Population Density Estimations for Disaster Management: Case Study Rural Zimbabwe
This paper tackles the need of enhanced population data for disaster management and aid delivery studies in developing countries. It analyses the usefulness of a set of spatial data layers, including medium resolution satellite imagery, for population density estimations in rural Zimbabwe. The exercise conducted on a 185 × 185km area at a grid cell size of 150m allowed us to develop a methodology that can be extended to the whole of Zimbabwe.
The surface modelling of population density was implemented by integrating 4 main variables: land use, settlements, road network, and slopes. During the modelling procedure, pixel weighting values were allocated according to pre-defined decision rules. In a final step the district population counts of the recent Zimbabwean census were distributed among all pixels of the relevant district according to the pixel weighting values. The resulting land use information and population data can be linked to vulnerability and food insecurity.
In order to be transferred to other countries, the modelling procedure needs to be adapted to case specific characteristics, the determination of which requires a certain level of local / expert knowledge. In addition, passive sensors might not provide sufficient cloud free satellite data for regions lying within the moist tropics.
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- Adeniyi PO (1983) An Aerial Photographic Method for Estimating Urban Population. Photogrammetric Engineering and Remote Sensing 49, pp 545–560Google Scholar
- Chen K (2002) An approach to linking remotely sensed data and areal census data. International Journal of Remote Sensing 23, pp 37–48Google Scholar
- Deichmann U (1996) A review of spatial population database design and modeling. Technical Report 96-3. National Center for Geographic Information and Analysis, Santa Barbara, USAGoogle Scholar
- Eicher CL, Brewer CA (2001) Dasymetric Mapping and Areal Interpolation: Implementation and Evaluation. Cartography and Geographic Information Science 28, pp 125–138Google Scholar
- Elvidge CK, Baugh E, Kihn H, Kroehl ED, Davis C (1997) Relation between satellite observed visible-near infrared emissions, population, economic activity and electric power consumption. International Journal of Remote Sensing 18, pp 1373–1379Google Scholar
- Giada S, De Groeve T, Ehrlich D, Soille P (2003a) Information extraction from very high resolution satellite imagery over the Lukole refugee camp, Tanzania. International Journal of Remote Sensing 24, pp 4251–4266Google Scholar
- Giada S, De Groeve T, Ehrlich D, Soille P (2003b) Can satellite images provide useful information on refugee camps? International Journal of Remote Sensing 24, pp 4249–4250.Google Scholar
- Holloway SR, Schumacher J, Redmond RL (1999) People and Place: Dasymetric Mapping Using ARC/INFO. In: Morain S (ed) GIS Solutions in Natural Resource Management, Onword Press, Santa Fe, New Mexico, pp 283–291Google Scholar
- Langford M, Maguire D, Unwin DJ (1991) The areal interpolation problem: estimating population using remote sensing in a GIS framework. In: Masser I, Blakemore M. (eds) Handling Geographical Information: Methodology and Potential Applications, Longman, New York, pp 55–77Google Scholar
- Langford M, Unwin DJ (1994) Generating and mapping population density surfaces within a geographical information system. Cartographic Journal 31(1), pp 21–6Google Scholar
- Lo CP (2003) Zone-based estimation of population and housing units from satellite-generated land use/land cover maps. In: Mesev V (ed) Remotely Sensed Cities, Taylor & Francis, London, pp 157–180Google Scholar
- Mennis J (2003) Generating Surface Models of Population Using Dasymetric Mapping. The Professional Geographer 55, pp 31–42Google Scholar
- Mesev V (2003) Remotely Sensed Cities (ed), Taylor & Francis, London, pp 372Google Scholar
- Mugnier C (2003): Grids and Datums, Republic of Zimbabwe. In: Photogrammetric Engineering and Remote Sensing 69, pp 1206–1207Google Scholar
- Olorunfemi JF (1984) Land Use and Population: A Linking Model. Photogrammetric Engineering and Remote Sensing 50, pp 221–227Google Scholar
- Sutton P, Roberts D, Elvidge C, Meij H (1997) A Comparison of Nighttime Satellite Imagery and Population Density for the Continental United States. Photogrammetric Engineering and Remote Sensing 63, pp 1303–1313Google Scholar
- Sutton P, Elvidge C, Obremski T (2003) Building and evaluating models to estimate ambient population density. Photogrammetric Engineering and Remote Sensing 69, pp 545–553Google Scholar
- Tobler W, Deichmann U, Gottsegen J, Maloy K (1995) The global demography project, Technical Report TR-95-6, National Center for Geographic Information and Analysis, Santa BarbaraGoogle Scholar
- Vallin, J (1992) La population mondiale. La Decouverte, ParisGoogle Scholar
- Vincent V, Thomas RG (1960) An agricultural survey of Southern Rhodesia: Part I: agro-ecological survey. Government Printer, SalisburyGoogle Scholar
- Xiaohang L (2004) Dasymetric mapping with image texture. In: Proceedings of the ASP R S 2004 Annual Conference, Denver, USA, pp 23–28Google Scholar