The database constitutes a comprehensive set of settlement polygons nationwide. It is in geodatabase format and consists of three feature classes for built up areas (BUA), small settlement areas (SSA), and hamlets (hamlets).

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Western Sahara.

GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/

Keywords: built up areas, BUA, small settlement areas, SSA, hamlets, settlement aggregation, settlement extent, CIESIN, GRID3, Novel-

Center for International Earth Science Information Network

Novel-T

English

Columbia University Academic Commons

                                                                                     1     Data Release Statement GRID3 Western Sahara Settlement Extents Version 01 Alpha April 2020 Abstract  This document outlines the data sets used to construct a spatial database with settlement extents in Western Sahara. Limitations and use constraints are provided.  Data Set Citation  Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 Western Sahara Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-m2yb-q916. Accessed DAY MONTH YEAR  Data Use Constraints  Users are free to use, copy, distribute, transmit, and adapt the work for commercial and non-commercial purposes, without restriction, as long as clear attribution of the source is provided.  Copyright 2020. The Trustees of Columbia University in the City of New York. The data and accompanying document is licensed under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0) and specified in legal code (http://creativecommons.org/licenses/by/4.0/legalcode).  Contacts and Data Queries  GRID3 and Novel-T appreciates feedback regarding this data set, such as suggestions, discovery of errors, difficulties in using the data, and format preferences.   Please contact: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) Email: data.queries@grid3.org or  Novel-T Email: info@novel-t.ch                                                                                         2      Table of Contents  1. Introduction …………………………………………………………………………………..……….… 3 2. Input Data ………………………………………………………………………………………………… 3 2.1 Digitize Africa Building Footprints………………………………………………… 3 3. Dataset Descriptions ………………………………………………………………………………… 3 4. Known data limitations and disclaimer ……………………………………………………… 4 5. Acknowledgments ……………………………………………………………………………………. 5 6. References ……………………………………………………………………………………………….. 5                                                                                      3    1. Introduction  This document describes the steps followed to produce the Western Sahara Settlement Extents Version 01 database, which constitute a comprehensive set of settlement polygons nationwide. This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Western Sahara and by Novel-T for the Global Polio Eradication Initiative (GPEI). The initiative is funded by the Bill & Melinda Gates Foundation and the United Kingdom’s Department for International Development. It is implemented by WorldPop/Flowminder and the United Nations Population Fund, and  the Center for International Earth Science Information Network (CIESIN) at Columbia University.   2. Input Data   The settlement extents are a derived data set utilizing the Digitize Africa building footprints to create the GRID3 Western Sahara settlement extents database.    2.1 Digitize Africa Building Footprints  The building footprint layer was from the "Ecopia Landbase Africa powered by Maxar", website - "DigitizeAfrica.ai". The data was produced by Ecopia Tech Corporation, and Maxar Technologies, Inc. The layer covers the country of Western Sahara.    3. Dataset Descriptions  The data are in geodatabase format and consist of three feature classes for built up areas (BUA), small settlement areas (SSA), and hamlets (hamlets).   Extent: Western Sahara: Admin Level 0 Boundaries. The overall extent of the layer is limited to the overall extent of the building footprint data set and may not reflect the extent of official administrative boundaries.   Coordinate system: GCS WGS 1984  The settlement extents and classification are derived solely from the building footprints, and no ancillary datasets are used. The centerpoints of building footprint features are converted to a 3 arc-second raster grid of building densities, referred to throughout this document as building densities. Shell-up contours are then generated using the building density grid to delineate settled vs non-settled areas. The shell-up method includes contours that start at the lower bounds, but includes all grid cells with building densities to the upper bounds of the grid. For example, a shell up contour of 10 would include all grid cells with a building density of 10 or more.                                                                                       4  Contours with a building density of one or more are used to create the settlement extent polygons. The GRID3 Western Sahara settlement extents characterised building density into three (3) classes: built-up areas (bua_extents), small settlement areas (ssa_extents), and hamlets (hamlet_extents) (Inuwa,2014). These three classes of settlement agglomerations are presented below:   Built-up areas (BUAs) A built-up area (BUA) is generally an area of urbanisation with moderately-to-densely-spaced buildings and a visible grid of streets and blocks. Built up areas are characterized by contours with an area greater than or equal to 400,000 meters square that maintains a building density of thirteen or more across the entire area.  Small Settlements (SSAs) A small settlement (SSA) is a settled area of permanently inhabited structures and compounds of roughly a few hundred to a few thousand inhabitants. The housing pattern in SSAs is an assemblage of family compounds adjoining other similar habitations. Small settlement areas are characterized by having 50 or more buildings and are not a BUA.  Hamlet  (HAMLET) A hamlet is a collection of several compounds or sleeping houses in isolation from small settlements or urban areas. Hamlets are characterized as a collection of low-density settlements between one and 50 buildings and falls within 65 meters of one another.  The Geodatabase contains the following fields:   OBJECTID       ArcGIS Unique ID for each row SHAPE       Geometry type mgrs_code       Unique name generated using the Military Grid Reference System type        The settlement type as defined by a BUA, SSA, or hamlet Shape_Length     The shape length in geographic coordinates Shape_Area       The shape area in geographic coordinates GlobalID       Universal unique identifier   4. Known data limitations and disclaimer  The GRID3 settlement extents have not been visually inspected for false negatives. A settlement may exist for a location where there is no polygon. This may lead to settlements not being identified. Likewise, the GRID3 settlement extents have not been visually inspected for false positives. A settlement polygon may have been falsely identified as an actual settlement.   These data are part of ongoing work and is not guaranteed to be accurate and clean. If users encounter apparent errors or misstatements in the data, they should contact GRID3 at data.queries@grid3.org.                                                                                         5  CIESIN, Columbia University, 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.   5. Acknowledgments  Funding for the development and dissemination of this data set was provided by the Bill & Melinda Gates Foundation and the United Kingdom Department for International Development.   6. References  Barau, I., et al.  2014. Improving Polio Vaccination Coverage in Nigeria Through the Use of Geographic Information System Technology.  The Journal of Infectious Diseases 210(suppl_1): S102-S110, https://doi.org/10.1093/infdis/jiu010  Maxar Technologies, Inc. and Ecopia Tech Corporation. 2020. Ecopia Landbase Africa powered by Maxar, website - "DigitizeAfrica.ai".

