GRID3 Kenya Social Distancing Layers, Version 1.0
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✦ Suggested by OrionAIThe two layers contained within the GRID3 KEN - Settlement Extents v3.0 include: GRID3_KEN_settlement_extents_v3.gpkg: a spatial layer representing settlement polygons. GRID3_KEN_settlement_grid_v3.gpkg: a spatial layer representing the centroids of settled grid cells. The current version supersedes GRID3 KEN - Settlement Extents v2.0; the following changes were made: Development of a new methodology to derive building counts and settlement polygons with open data. Estimation of a probability value for settlement polygons Addition of a building-area measure Replacement of degree of urbanization with classification based on built-up areas, small settlement areas, and hamlets Elimination of building-count ranges Elimination of variable comparing to previous versions For more information on data inputs, methodology, and codebooks please see the Data Release Notes. Recommended Citation: Center for International Earth Science Information Network (CIESIN), Columbia University. 2024. GRID3 KEN - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/6hnz-fr54. Accessed [DAY MONTH YEAR]. Terms of use: Users are free to download, store, access, use, copy, adapt, transform, alter, arrange, build upon, distribute and transmit this work and any derivative works. Attribution of the source must be provided, and further distribution of this work or derived work must maintain the same terms of data use and license as set forth in this Terms of Use. Copyright 2024. The Trustees of Columbia University in the City of New York. Data license: The data and accompanying document are licensed under a Creative Commons Attribution-ShareAlike 4.0 International, CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0) and specified in legal code (https://creativecommons.org/licenses/by-sa/4.0/legalcode). Contacts and data queries: The authors of this dataset appreciate feedback regarding the data, including suggestions, discovery of errors, difficulties in using the data, and format preferences. For dataset-related questions, please send an email to: info@ciesin.columbia.edu
These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the United Nations Children's Fund ( UNICEF ) - Population Modelling for use in Routine Health Planning and Monitoring project (contract no. 43335861). Projects partners included the Kenya Unicef Regional and Country Offices, WorldPop research group at the University of Southampton and the Center for International Earth Science Information Network CIESIN in the Columbia Climate School at Columbia University. Assane Gadiaga (WorldPop) led the input processing and the modelling work following the Random Forest (RF)-based dasymetric mapping approach developed by Stevens et al. (2015). Thomas Abbott supported the covariates processing work, as well as Christopher Lloyd, particularly for the processing of residential/non-residential building footprints. In-country engagements were done by Benard Mitto, Justine Dowden (CIESIN) and Maria Muniz (Unicef). Using the 2009 and 2019 census data from the Kenya’s National Bureau of Statistics (KNBS), the US Census Bureau released the census-based total population projections, population by age and gender and digital sub-counties boundaries. Duygu Cihan helped in the preparation of these input population data. Attila N Lazar, Edith Darin and Heather Chamberlain advised on the modelling procedure. The work was overseen by Attila N Lazar and Andy J Tatem. For further details, please, read the Release Statement. **Release content** 1. KEN_population_v1_0_gridded.tif 2. KEN_population_v1_0_agesex.zip 3. KEN_population_v1_0_mastergrid.tif **Recommended citations** Gadiaga A. N., Abbott T. J., Chamberlain H., Lloyd C. T., Lazar A. N., Darin E., Tatem A. J. 2022. *Census disaggregated gridded population estimates for Kenya (2021), version 1.0* University of Southampton. doi:10.5258/SOTON/WP00747 **License** *These data may be distributed using a Creative Commons Attribution 4.0 International (CC BY 4.0) License, specified in legal code. Contact release[at]worldpop.org for more information*. The authors followed rigorous procedures designed to ensure that the used data, the applied method and thus the results are appropriate and of reasonable quality. If users encounter apparent errors or misstatements, they should contact WorldPop at release[at]worldpop.org. WorldPop, University of Southampton, and their sponsors offer these data on a "where is, as is" basis; do not offer an express or implied warranty of any kind; do not guarantee the quality, applicability, accuracy, reliability or completeness of any data provided; and shall not be liable for incidental, consequential, or special damages arising out of the use of any data that they offer.
Gridded population density of Kenya for the year 2020 at 1km resolution, adjusted to match UN national population estimates. Each grid cell shows the estimated number of people per square kilometre. Use this layer for settlement pattern analysis, infrastructure planning, service delivery optimisation, and identifying high and low density areas.
