Modelling changing population distributions: an example of the Kenyan Coast, 1979–2009
Large-scale gridded population datasets are usually produced for the year of input census data using a top-down approach and projected backward and forward in time using national growth rates. Such temporal projections do not include any subnational variation in population distribution trends and ig...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2017-10-01
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| Series: | International Journal of Digital Earth |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/17538947.2016.1275829 |
| _version_ | 1797678634428792832 |
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| author | Catherine Linard Caroline W. Kabaria Marius Gilbert Andrew J. Tatem Andrea E. Gaughan Forrest R. Stevens Alessandro Sorichetta Abdisalan M. Noor Robert W. Snow |
| author_facet | Catherine Linard Caroline W. Kabaria Marius Gilbert Andrew J. Tatem Andrea E. Gaughan Forrest R. Stevens Alessandro Sorichetta Abdisalan M. Noor Robert W. Snow |
| author_sort | Catherine Linard |
| collection | DOAJ |
| description | Large-scale gridded population datasets are usually produced for the year of input census data using a top-down approach and projected backward and forward in time using national growth rates. Such temporal projections do not include any subnational variation in population distribution trends and ignore changes in geographical covariates such as urban land cover changes. Improved predictions of population distribution changes over time require the use of a limited number of covariates that are time-invariant or temporally explicit. Here we make use of recently released multi-temporal high-resolution global settlement layers, historical census data and latest developments in population distribution modelling methods to reconstruct population distribution changes over 30 years across the Kenyan Coast. We explore the methodological challenges associated with the production of gridded population distribution time-series in data-scarce countries and show that trade-offs have to be found between spatial and temporal resolutions when selecting the best modelling approach. Strategies used to fill data gaps may vary according to the local context and the objective of the study. This work will hopefully serve as a benchmark for future developments of population distribution time-series that are increasingly required for population-at-risk estimations and spatial modelling in various fields. |
| first_indexed | 2024-03-11T23:02:47Z |
| format | Article |
| id | doaj.art-94196fe0bbdf4d0397368754f2b65fe6 |
| institution | Directory Open Access Journal |
| issn | 1753-8947 1753-8955 |
| language | English |
| last_indexed | 2024-03-11T23:02:47Z |
| publishDate | 2017-10-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Digital Earth |
| spelling | doaj.art-94196fe0bbdf4d0397368754f2b65fe62023-09-21T14:38:05ZengTaylor & Francis GroupInternational Journal of Digital Earth1753-89471753-89552017-10-0110101017102910.1080/17538947.2016.12758291275829Modelling changing population distributions: an example of the Kenyan Coast, 1979–2009Catherine Linard0Caroline W. Kabaria1Marius Gilbert2Andrew J. Tatem3Andrea E. Gaughan4Forrest R. Stevens5Alessandro Sorichetta6Abdisalan M. Noor7Robert W. Snow8Université Libre de BruxellesKEMRI Wellcome Trust Research ProgrammeUniversité Libre de BruxellesUniversity of SouthamptonUniversity of LouisvilleUniversity of LouisvilleUniversity of SouthamptonKEMRI Wellcome Trust Research ProgrammeKEMRI Wellcome Trust Research ProgrammeLarge-scale gridded population datasets are usually produced for the year of input census data using a top-down approach and projected backward and forward in time using national growth rates. Such temporal projections do not include any subnational variation in population distribution trends and ignore changes in geographical covariates such as urban land cover changes. Improved predictions of population distribution changes over time require the use of a limited number of covariates that are time-invariant or temporally explicit. Here we make use of recently released multi-temporal high-resolution global settlement layers, historical census data and latest developments in population distribution modelling methods to reconstruct population distribution changes over 30 years across the Kenyan Coast. We explore the methodological challenges associated with the production of gridded population distribution time-series in data-scarce countries and show that trade-offs have to be found between spatial and temporal resolutions when selecting the best modelling approach. Strategies used to fill data gaps may vary according to the local context and the objective of the study. This work will hopefully serve as a benchmark for future developments of population distribution time-series that are increasingly required for population-at-risk estimations and spatial modelling in various fields.http://dx.doi.org/10.1080/17538947.2016.1275829human populationdistribution modellinggridded population datasetstemporal changekenya |
| spellingShingle | Catherine Linard Caroline W. Kabaria Marius Gilbert Andrew J. Tatem Andrea E. Gaughan Forrest R. Stevens Alessandro Sorichetta Abdisalan M. Noor Robert W. Snow Modelling changing population distributions: an example of the Kenyan Coast, 1979–2009 International Journal of Digital Earth human population distribution modelling gridded population datasets temporal change kenya |
| title | Modelling changing population distributions: an example of the Kenyan Coast, 1979–2009 |
| title_full | Modelling changing population distributions: an example of the Kenyan Coast, 1979–2009 |
| title_fullStr | Modelling changing population distributions: an example of the Kenyan Coast, 1979–2009 |
| title_full_unstemmed | Modelling changing population distributions: an example of the Kenyan Coast, 1979–2009 |
| title_short | Modelling changing population distributions: an example of the Kenyan Coast, 1979–2009 |
| title_sort | modelling changing population distributions an example of the kenyan coast 1979 2009 |
| topic | human population distribution modelling gridded population datasets temporal change kenya |
| url | http://dx.doi.org/10.1080/17538947.2016.1275829 |
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