GRID3 Western Sahara Settlement Extents Version 01, Alpha

NOTE: This version of the Tanzania settlement extents has been superseded by "GRID3 Tanzania Settlement Extents, Version 01.01", now available here: https://doi.org/10.7916/d8-vhma-fw24

The dataset consists of settlement extents across Tanzania, as well as accompanying population estimates for each settlement extent.

This data product contains all information contained in the previous GRID3 Tanzania Settlement Extents, Version 01 Alpha product, with updates. Updates in this version include: a single settlement extent feature class (Alpha contained the same data in three (3) separate feature class layers: BUAs, SSAs & Hamlets), and new population estimate fields ("Population" and "Pop_UN_adj") for each settlement extent .

This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/

Keywords: Settlements, Hamlets, Built-up Areas (BUA), Small Settlement Areas (SSA)

The programme is funded by the Bill & Melinda Gates Foundation and United Kingdom's Foreign, Commonwealth, Development Office. It is implemented by Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund (UNFPA), and the Center for International Earth Science Information Network (CIESIN) at Columbia University

                                                                                     1                                                                                        Data Release Statement  GRID3 Tanzania Settlement Extents, Version 01   July 2021  Abstract    This document outlines the methodological approach and data sources used to construct the “GRID3 Tanzania Settlement Extents, Version 01 dataset.” The dataset consists of settlement extents across Tanzania , as well as accompanying population estimates for each settlement extent. Limitations and use constraints are provided.    Dataset citation    Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2021. GRID3 Tanzania Settlement Extents, Version 01. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). htps://doi.org/10.7916/d8-5cm5-cj43 .Accessed DAY MONTH YEAR.    Data use constraints    Users are free to use, copy, distribute, transmit, and adapt the work for commercial and non-commercial purposes, without restriction, as long as clear attribution of the source is provided.    Copyright 2021. The Trustees of Columbia University in the City of New York.   The data and accompanying document is licensed under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0) and specified in legal code (http://creativecommons.org/licenses/by/4.0/legalcode).    Contacts and data queries    GRID3 appreciates feedback regarding this dataset, such as suggestions, discovery of errors, difficulties in using the data, and format preferences.     For dataset-related questions, please send an email to any of the following organisations:  GRID3: data.queries@grid3.org                                                                                          2     Table of Contents    Introduction 3 Methodological approach 3 Input data 3 Methods 4 Dataset description 6 Dataset codebook 7 Version History 8 Known data limitations and disclaimer 8 Acknowledgments 9 References 9                                                                                        3    Introduction    Settlement extents are polygons representing areas where there is likely a human settlement based on the presence of buildings detected in satellite imagery. Settlement extents are not meant to represent the boundaries of an administrative unit or locality. A single settlement extent may be made up of multiple localities, especially in urban areas. Each settlement extent has an associated population estimate. This document details the methodology applied to produce the dataset “GRID3 Tanzania Settlement Extents, Version 01.”   This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The programme is funded by the Bill & Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office. It is implemented by the Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University.   Methodological approach        Input data    Settlement extents and associated population estimates are derived from two primary input datasets: building footprints and population estimates (Table 1). Where available, additional bottom-up modelled population estimates are also included.   Table 1. Input datasets Data Description  Source Building footprints Building footprints are derived by the Ecopia Tech Corporation using a feature extraction algorithm. The dataset consists of polygon data delineating rooftops present in satellite imagery captured between 2009 and 2019.  Maxar Technologies, Inc. and Ecopia Tech Corporation. 