Estimating the size of urban populations using Landsat images: a case study of Bo, Sierra Leone, West Africa.

BACKGROUND: This is the third paper in a 3-paper series evaluating alternative models for rapidly estimating neighborhood populations using limited survey data, augmented with aerial imagery. METHODS: Bayesian methods were used to sample the large solution space of candidate regression models for estimating population density. RESULTS: We accurately estimated the population densities and counts of 20 neighborhoods in the city of Bo, Sierra Leone, using statistical measures derived from Landsat multi-band satellite imagery. The best regression model proposed estimated the latter with an absolute median proportional error of 8.0%, while the total population of the 20 neighborhoods was estimated with an error of less than 1.0%. We also compare our results with those obtained using an empirical Bayes approach. CONCLUSIONS: Our approach provides a rapid and effective method for constructing predictive models for population densities and counts utilizing remote sensing imagery. Our results, including cross-validation analysis, suggest that masking non-urban areas in the Landsat section images prior to computing the candidate covariate regressors should further improve model generality.

Health-care availability, preference, and distance for women in urban Bo, Sierra Leone.

OBJECTIVES: To examine the diversity of the health-care providers in urban Bo, Sierra Leone, identify the types of health-care facilities preferred by women for fevers, and analyze the road network distances from homes to preferred health-care providers. METHODS: A population-based random sampling method was used to recruit 2419 women from Bo. A geographic information system was used to measure the road distance from each woman's home to her preferred provider. RESULTS: Preferred health-care providers for acute febrile illnesses (commonly referred to as "malaria" in the study communities) were hospitals (62.3 %), clinics (12.6 %), and pharmacies (12.4 %). Participants lived a median distance of 0.6 km from the nearest provider, but on average each woman lived 2.2 km one-way from her preferred provider. Women living farther from the city center had preferred providers significantly farther from home than women living downtown. CONCLUSIONS: The diverse health-care marketplace in Bo allows women to select clinical facilities from across the city. Most women prefer a malaria care provider farther from home than they could comfortably walk when ill.

Stratified Sampling of Neighborhood Sections for Population Estimation: A Case Study of Bo City, Sierra Leone.

There is a need for better estimators of population size in places that have undergone rapid growth and where collection of census data is difficult. We explored simulated estimates of urban population based on survey data from Bo, Sierra Leone, using two approaches: (1) stratified sampling from across 20 neighborhoods and (2) stratified single-stage cluster sampling of only four randomly-sampled neighborhoods. The stratification variables evaluated were (a) occupants per individual residence, (b) occupants per neighborhood, and (c) residential structures per neighborhood. For method (1), stratification variable (a) yielded the most accurate re-estimate of the current total population. Stratification variable (c), which can be estimated from aerial photography and zoning type verification, and variable (b), which could be ascertained by surveying a limited number of households, increased the accuracy of method (2). Small household-level surveys with appropriate sampling methods can yield reasonably accurate estimations of urban populations.

Methods for determining the uncertainty of population estimates derived from satellite imagery and limited survey data: a case study of Bo city, Sierra Leone.

This study demonstrates the use of bootstrap methods to estimate the total population of urban and periurban areas using satellite imagery and limited survey data. We conducted complete household surveys in 20 neighborhoods in the city of Bo, Sierra Leone, which collectively were home to 25,954 persons living in 1,979 residential structures. For five of those twenty sections, we quantized the rooftop areas of structures extracted from satellite images. We used bootstrap statistical methods to estimate the total population of the pooled sections, including the associated uncertainty intervals, as a function of sample size. Evaluations based either on rooftop area per person or on the mean number of occupants per residence both converged on the true population size. We demonstrate with this simulation that demographic surveys of a relatively small proportion of residences can provide a foundation for accurately estimating the total population in conjunction with aerial photographs.