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Social cartography and satellite-derived building coverage for post-census population estimates in difficult-to-access regions of Colombia

Dados Bibliográficos

ID7980209
AutoresLina Maria Sanchez-Cespedes (0000-0003-0698-8542, National Administrative Department of Statistics, Colombia), Douglas Ryan Leasure (0000-0002-8768-2811, University of Oxford), Natalia Tejedor-Garavito (0000-0002-1140-6263, WorldPop, University of Southampton), Glenn Harry Amaya Cruz (0000-0002-3412-6379, National Administrative Department of Statistics, Colombia), Gustavo Adolfo Garcia Velez (0000-0002-7339-6814, National Administrative Department of Statistics, Colombia), Andryu Enrique Mendoza (0000-0001-6498-8108, National Administrative Department of Statistics, Colombia), Yenny Andrea Marín Salazar (0000-0002-4649-438X, National Administrative Department of Statistics, Colombia), Thomas Esch (0000-0002-3534-0801, Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)), Andrew J Tatem (0000-0002-7270-941X, WorldPop, University of Southampton), Mariana Ospina Bohórquez (0000-0001-5722-4767, National Administrative Department of Statistics, Colombia)
Ano2024
Volume78
Fascículo1
Páginas3-20
Data de publicação2024-01-02
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoPopulation Studies (JOURNAL)
Identificadores do periódicoISSN: 0032-4728 • E-ISSN: 1477-4747
EditoraInforma UK Limited (PUBLISHER • GB)
DOI10.1080/00324728.2023.2190151
PMID36977422
OpenAlexW4361215284
IdiomaEN
Citações recebidas4
Referências citadas27

Effective government services rely on accurate population numbers to allocate resources. In Colombia and globally, census enumeration is challenging in remote regions and where armed conflict is occurring. During census preparations, the Colombian National Administrative Department of Statistics conducted social cartography workshops, where community representatives estimated numbers of dwellings and people throughout their regions. We repurposed this information, combining it with remotely sensed buildings data and other geospatial data. To estimate building counts and population sizes, we developed hierarchical Bayesian models, trained using nearby full-coverage census enumerations and assessed using 10-fold cross-validation. We compared models to assess the relative contributions of community knowledge, remotely sensed buildings, and their combination to model fit. The Community model was unbiased but imprecise; the Satellite model was more precise but biased; and the Combination model was best for overall accuracy. Results reaffirmed the power of remotely sensed buildings data for population estimation and highlighted the value of incorporating local knowledge

American Community Survey · Cartography · Census · Estimation · Geography · Geospatial analysis · Government (linguistics) · Population · Remote sensing · Sociology · Computer Science · Demography · Engineering · Human Mobility and Location-Based Analysis · Impact of Light on Environment and Health · Land Use and Ecosystem Services

  • Building footprint data for countries in Africa

    Open Access•Heather Chamberlain, Heather R Chamberlain et al.•Computers Environment and Urban…•2024

  • Demographic figures at risk in the digital era

    Open Access•Edith Darin•Big Data & Society•2025

  • How Accurate Are High Resolution Settlement Maps at Predicting Population Counts in Data Scarce Settings

    Open Access•Edith Darin, Ridhi Kashyap et al.•Population Space and Place•2025

  • Tackling public health data gaps through Bayesian high-resolution population estimation

    Open Access•Gianluca Boo, Edith Darin et al.•PLOS Global Public Health•2025

  • Prior distributions for variance parameters in hierarchical models (comment on article by Browne and Draper)

    Open Access•Andrew Gelman•Bayesian Analysis•2006

  • The Shuttle Radar Topography Mission

    Open Access•T G Farr, P A Rosen et al.•Reviews of Geophysics•2007

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

    Open Access•Nicola Wardrop, N A Wardrop et al.•Proceedings of the National…•2018

  • General Methods for Monitoring Convergence of Iterative Simulations

    Stephen P Brooks, Andrew Gelman•Journal of Computational and…•1998

  • Viirs night-time lights

    Open Access•Christopher D Elvidge, Kimberly Baugh et al.•International Journal of Remote…•2017

  • Google Earth Engine

    Open Access•Noel Gorelick, Matt Hancher et al.•Remote Sensing of Environment•2017

  • Inference from Iterative Simulation Using Multiple Sequences

    Andrew Gelman, Donald B Rubin•Statistical Science•1992

  • First Steps in Initiating an Effective Maternal, Neonatal, and Child Health Program in Urban Slums

    Open Access•Lucy E Marcil, Lucy Marcil et al.•Journal of Urban Health•2016

  • Missing Millions and Measuring Development Progress

    Open Access•Roy Carr‐hill, Roy Carr-Hill•World Development•2013

  • Racial and Ethnic Differences in U.S. Census Omission Rates

    Open Access•David J Fein, David Fein•Demography•1990

  • An Invitation to Postmodern Social Cartography

    Rolland G Paulston, Martin Liebman•Comparative Education Review•1994

  • Os indígenas nos censos demográficos brasileiros pré-1991

    Open Access•Claudio Santiago Dias, Ana Paula De Andrade Verona•Revista Brasileira de Estudos de…•2018

Obras citantes distintas4
Citações por ano2
Intervalo de citações2024 - 2025 (2)
Velocidade de citaçãorecent
Altamente citadoNão
Tipos de citaçãoNeutras: 4
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