2020. Ecopia Landbase Africa powered by Maxar. Available at DigitizeAfrica.ai WorldPop Population estimates  Population estimates (2020): Top-down modeled population estimates (100-meter resolution) produced by WorldPop at the University of Bondarenko M., Kerr D., Sorichetta A., and Tatem, A.J. 2020. Census/projection-                                                                                     4  Southhampton. Units: Total population per pixel. Extent: Tanzania https://www.worldpop.org/methods/populations  UN-adjusted Population estimates (2020): Identical to above, but country population totals for Tanzania are adjusted to match estimates prepared by: United Nations, Department of Economic and Social Affairs, Population Division (2019). World Population Prospects 2019, Online Edition. Rev. 1. disaggregated gridded population datasets for 51 countries across sub-Saharan Africa in 2020 using building footprints. WorldPop, University of Southampton, UK.  doi:10.5258/SOTON/WP00682  doi:10.5258/SOTON/WP00683 (UN-adjusted)      Methods  Both the settlements’ extents and classification are derived solely from Ecopia’s building footprints. Data analysis and processing were achieved entirely using Esri’s ArcGIS software (Pro version 2.7.3), it’s native module arcpy, and open source python library pandas 1.3.0.   The center points of building footprint features are converted to a raster grid (3 arc-second resolution) of building densities (i.e. total number of building points within each cell), referred to throughout this document as “building densities.” The ArcGIS Pro “Contour” tool was used to generate shell-up contours from the building density grid to delineate settled versus non-settled areas. The shell-up method includes contours that start at the lower bounds, but includes all grid cells with building densities to the upper bounds of the grid. For example, a shell-up contour of 10 would include all grid cells with a building density of 10 or more. Contours with a building density of one or more are used to create the settlement extent polygons (see Figure 1).                                                                                        5   Figure 1: Part 1: Illustration of methods used to generate settlement extents: 1) Building footprints (Ecopia/Maxar) are projected to map and 2) Building footprints are converted to points. 3) Building points are converted to a building density raster layer at 100m resolution. Values represent the total number of building points within each cell. 4) Shell-up contours are generated around building density cells, and building counts within each settlement extent are summed. Contour geometry is smoothed to produce final settlement extent polygons. Part 2: Illustration of methods to generate population estimates for each settlement extent: 5) A population raster (100m, WorldPop) is added to the map and 6) cells are converted to points. Each population point is assigned to the nearest settlement extent and population values are summed to produce population estimates. Steps 5 and 6 are performed once for a WorldPop raster and once for a UN-adjusted WorldPop raster. Bottom panel represents final                                                                                      6  settlement extents with associated population count (rounded to nearest integer for clarity).  The GRID3 Tanzania settlement extents are then classified (based on building density) into three classes: built-up areas (BUA), small settlement areas (SSA), and Hamlets (Barau et al., 2014).    Table 2. Settlement extent classification Settlement class Description  Built-up areas (BUAs) A built-up area (BUA) is generally an area of urbanisation with moderately-to-densely-spaced buildings and a visible grid of streets and blocks. BUAs are characterised as polygons that maintain a 100 m2 building density of  13 or more across  an area greater than or equal to 0.4 km2. Small Settlements (SSAs) A small settlement (SSA) is a settled area of permanently inhabited structures and compounds of roughly a few hundred to a few thousand inhabitants. The housing pattern in SSAs is an assemblage of family compounds adjoining other similar habitations. Small settlement areas are characterised as polygons containing 50 or more buildings and not a BUA. Hamlet  A hamlet is a collection of several compounds or sleeping houses in isolation from small settlements or urban areas. Hamlets are characterised as polygons containing between 1 and 49 buildings.  