Spatial and temporal changes in household structure locations using high-resolution satellite imagery for population assessment: an analysis in southern Zambia, 2006-2011

Abstract

Satellite imagery is increasingly available at high spatial resolution and can be used for various purposes in public health research and program implementation. Comparing a census generated from two satellite images of the same region in rural southern Zambia obtained four and a half years apart identified patterns of household locations and change over time. The length of time that a satellite image-based census is accurate determines its utility. Households were enumerated manually from satellite images obtained in 2006 and 2011 of the same area. Spatial statistics were used to describe clustering, cluster detection, and spatial variation in the location of households. A total of 3,821 household locations were enumerated in 2006 and 4,256 in 2011, a net change of 435 houses (11.4% increase). Comparison of the images indicated that 971 (25.4%) structures were added and 536 (14.0%) removed. Further analysis suggested similar household clustering in the two images and no substantial difference in concentration of households across the study area. Cluster detection analysis identified a small area where significantly more household structures were removed than expected; however, the amount of change was of limited practical significance. These findings suggest that random sampling of households for study participation would not induce geographic bias if based on a 4.5 year old image in this region. Application of spatial statistical methods provide insights into the population distribution changes between two time periods and can be helpful in assessing the accuracy of satellite imagery.

Evaluation of residential structures not covered by aerial photographs used to generate a sampling frame – Nueva Santa Rosa, Guatemala

“…However, it has been shown previously that images of that age (>4 years) may not introduce significant geographic bias when constructing a random sampling of households. 24 This provides further justification for utilizing aerial photographs despite a gap between the time in which the images were captured and a ground study was conducted.…”

Satellite Observations and Malaria: New Opportunities for Research and Applications

“…There is potential for much broader use of Landsat time series in malaria research. One limiting factor is the availability of long-term epidemiological and entomological datasets with [45][46][47]. Building data obtained from VHR imagery are also useful for developing localized population estimates in settings where national census data are unavailable or inadequate [48].…”

“…Mapping this level of detail requires very high resolution (VHR) satellite imagery (ranging from <1 m to 5 m pixel size), which is acquired by commercial satellites such as Ikonos, GeoEye, and WorldView 1–3. These images can be used to enumerate individual households for selecting study subjects or implementing household-level interventions [ 45 – 47 ]. Building data obtained from VHR imagery are also useful for developing localized population estimates in settings where national census data are unavailable or inadequate [ 48 ].…”

Remote sensing of environmental risk factors for malaria in different geographic contexts

“…Data from high-resolution sensors such as Landsat (30 m spatial resolution) have been used to assess the effects of water, land cover, and land use on spatial patterns of mosquito vectors [ 26 ] and malaria cases [ 27 – 29 ]. Very-high resolution imagery from commercial satellites such as GeoEye (0.5 m spatial resolution) has been used to map individual households [ 30 ], and SPOT imagery (1.5 m spatial resolution) has been used to map larval habitats [ 31 ] in support of malaria research and control efforts. Thus, remote sensing is a useful tool for studying the effects of environmental conditions on mosquito borne diseases like malaria [ 24 , 32 – 35 ].…”