Literature DB >> 27245798

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

Timothy Shields1, Jessie Pinchoff, Jailos Lubinda, Harry Hamapumbu, Kelly Searle, Tamaki Kobayashi, Philip E Thuma, William J Moss, Frank C Curriero.   

Abstract

Satellite imagery is increasingly available at high spatial resolution and can be used for various purposes in public health research and programme 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 3821 household locations were enumerated in 2006 and 4256 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 provides insights into the population distribution changes between two time periods and can be helpful in assessing the accuracy of satellite imagery.

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Year:  2016        PMID: 27245798      PMCID: PMC4890610          DOI: 10.4081/gh.2016.410

Source DB:  PubMed          Journal:  Geospat Health        ISSN: 1827-1987            Impact factor:   1.212


  23 in total

1.  A real-time platform for monitoring schistosomiasis transmission supported by Google Earth and a web-based geographical information system.

Authors:  Kun Yang; Le-Ping Sun; Yi-Xin Huang; Guo-Jing Yang; Feng Wu; De-Rong Hang; Wei Li; Jian-Feng Zhang; Yong-Sheng Liang; Xiao-Nong Zhou
Journal:  Geospat Health       Date:  2012-05       Impact factor: 1.212

2.  Earth observation in support of malaria control and epidemiology: MALAREO monitoring approaches.

Authors:  Jonas Franke; Michael Gebreslasie; Ides Bauwens; Julie Deleu; Florian Siegert
Journal:  Geospat Health       Date:  2015-06-03       Impact factor: 1.212

3.  Feasibility of satellite image-based sampling for a health survey among urban townships of Lusaka, Zambia.

Authors:  Sara A Lowther; Frank C Curriero; Timothy Shields; Saifuddin Ahmed; Mwaka Monze; William J Moss
Journal:  Trop Med Int Health       Date:  2008-12-11       Impact factor: 2.622

4.  Population distribution, settlement patterns and accessibility across Africa in 2010.

Authors:  Catherine Linard; Marius Gilbert; Robert W Snow; Abdisalan M Noor; Andrew J Tatem
Journal:  PLoS One       Date:  2012-02-21       Impact factor: 3.240

5.  A random spatial sampling method in a rural developing nation.

Authors:  Michelle C Kondo; Kent D W Bream; Frances K Barg; Charles C Branas
Journal:  BMC Public Health       Date:  2014-04-10       Impact factor: 3.295

6.  Using high spatial resolution remote sensing for risk mapping of malaria occurrence in the Nouna district, Burkina Faso.

Authors:  Peter Dambach; Ali Sié; Jean-Pierre Lacaux; Cécile Vignolles; Vanessa Machault; Rainer Sauerborn
Journal:  Glob Health Action       Date:  2009-11-11       Impact factor: 2.640

7.  Usefulness of commercially available GPS data-loggers for tracking human movement and exposure to dengue virus.

Authors:  Gonzalo M Vazquez-Prokopec; Steven T Stoddard; Valerie Paz-Soldan; Amy C Morrison; John P Elder; Tadeusz J Kochel; Thomas W Scott; Uriel Kitron
Journal:  Int J Health Geogr       Date:  2009-11-30       Impact factor: 3.918

8.  Identifying landscape features associated with Rift Valley fever virus transmission, Ferlo region, Senegal, using very high spatial resolution satellite imagery.

Authors:  Valérie Soti; Véronique Chevalier; Jonathan Maura; Agnès Bégué; Camille Lelong; Renaud Lancelot; Yaya Thiongane; Annelise Tran
Journal:  Int J Health Geogr       Date:  2013-03-01       Impact factor: 3.918

9.  Validity and feasibility of a satellite imagery-based method for rapid estimation of displaced populations.

Authors:  Francesco Checchi; Barclay T Stewart; Jennifer J Palmer; Chris Grundy
Journal:  Int J Health Geogr       Date:  2013-01-23       Impact factor: 3.918

10.  High resolution population maps for low income nations: combining land cover and census in East Africa.

Authors:  Andrew J Tatem; Abdisalan M Noor; Craig von Hagen; Antonio Di Gregorio; Simon I Hay
Journal:  PLoS One       Date:  2007-12-12       Impact factor: 3.240

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  4 in total

Review 1.  Satellite Observations and Malaria: New Opportunities for Research and Applications.

Authors:  Michael C Wimberly; Kirsten M de Beurs; Tatiana V Loboda; William K Pan
Journal:  Trends Parasitol       Date:  2021-03-25

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

Authors:  Andrea McMahon; Abere Mihretie; Adem Agmas Ahmed; Mastewal Lake; Worku Awoke; Michael Charles Wimberly
Journal:  Int J Health Geogr       Date:  2021-06-13       Impact factor: 3.918

3.  Spatially disaggregated population estimates in the absence of national population and housing census data.

Authors:  N A Wardrop; W C Jochem; T J Bird; H R Chamberlain; D Clarke; D Kerr; L Bengtsson; S Juran; V Seaman; A J Tatem
Journal:  Proc Natl Acad Sci U S A       Date:  2018-03-19       Impact factor: 11.205

4.  Residential scene classification for gridded population sampling in developing countries using deep convolutional neural networks on satellite imagery.

Authors:  Robert F Chew; Safaa Amer; Kasey Jones; Jennifer Unangst; James Cajka; Justine Allpress; Mark Bruhn
Journal:  Int J Health Geogr       Date:  2018-05-09       Impact factor: 3.918

  4 in total

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