The population estimates for each settlement extent were calculated using population estimates from WorldPop. Individual, country-constrained population raster cells and their associated population estimate (100m resolution) were converted to individual points and joined to the nearest settlement extent. Finally, the values within a settlement extent were summed to obtain the total population for each settlement extent. Settlement extents from population estimates can be found in the “Population” and “Pop_UN_adj” fields.     Dataset description  The data are in geodatabase format and consist of a single-feature class. An example of data is shown on Figure 3.                                                                                       7    Extent: Tanzania: Admin Level 0 Boundaries. The overall extent of the layer is limited to the overall extent of the building footprint dataset and may not reflect the extent of official administrative boundaries.     Coordinate system: GCS WGS 1984     Figure 3: Sample map depicting a settlement extent data layer, with building footprint layer for reference. Note: Building footprint layers are not included in this data product.                                                                                                8   Dataset codebook  Field Description OBJECTID Default ESRI field: Unique sequential numeric identifier maintained by the database. Shape Default ESRI field: Geometry type  MGRS_Code Unique name generated using the Military Grid Reference System  Country Country name  ISO Three-letter country ISO code Type The settlement type as defined by a built-up area, small-settlement area, or hamlet  Population Total population estimate for settlement extent derived from constrained WorldPop raster Pop_UN_adj Total population estimate for settlement extent derived from constrained and UN-adjusted WorldPop raster Shape_Length Default ESRI field: The shape length in geographic coordinates (decimal degrees)  Shape_Area Default ESRI field: The shape area in geographic coordinates (decimal degrees)   Version History This data product contains all information contained in the previous “GRID3 Tanzania Settlement Extents, Version 01 Alpha” product, with updates. Updates in this version include: a single settlement extent feature class (alpha version contains the same data in three separate feature class layers: BUAs, SSAs, and hamlets) and new population estimate fields (Population and Pop_UN_adj) for each settlement extent.   Known data limitations and disclaimer    The “GRID3 Tanzania Settlement Extents, Version 01” has not been visually inspected for false negatives. A settlement may exist for a location where there is no building footprint data and consequently no settlement extent. This may lead to settlements not being identified. Likewise, the GRID3 settlement extents have not been visually inspected for false positives. A settlement polygon may have been falsely identified as                                                                                      9  an actual settlement. The type or use of buildings (e.g. residential, non-residential, mixed use, shed, etc) are not known.    CIESIN, Columbia University, and GRID3 follow procedures designed to ensure that data disseminated by project are of reasonable quality. If, despite these procedures, users encounter apparent errors or misstatements in the data, they should contact GRID3 at data.queries@grid3.org. CIESIN, Columbia University, and their sponsors do not guarantee the accuracy, reliability, or completeness of any data provided. We provide these data without warranty of any kind whatsoever, either expressed or implied, and shall not be liable for incidental, consequential, or special damages arising out of the use of any data provided.      Acknowledgments    Funding for the development and dissemination of this dataset was provided by the Bill & Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office.     References    Barau, I., et al.  2014. “Improving Polio Vaccination Coverage in Nigeria Through the Use of Geographic Information System Technology, The Journal of Infectious Diseases, Volume 210, Issue suppl_1, Pages S102–S110, https://doi.org/10.1093/infdis/jiu010   Bondarenko M., Kerr D., Sorichetta A., and Tatem, A.J. 2020. “Census/projection-disaggregated gridded population datasets for 51 countries across sub-Saharan Africa in 2020 using building footprints.” WorldPop, University of Southampton, UK. doi:10.5258/SOTON/WP00682; doi:10.5258/SOTON/WP00683  Esri Inc. 2020.  ArcGIS Pro (Version 2.7.3). Esri Inc. https://www.esri.com/en-us/arcgis/products/arcgis-pro/overview  Maxar Technologies, Inc. and Ecopia Tech Corporation. 2020. Ecopia Landbase Africa powered by Maxar, website - "DigitizeAfrica.ai".  McKinney, Wes. 2010. Data Structures for Statistical Computing in Python (Pandas), Proceedings of the 9th Python in Science Conference, 51-56   

