important task with respect to providing support for decision makers. However, the collection of census data is also resource intensive. This is especially the case in areas which feature poor communication and transport networks. In this paper a method is proposed for collecting census data by applying classification techniques to relevant satellite imagery. The test site for the work is a collection of villages lying some 300km to the northwest of Addis Ababa in Ethiopia. The idea is to build a classifier that can label households according to “family” size. To this end training data has been obtained, by collecting on ground census data and aligning this up with satellite data. The fundamental idea is to segment satellite images so as to obtain the satellite pixels describing individual households and representing these segmentations using a histogram representation. By pairing each histogram represented household with collated census data, namely family size, a classifier can be constructed to predict household sizes according to the nature of the histograms. This classifier can then be used to provide a quick and easy mechanism for the approximate collection of census data that does not require significant resource.
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Dittakan, K., Coenen, F., Christley, R. (2012). Towards The Collection of Census Data From Satellite Imagery Using Data Mining: A Study With Respect to the Ethiopian Hinterland. In: Bramer, M., Petridis, M. (eds) Research and Development in Intelligent Systems XXIX. SGAI 2012. Springer, London. https://doi.org/10.1007/978-1-4471-4739-8_31
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DOI: https://doi.org/10.1007/978-1-4471-4739-8_31
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