Modeling human migration across spatial scales in Colombia
Modeling human migration across spatial scales in Colombia
We developed a novel spatial interaction modeling approach for Colombia using previously identified economic, socio-demographic and geographic factors including the regional equivalent of the gross domestic product, relative population size, proportion of urban population and geographic contiguity of locations, in addition to the absolute population size and distance between locations to fit a municipality level (i.e., Admin-2 level) model to observed census-based department level (i.e., Admin-1 level) migration data.,Human mobility, both short and long term, are important considerations in the study of numerous systems. Economic and technological advances have led to a more interconnected global community, further increasing the need for considerations of human mobility. While data on human mobility are better recorded in many developed countries, availability of such data remains limited in many low- and middle-income countries around the world, particularly at the fine temporal and spatial scales required by many applications. In this study, we used 5-year census-based internal migration microdata for 32 departments in Colombia (i.e., Admin-1 level) to develop a novel spatial interaction modeling approach for estimating migration, at a finer spatial scale, among the 1,122 municipalities in the country (i.e., Admin-2 level). Our modeling approach bridges a significant gap in the availability of migration data at administrative unit levels finer than those at which migration data are typically recorded. Due to the widespread availability of census-based migration microdata at the Admin-1 level, our modeling approach opens up for the possibilities of modeling migration patterns at Admin-2 and Admin-3 levels across many other countries where such data are currently lacking.,The dataset contains estimated migration between 2000 and 2005 between 1122 municipalities in Columbia. The first three columns identify the municipalities. While the remainder are estimated figures of migrant numbers from the munucipality identified by the row to the minicipality identified by the column. All rows and columns are sorted the same way.
Siraj, Amir
04c56878-d633-4728-a824-b1db6a6aa4df
Sorichetta, Alessandro
c80d941b-a3f5-4a6d-9a19-e3eeba84443c
España, Guido
492ecc93-5174-4509-819f-4de0e4bde815
Tatem, Andrew
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Perkins, Alex
6a3765cc-2473-4aff-8735-b8174b64b34e
Siraj, Amir
04c56878-d633-4728-a824-b1db6a6aa4df
Sorichetta, Alessandro
c80d941b-a3f5-4a6d-9a19-e3eeba84443c
España, Guido
492ecc93-5174-4509-819f-4de0e4bde815
Tatem, Andrew
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Perkins, Alex
6a3765cc-2473-4aff-8735-b8174b64b34e
Abstract
We developed a novel spatial interaction modeling approach for Colombia using previously identified economic, socio-demographic and geographic factors including the regional equivalent of the gross domestic product, relative population size, proportion of urban population and geographic contiguity of locations, in addition to the absolute population size and distance between locations to fit a municipality level (i.e., Admin-2 level) model to observed census-based department level (i.e., Admin-1 level) migration data.,Human mobility, both short and long term, are important considerations in the study of numerous systems. Economic and technological advances have led to a more interconnected global community, further increasing the need for considerations of human mobility. While data on human mobility are better recorded in many developed countries, availability of such data remains limited in many low- and middle-income countries around the world, particularly at the fine temporal and spatial scales required by many applications. In this study, we used 5-year census-based internal migration microdata for 32 departments in Colombia (i.e., Admin-1 level) to develop a novel spatial interaction modeling approach for estimating migration, at a finer spatial scale, among the 1,122 municipalities in the country (i.e., Admin-2 level). Our modeling approach bridges a significant gap in the availability of migration data at administrative unit levels finer than those at which migration data are typically recorded. Due to the widespread availability of census-based migration microdata at the Admin-1 level, our modeling approach opens up for the possibilities of modeling migration patterns at Admin-2 and Admin-3 levels across many other countries where such data are currently lacking.,The dataset contains estimated migration between 2000 and 2005 between 1122 municipalities in Columbia. The first three columns identify the municipalities. While the remainder are estimated figures of migrant numbers from the munucipality identified by the row to the minicipality identified by the column. All rows and columns are sorted the same way.
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Published date: 1 January 2019
Identifiers
Local EPrints ID: 446297
URI: http://eprints.soton.ac.uk/id/eprint/446297
PURE UUID: 9dcf678e-d832-4ca1-897c-e4e279a4616f
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Date deposited: 03 Feb 2021 17:35
Last modified: 05 Aug 2023 01:42
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Contributors
Contributor:
Amir Siraj
Contributor:
Guido España
Contributor:
Alex Perkins
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