GRID3 Tanzania Settlement Extents, Version 01

NOTE: This version of the Mali settlement extents has been superseded by "GRID3 Mali Settlement Extents, Version 01.01", now available here: https://doi.org/10.7916/d8-hr0y-v173

The database constitutes a comprehensive set of settlement polygons nationwide. It is in geodatabase format and consists of three feature classes for built up areas (BUA), small settlement areas (SSA), and hamlets (hamlets).

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Mali.

GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/

Keywords: built up areas, BUA, small settlement areas, SSA, hamlets, settlement aggregation, settlement extent, CIESIN, GRID3, Novel-

                                                                                     1     Data Release Statement GRID3 Mali Settlement Extents Version 01 Alpha April 2020 Abstract  This document outlines the data sets used to construct a spatial database with settlement extents in Mali. Limitations and use constraints are provided.  Data Set Citation  Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 Mali Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-pejd-bf71. Accessed DAY MONTH YEAR  Data Use Constraints  Users are free to use, copy, distribute, transmit, and adapt the work for commercial and non-commercial purposes, without restriction, as long as clear attribution of the source is provided.  Copyright 2020. The Trustees of Columbia University in the City of New York. The data and accompanying document is licensed under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0) and specified in legal code (http://creativecommons.org/licenses/by/4.0/legalcode).  Contacts and Data Queries  GRID3 and Novel-T appreciates feedback regarding this data set, such as suggestions, discovery of errors, difficulties in using the data, and format preferences.   Please contact: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) Email: data.queries@grid3.org or  Novel-T Email: info@novel-t.ch                                                                                         2      Table of Contents  1. Introduction …………………………………………………………………………………..……….… 3 2. Input Data ………………………………………………………………………………………………… 3 2.1 Digitize Africa Building Footprints………………………………………………… 3 3. Dataset Descriptions ………………………………………………………………………………… 3 4. Known data limitations and disclaimer ……………………………………………………… 4 5. Acknowledgments ……………………………………………………………………………………. 5 6. References ……………………………………………………………………………………………….. 5                                                                                      3    1. Introduction  This document describes the steps followed to produce the Mali Settlement Extents Version 01 database, which constitute a comprehensive set of settlement polygons nationwide. This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Mali and by Novel-T for the Global Polio Eradication Initiative (GPEI). The initiative is funded by the Bill & Melinda Gates Foundation and the United Kingdom’s Department for International Development. It is implemented by WorldPop/Flowminder and the United Nations Population Fund, and  the Center for International Earth Science Information Network (CIESIN) at Columbia University.   2. Input Data   The settlement extents are a derived data set utilizing the Digitize Africa building footprints to create the GRID3 Mali settlement extents database.    2.1 Digitize Africa Building Footprints  The building footprint layer was from the "Ecopia Landbase Africa powered by Maxar", website - "DigitizeAfrica.ai". The data was produced by Ecopia Tech Corporation, and Maxar Technologies, Inc. The layer covers the country of Mali.    3. Dataset Descriptions  The data are in geodatabase format and consist of three feature classes for built up areas (BUA), small settlement areas (SSA), and hamlets (hamlets).   Extent: Mali: Admin Level 0 Boundaries. The overall extent of the layer is limited to the overall extent of the building footprint data set and may not reflect the extent of official administrative boundaries.   Coordinate system: GCS WGS 1984  The settlement extents and classification are derived solely from the building footprints, and no ancillary datasets are used. The centerpoints of building footprint features are converted to a 3 arc-second raster grid of building densities, referred to throughout this document as building densities. Shell-up contours are then generated using the building density grid to delineate settled vs non-settled areas. The shell-up method includes contours that start at the lower bounds, but includes all grid cells with building densities to the upper bounds of the grid. For example, a shell up contour of 10 would include all grid cells with a building density of 10 or more.                                                                                       4  Contours with a building density of one or more are used to create the settlement extent polygons. The GRID3 Mali settlement extents characterised building density into three (3) classes: built-up areas (bua_extents), small settlement areas (ssa_extents), and hamlets (hamlet_extents) (Inuwa,2014). These three classes of settlement agglomerations are presented below:   Built-up areas (BUAs) A built-up area (BUA) is generally an area of urbanisation with moderately-to-densely-spaced buildings and a visible grid of streets and blocks. Built up areas are characterized by contours with an area greater than or equal to 400,000 meters square that maintains a building density of thirteen or more across the entire area.  Small Settlements (SSAs) A small settlement (SSA) is a settled area of permanently inhabited structures and compounds of roughly a few hundred to a few thousand inhabitants. The housing pattern in SSAs is an assemblage of family compounds adjoining other similar habitations. Small settlement areas are characterized by having 50 or more buildings and are not a BUA.  Hamlet  (HAMLET) A hamlet is a collection of several compounds or sleeping houses in isolation from small settlements or urban areas. Hamlets are characterized as a collection of low-density settlements between one and 50 buildings and falls within 65 meters of one another.  The Geodatabase contains the following fields:   OBJECTID       ArcGIS Unique ID for each row SHAPE       Geometry type mgrs_code       Unique name generated using the Military Grid Reference System type        The settlement type as defined by a BUA, SSA, or hamlet Shape_Length     The shape length in geographic coordinates Shape_Area       The shape area in geographic coordinates GlobalID       Universal unique identifier   4. Known data limitations and disclaimer  The GRID3 settlement extents have not been visually inspected for false negatives. A settlement may exist for a location where there is no polygon. This may lead to settlements not being identified. Likewise, the GRID3 settlement extents have not been visually inspected for false positives. A settlement polygon may have been falsely identified as an actual settlement.   These data are part of ongoing work and is not guaranteed to be accurate and clean. If users encounter apparent errors or misstatements in the data, they should contact GRID3 at data.queries@grid3.org.                                                                                         5  CIESIN, Columbia University, 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.   5. Acknowledgments  Funding for the development and dissemination of this data set was provided by the Bill & Melinda Gates Foundation and the United Kingdom Department for International Development.   6. References  Barau, I., et al.  2014. Improving Polio Vaccination Coverage in Nigeria Through the Use of Geographic Information System Technology.  The Journal of Infectious Diseases 210(suppl_1): S102-S110, https://doi.org/10.1093/infdis/jiu010  Maxar Technologies, Inc. and Ecopia Tech Corporation. 2020. Ecopia Landbase Africa powered by Maxar, website - "DigitizeAfrica.ai".

