The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The All Roads Shapefile includes all features within the MTDB Super Class "Road/Path Features" distinguished where the MAF/TIGER Feature Classification Code (MTFCC) for the feature in MTDB that begins with "S". This includes all primary, secondary, local neighborhood, and rural roads, city streets, vehicular trails (4wd), ramps, service drives, alleys, parking lot roads, private roads for service vehicles (logging, oil fields, ranches, etc.), bike paths or trails, bridle/horse paths, walkways/pedestrian trails, and stairways.

Ground survey route covered by NTP team for the September 7, 2021, Southampton, ON downburst. Ground survey conducted September 9, 2021. Survey route tracked by iPad while surveying in car and on foot.View event map here

DATASET: Version 4.0 2010 estimates of numbers of people per grid square for 2010, 2015, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/), and remaining unadjusted. REGION: Africa SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: WorldPop naming convention applied; example SSD_ppp_2010_adj_v4.tif = South Sudan population per pixel (ppp) map for 2010 adjusted to match UN national estimates (adj), dataset version 4 (v4). DATE OF PRODUCTION: Jan 2013 (Updated July 2018) CITATION: WorldPop. 2013. South Sudan 100m Population, Version 4. University of Southampton. DOI: 10.5258/SOTON/WP00642.

Additional photos collected via drone for the September 7, 2021, Southampton, ON event. Ground survey conducted September 9, 2021. DJI Air 2S used to capture 217 images. Does not include videos or drone mapping photos [where applicable], View event map here

Francis S. Gabreski Airport is a general aviation airport utilized by private aviation, corporate businesses, and air taxi services located in the Town of Southampton. This dataset summarizes the airport operations (takeoff or landing) activity, totaling the number of flights utilizing the airport each month.

The zip files contain the following files:SLE_population_v1_0_gridded.tifThis geotiff raster (.tif), at a resolution of 3 arc (approximately 100m at the equator), contains estimated population counts per grid cell across Sierra Leone. The projection is Geographic Coordinate System, WGS84. ‘NoData’ values represent areas that were mapped as unsettled based on building footprints from “Digitize Africa data © 2020 Maxar Technologies, Ecopia.AI”. These data are stored as floating-point numbers rather than integers to avoid rounding errors in aggregated population totals for larger areas.SLE_population_v1_0_agesex.zipThis zip file contains 36 geotiff rasters (.tif) at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Each raster contains estimated counts per grid cell for an age-sex group. The file names refer to the age-sex group represented by the raster. Age-sex group labels beginning with “f” are female populations and labels beginning with “m” are male populations. The age group labels refer to the first year of the age range. For example: “f_0” is females less than one year old. “f1” is females 1 to 4 years old. “f5” is females 5 to 9 years old. “f10” is females 10 to 14 years old. This pattern continues for each 5 year interval up to 80. “f80” is females greater than 80 years old. The labelling is the same for males: “m0”, “m1”, “m5”, “m10”, ... , “m80”.Data Citation: WorldPop and Statistics Sierra Leone. 2020. Census disaggregated gridded population estimates for Sierra Leone (2015), version 1.0. University of Southampton. doi:10.5258/SOTON/WP00668 CREDITS: Oliver Pannell (WorldPop) supported the generation of inputs for the application of the Random Forest (RF)- based dasymetric mapping approach developed by Stevens et al. (2015). The disaggregation was done by Maksym Bondarenko (WorldPop), using the Random Forests population modelling R scripts (Bondarenko et al., 2020), with oversight from Alessandro Sorichetta (WorldPop). Doug Leasure (WorldPop) prepared the mastergrid, tiles, and SQLite database. The sections-level administrative boundaries were provided by Jolynn Schmidt and Eniko Kelly-Voicu (CIESIN). The whole WorldPop group and GRID3 partners are acknowledged for overall project support.These data were produced by the WorldPop Research Group at the University of Southampton. This work is part of the GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development) programme funded by the Bill & Melinda Gates Foundation (BMGF) and the United Kingdom’s Foreign, Commonwealth & Development Office. It is implemented by Columbia University’s Center for International Earth Science Information Network (CIESIN), the United Nations Population Fund (UNFPA), WorldPop at the University of Southampton, and the Flowminder Foundation.The downloadable Metadata provides more information about Source Data, Methods Overview, Assumptions & Limitations and Works and Data CitedContact release@worldpop.org for more information or go here.

Estimates of 2020 total number of people per grid square, adjusted to match the corresponding UNPD 2020 estimates and broken down by gender and age groupings, produced using Built-Settlement Growth Model (BSGM) outputs.

