Methods for Determining the Uncertainty of Population Estimates Derived from Satellite Imagery and Limited Survey Data: A Case Study of Bo City, Sierra Leone

Hillson, Roger; Alejandre, Joel D.; Jacobsen, Kathryn H.; Ansumana, Rashid; Bockarie, Alfred S.; Bangura, Umaru; Lamin, Joseph M.; Malanoski, Anthony P.; Stenger, David A.

doi:10.1371/journal.pone.0112241

Cited by 25 publications

(38 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In recent years, several studies have focused on estimating population in data-poor regions using high resolution remotely sensed imagery. Population estimation in these studies is mostly based on identifying the number of dwellings, or on estimating the total rooftop area [20,25,26]. Estimates of population are then obtained (a) by multiplying the number of dwellings with an estimated number of people per building structure [25,27], or (b) by multiplying the rooftop area of all buildings with the average number of people per square meter [20,25,26].…”

Section: Introductionmentioning

confidence: 99%

Mapping Population Distribution from High Resolution Remotely Sensed Imagery in a Data Poor Setting

Mossoux

Kervyn

Soulé³

et al. 2018

Remote Sensing

View full text Add to dashboard Cite

Accurate mapping of population distribution is essential for policy-making, urban planning, administration, and risk management in hazardous areas. In some countries, however, population data is not collected on a regular basis and is rarely available at a high spatial resolution. In this study, we proposed an approach to estimate the absolute number of inhabitants at the neighborhood level, combining data obtained through field work with high resolution remote sensing. The approach was tested on Ngazidja Island (Union of the Comoros). A detailed survey of neighborhoods at the level of individual dwellings, showed that the average number of inhabitants per dwelling was significantly different between buildings characterized by a different roof type. Firstly, high spatial resolution remotely sensed imagery was used to define the location of individual buildings, and second to determine the roof type for each building, using an object-based classification approach. Knowing the location of individual houses and their roof type, the number of inhabitants was estimated at the neighborhood level using the data on house occupancy of the field survey. To correct for misclassification bias in roof type discrimination, an inverse calibration approach was applied. To assess the impact of variations in average dwelling occupancy between neighborhoods on model outcome, a measure of the degree of confidence of population estimates was calculated. Validation using the leave-one-out approach showed low model bias, and a relative error at the neighborhood level of 17%. With the increasing availability of high resolution remotely sensed data, population estimation methods combining data from field surveys with remote sensing, as proposed in this study, hold great promise for systematic mapping of population distribution in areas where reliable census data are not available on a regular basis.

show abstract

Section: Introductionmentioning

confidence: 99%

Mapping Population Distribution from High Resolution Remotely Sensed Imagery in a Data Poor Setting

Mossoux

Kervyn

Soulé³

et al. 2018

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Other projects have resulted in a bottom-up gridded population estimate for a single country (e.g. Sierra Leone [45], Afghanistan [46]), and an early version of GRID3's Nigeria dataset is currently available [47].…”

Section: Gridded Population Datamentioning

confidence: 99%

Gridded Population Survey Sampling: A Review of the Field and Strategic Research Agenda

Thomson¹,

Rhoda²,

Tatem³

et al. 2020

Preprint

View full text Add to dashboard Cite

Objective: In low- and middle-income countries (LMICs), household survey data are a main source of information for planning, evaluation, and decision-making. Standard surveys are based on censuses, however, for many LMICs it has been more than ten years since their last census and they face high urban growth rates. Over the last decade, survey designers have begun to use modelled gridded population estimates as sample frames. We summarize the state of the emerging field of gridded population survey sampling, focussing on LMICs. Methods: We performed a systematic review and identified 43 national and sub-national gridded population-based household surveys implemented across 29 LMICs. Findings: Gridded population surveys used automated and manual approaches to derive clusters from WorldPop and LandScan gridded population estimates. After sampling, many surveys interviewed all households in each cluster or segment, though some sampled households from larger clusters. Tools to select gridded population survey clusters include the GridSample R package, Geo-sampling tool, and GridSample.org. In the field, gridded population surveys generally relied on geographically accurate maps based on satellite imagery or OpenStreetMap, and a tablet or GPS technology for navigation. Conclusions: For gridded population survey sampling to be adopted more widely, several strategic questions need answering regarding cell-level accuracy and uncertainty of gridded population estimates, the methods used to group/split cells into sample frame units, design effects of new sample designs, and feasibility of tools and methods to implement surveys across diverse settings.

show abstract

“…The use of GNSS as a new tool for epidemiological research was discussed in a variety of articles [282,275,270,274,280,279,281,287,288,271,269,284,268]. GNSS use was reported to construct random sampling frames for surveys, mapping households, or determining population estimates [267,278,272,277,273,266,285,289,276]. The potential future impacts of GPS devices on medicine is discussed in Pager's article, Impacts for medicine of global monitoring [283].…”

Section: Insights From the Literature Reviewmentioning

confidence: 99%

Applications of Space Technologies to Global Health: Scoping Review (Preprint)

Dietrich¹,

Dekova²,

Davy³

et al. 2017

Preprint

View full text Add to dashboard Cite

BACKGROUND Space technology has an impact on many domains of activity on earth, including in the field of global health. With the recent adoption of the United Nations’ Sustainable Development Goals that highlight the need for strengthening partnerships in different domains, it is useful to better characterize the relationship between space technology and global health. OBJECTIVE The aim of this study was to identify the applications of space technologies to global health, the key stakeholders in the field, as well as gaps and challenges. METHODS We used a scoping review methodology, including a literature review and the involvement of stakeholders, via a brief self-administered, open-response questionnaire. A distinct search on several search engines was conducted for each of the four key technological domains that were previously identified by the UN Office for Outer Space Affairs’ Expert Group on Space and Global Health (Domain A: remote sensing; Domain B: global navigation satellite systems; Domain C: satellite communication; and Domain D: human space flight). Themes in which space technologies are of benefit to global health were extracted. Key stakeholders, as well as gaps, challenges, and perspectives were identified. RESULTS A total of 222 sources were included for Domain A, 82 sources for Domain B, 144 sources for Domain C, and 31 sources for Domain D. A total of 3 questionnaires out of 16 sent were answered. Global navigation satellite systems and geographic information systems are used for the study and forecasting of communicable and noncommunicable diseases; satellite communication and global navigation satellite systems for disaster response; satellite communication for telemedicine and tele-education; and global navigation satellite systems for autonomy improvement, access to health care, as well as for safe and efficient transportation. Various health research and technologies developed for inhabited space flights have been adapted for terrestrial use. CONCLUSIONS Although numerous examples of space technology applications to global health exist, improved awareness, training, and collaboration of the research community is needed.

show abstract

Methods for Determining the Uncertainty of Population Estimates Derived from Satellite Imagery and Limited Survey Data: A Case Study of Bo City, Sierra Leone

Cited by 25 publications

References 27 publications

Mapping Population Distribution from High Resolution Remotely Sensed Imagery in a Data Poor Setting

Mapping Population Distribution from High Resolution Remotely Sensed Imagery in a Data Poor Setting

Gridded Population Survey Sampling: A Review of the Field and Strategic Research Agenda

Applications of Space Technologies to Global Health: Scoping Review (Preprint)

Contact Info

Product

Resources

About