GRID3 Mali Settlement Extents Version 01, Alpha

NOTE: This version of the Tanzania settlement extents has been superseded by "GRID3 Tanzania Settlement Extents, Version 01.01", now available here: https://doi.org/10.7916/d8-vhma-fw24

The database constitutes a comprehensive set of settlement polygons nationwide.  It is in geodatabase format and consists of three feature classes for built up areas (BUA), small settlement areas (SSA), and hamlets (hamlets).

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative.

GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/

Keywords: built up areas, BUA, small settlement areas, SSA, hamlets, settlement aggregation, settlement extent, CIESIN, GRID3, Novel-

                                                                                     1     Data Release Statement GRID3 Tanzania Settlement Extents Version 01 Alpha September 2020 Abstract  This document outlines the data sets used to construct a spatial database with settlement extents in Tanzania. Limitations and use constraints are provided.  Data Set Citation  Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 Tanzania Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-ve7a-dm77 . Accessed DAY MONTH YEAR  Data Use Constraints  Users are free to use, copy, distribute, transmit, and adapt the work for commercial and non-commercial purposes, without restriction, as long as clear attribution of the source is provided.  Copyright 2020. The Trustees of Columbia University in the City of New York. The data and accompanying document is licensed under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0) and specified in legal code (http://creativecommons.org/licenses/by/4.0/legalcode).  Contacts and Data Queries  GRID3 and Novel-T appreciates feedback regarding this data set, such as suggestions, discovery of errors, difficulties in using the data, and format preferences.   Please contact: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) Email: data.queries@grid3.org or  Novel-T Email: info@novel-t.ch                                                                                           2     Table of Contents  1. Introduction …………………………………………………………………………………..……….… 3 2. Input Data ………………………………………………………………………………………………… 3 2.1 Digitize Africa Building Footprints………………………………………………… 3 3. Dataset Descriptions ………………………………………………………………………………… 3 4. Known data limitations and disclaimer ……………………………………………………… 4 5. Acknowledgments ……………………………………………………………………………………. 5 6. References ……………………………………………………………………………………………….. 5                                                                                        3   1. Introduction  This document describes the steps followed to produce the Tanzania Settlement Extents Version 01 database, which constitute a comprehensive set of settlement polygons nationwide. This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Tanzania and by Novel-T for the Global Polio Eradication Initiative (GPEI). The initiative is funded by the Bill & Melinda Gates Foundation and UK aid from the UK government. It is implemented by WorldPop/Flowminder and the United Nations Population Fund, and  the Center for International Earth Science Information Network (CIESIN) at Columbia University.   2. Input Data   The settlement extents are a derived data set utilizing the Digitize Africa building footprints to create the GRID3 Tanzania settlement extents database.    2.1 Digitize Africa Building Footprints  The building footprint layer was from the "Ecopia Landbase Africa powered by Maxar", website - "DigitizeAfrica.ai". The data was produced by Ecopia Tech Corporation, and Maxar Technologies, Inc. The layer covers the country of Tanzania.    3. Dataset Descriptions  The data are in geodatabase format and consist of three feature classes for built up areas (BUA), small settlement areas (SSA), and hamlets (hamlets).   Extent: Tanzania: Admin Level 0 Boundaries. The overall extent of the layer is limited to the overall extent of the building footprint data set and may not reflect the extent of official administrative boundaries.   