These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the United Nations Children's Fund ( UNICEF ) - Population Modelling for use in Routine Health Planning and Monitoring project (contract no. 43335861). Projects partners included the Kenya Unicef Regional and Country Offices, WorldPop research group at the University of Southampton and the Center for International Earth Science Information Network in the Columbia Climate School at Columbia University. Assane Gadiaga (WorldPop) led the input processing and the modelling work following the Random Forest (RF)-based dasymetric mapping approach developed by Stevens et al. (2015). Thomas Abbott supported the covariates processing work. In-country engagements were done by David Kyalo, Olena Borkovska ( GRID3 , Maria Muniz (Unicef). Using the 2009 and 2019 census data from the Kenya’s National Bureau of Statistics (KNBS), the US Census Bureau released the census-based total population projections, population by age and gender and digital sub-counties boundaries. Duygu Cihan helped in the preparation of these input population data. Attila N Lazar, Edith Darin and Heather Chamberlain advised on the modelling procedure. The work was overseen by Attila N Lazar and Andy J Tatem. **Recommended citations** Gadiaga A. N., Abbott T. J., Chamberlain H., Lazar A. N., Darin E., Tatem A. J. 2023. Census disaggregated gridded population estimates for Kenya (2022), version 2.0. University of Southampton. doi:10.5258/SOTON/WP00762 **License** *These data may be distributed using a Creative Commons Attribution 4.0 International (CC BY 4.0) License, specified in legal code. Contact release[at]worldpop.org for more information*. The authors followed rigorous procedures designed to ensure that the used data, the applied method and thus the results are appropriate and of reasonable quality. If users encounter apparent errors or misstatements, they should contact WorldPop at release[at]worldpop.org. WorldPop, University of Southampton, and their sponsors offer these data on a "where is, as is" basis; do not offer an express or implied warranty of any kind; do not guarantee the quality, applicability, accuracy, reliability or completeness of any data provided; and shall not be liable for incidental, consequential, or special damages arising out of the use of any data that they offer.
The two layers contained within the GRID3 KEN - Settlement Extents v3.0 include: GRID3_KEN_settlement_extents_v3.gpkg: a spatial layer representing settlement polygons. GRID3_KEN_settlement_grid_v3.gpkg: a spatial layer representing the centroids of settled grid cells. This is the settlement extents layer. The current version supersedes GRID3 KEN - Settlement Extents v2.0; the following changes were made: Development of a new methodology to derive settlement polygons with open data. Estimate a probability value for settlement polygons For more information on data inputs, methodology, and codebooks please see the Data Release Notes. Recommended Citation: Center for International Earth Science Information Network (CIESIN), Columbia University. 2024. GRID3 KEN - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/6hnz-fr54. Accessed [DAY MONTH YEAR]. Terms of use: Users are free to download, store, access, use, copy, adapt, transform, alter, arrange, build upon, distribute and transmit this work and any derivative works. Attribution of the source must be provided, and further distribution of this work or derived work must maintain the same terms of data use and license as set forth in this Terms of Use. Copyright 2024. The Trustees of Columbia University in the City of New York. Data license: The data and accompanying document are licensed under a Creative Commons Attribution-ShareAlike 4.0 International, CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0) and specified in legal code (https://creativecommons.org/licenses/by-sa/4.0/legalcode). Contacts and data queries: The authors of this dataset appreciate feedback regarding the data, including suggestions, discovery of errors, difficulties in using the data, and format preferences. For dataset-related questions, please send an email to: info@ciesin.columbia.edu
The two layers contained within the GRID3 KEN - Settlement Extents v3.0 include: GRID3_KEN_settlement_extents_v3.gpkg: a spatial layer representing settlement polygons. GRID3_KEN_settlement_grid_v3.gpkg: a spatial layer representing the centroids of settled grid cells. This is the settlement extents layer. The current version supersedes GRID3 KEN - Settlement Extents v2.0; the following changes were made: Development of a new methodology to derive settlement polygons with open data. Estimate a probability value for settlement polygons For more information on data inputs, methodology, and codebooks please see the Data Release Notes. Recommended Citation: Center for International Earth Science Information Network (CIESIN), Columbia University. 2024. GRID3 KEN - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/6hnz-fr54. Accessed [DAY MONTH YEAR]. Terms of use: Users are free to download, store, access, use, copy, adapt, transform, alter, arrange, build upon, distribute and transmit this work and any derivative works. Attribution of the source must be provided, and further distribution of this work or derived work must maintain the same terms of data use and license as set forth in this Terms of Use. Copyright 2024. The Trustees of Columbia University in the City of New York. Data license: The data and accompanying document are licensed under a Creative Commons Attribution-ShareAlike 4.0 International, CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0) and specified in legal code (https://creativecommons.org/licenses/by-sa/4.0/legalcode). Contacts and data queries: The authors of this dataset appreciate feedback regarding the data, including suggestions, discovery of errors, difficulties in using the data, and format preferences. For dataset-related questions, please send an email to: info@ciesin.columbia.edu
Indexed by OrionGIS from Kenya Open Data (opendata.go.ke, ArcGIS Hub-hosted). Data is loaded from the publisher's own server when you use it. Permanent link