Coordinate system: GCS WGS 1984  The settlement extents and classification are derived solely from the building footprints, and no ancillary datasets are used. The centerpoints of building footprint features are converted to a 3 arc-second raster grid of building densities, referred to throughout this document as building densities. Shell-up contours are then generated using the building density grid to delineate settled vs non-settled areas. The shell-up method includes contours that start at the lower bounds, but includes all grid cells with building densities to the upper bounds of the grid. For example, a shell up contour of 10 would include all grid cells with a building density of 10 or more.  Contours with a building density of one or more are used to create the settlement extent polygons. The GRID3 Tanzania settlement extents characterised building                                                                                      4  density into three (3) classes: built-up areas (bua_extents), small settlement areas (ssa_extents), and hamlets (hamlet_extents) (Inuwa,2014). These three classes of settlement agglomerations are presented below:   Built-up areas (BUAs) A built-up area (BUA) is generally an area of urbanisation with moderately-to-densely-spaced buildings and a visible grid of streets and blocks. Built up areas are characterized by contours with an area greater than or equal to 400,000 meters square that maintains a building density of thirteen or more across the entire area.  Small Settlements (SSAs) A small settlement (SSA) is a settled area of permanently inhabited structures and compounds of roughly a few hundred to a few thousand inhabitants. The housing pattern in SSAs is an assemblage of family compounds adjoining other similar habitations. Small settlement areas are characterized by having 50 or more buildings and are not a BUA.  Hamlet  (HAMLET) A hamlet is a collection of several compounds or sleeping houses in isolation from small settlements or urban areas. Hamlets are characterized as a collection of low-density settlements between one and 50 buildings and falls within 65 meters of one another.  The Geodatabase contains the following fields:   OBJECTID       ArcGIS Unique ID for each row SHAPE       Geometry type mgrs_code       Unique name generated using the Military Grid Reference System type        The settlement type as defined by a BUA, SSA, or hamlet Shape_Length     The shape length in geographic coordinates Shape_Area       The shape area in geographic coordinates GlobalID       Universal unique identifier   4. Known data limitations and disclaimer  The GRID3 settlement extents have not been visually inspected for false negatives. A settlement may exist for a location where there is no polygon. This may lead to settlements not being identified. Likewise, the GRID3 settlement extents have not been visually inspected for false positives. A settlement polygon may have been falsely identified as an actual settlement.   These data are part of ongoing work and is not guaranteed to be accurate and clean. If users encounter apparent errors or misstatements in the data, they should contact GRID3 at data.queries@grid3.org.    CIESIN, Columbia University, 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                                                                                      5  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.   5. Acknowledgments  Funding for the development and dissemination of this data set was provided by the Bill & Melinda Gates Foundation and UK aid from the UK government.   6. References  Barau, I., et al.  2014. Improving Polio Vaccination Coverage in Nigeria Through the Use of Geographic Information System Technology.  The Journal of Infectious Diseases 210(suppl_1): S102-S110, https://doi.org/10.1093/infdis/jiu010  Maxar Technologies, Inc. and Ecopia Tech Corporation. 2020. Ecopia Landbase Africa powered by Maxar, website - "DigitizeAfrica.ai". 

GRID3 Tanzania Settlement Extents Version 01, Alpha

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GRID3 Western Sahara Settlement Extents Version 01, Alpha

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