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 Bill and Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office (INV-009579, formerly OPP1182425), and GRID3 COVID-19 Support Scale-up (INV-018067). Project partners included the United Nations Population Fund, Center for International Earth Science Information Network in the Columbia Climate School at Columbia University, and the Flowminder Foundation. The new age-structured population estimates are based on the existing Census-based gridded population estimates for Burkina Faso (2019), version 1.0 (WorldPop and Institut National de la Statistique et de la Demographie du Burkina Faso, 2020). Duygu Cihan, Heather Chamberlain and Thomas Abbott led the data processing, with advice from Édith Darin.RELEASE CONTENT Aggregated_BFA_under18_population_100m.tif Aggregated_BFA_18_45_population_100m.tif Aggregated_BFA_over45_population_100m.tifFILE DESCRIPTIONS The coordinate system for all GIS files is the geographic coordinate system WGS84 (World Geodetic System 1984, EPSG: 4326). Aggregated_BFA_ under18_population _100m.tifThis geotiff raster, at a spatial resolution of 3 arc-seconds (approximately 100m at the equator), contains estimates of the total population of persons aged under 18 (0-17) per grid cell across Burkina Faso. NA values represent areas that were mapped as unsettled based on gridded building patterns derived from building footprints (Dooley and Tatem, 2020). These data are stored as floating-point numbers rather than integers to avoid rounding errors in aggregated population totals for larger areas.Aggregated_BFA_18_45_population_100m.tif This geotiff raster, at a spatial resolution of 3 arc-seconds (approximately 100m at the equator), contains estimates of the total population of persons aged 18 to 45 (18-45) per grid cell across Burkina Faso. NA values represent areas that were mapped as unsettled based on gridded building patterns derived from building footprints (Dooley and Tatem, 2020). These data are stored as floating-point numbers rather than integers to avoid rounding errors in aggregated population totals for larger areas. Aggregated_BFA_over45_population_100m.tif This geotiff raster, at a spatial resolution of 3 arc-seconds (approximately 100m at the equator), contains estimates of the total population of persons aged over 45 (46+) per grid cell across Burkina Faso. NA values represent areas that were mapped as unsettled based on gridded building patterns derived from building footprints (Dooley and Tatem, 2020). These data are stored as floating-point numbers rather than integers to avoid rounding errors in aggregated population totals for larger areas.METHODS OVERVIEW Processing: The existing 2019 gridded population estimates (WorldPop and Institut National de la Statistique et de la Demographie du Burkina Faso, 2020) include age- and sex- structured population estimates for 5 year age classes, based on the age and sex breakdown of population totals at the national level, from the preliminary census results. A Sprague multiplier approach was used to further disaggregate the 5-year age classes at the national level, to create three custom age-classes (under 18, 18-45 and over 45). The population for each of these custom age classes, was calculated as the proportion of the total population at the national level. This proportion was applied to the count of total population at the grid cell level.ASSUMPTIONS AND LIMITATIONS The custom age classes are estimated using a Sprague multiplier approach to interpolate the 5-year age classes and provide the population for a single year age class, which is then summed to provide the custom age classes. Interpolation introduces uncertainty in the estimates.The population estimates for the custom age classes were calculated from national level totals for 5-year age classes. A constant age-structure across all grid cells was assumed in applying the national proportions for the custom age classes to the grid cell level.RELEASE HISTORYVersion 1.0 (25/05/2022) - Original release of this data set.WORKS CITEDDooley, C. A. and Tatem, A.J. 2020. Gridded maps of building patterns throughout sub-Saharan Africa, version 1.0. University of Southampton: Southampton, UK. Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. https://dx.doi.org/10.5258/SOTON/WP00666.WorldPop and Institut National de la Statistique et de la Demographie du Burkina Faso. 2020. Census-based gridded population estimates for Burkina Faso (2019), version 1.0. WorldPop, University of Southampton. https://dx.doi.org/10.5258/SOTON/WP00687

WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by the Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00646

DATASET: Alpha version 2010 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/). REGION: Africa SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available. DATE OF PRODUCTION: January 2013

DATASET: Alpha version 2008 estimates of proportion of people per grid square living in poverty, as defined by the Multidimensional Poverty Index (http://www.ophi.org.uk/policy/multidimensional-poverty-index/), and associated uncertainty metrics. REGION: Africa SPATIAL RESOLUTION: 0.00833333 decimal degrees (approx 1km at the equator) PROJECTION: Geographic, WGS84 UNITS: Proportion of residents living in MPI-defined poverty (poverty dataset); 95% credible interval (uncertainty dataset) MAPPING APPROACH: Bayesian model-based geostatistics in combination with high resolution gridded spatial covariates applied to GPS-located household survey data on poverty from the DHS and/or LSMS programs. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Examples - ken08povmpi.tif = Kenya (ken) MPI poverty map for 2008. ken08povmpi-uncert.tif = uncertainty dataset showing 95% credible intervals. DATE OF PRODUCTION: January 2013 CITATION: Tatem AJ, Gething PW, Bhatt S, Weiss D and Pezzulo C (2013) Pilot high resolution poverty maps, University of Southampton/Oxford.

DATASET: Alpha version 2010 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/). REGION: Africa SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available. DATE OF PRODUCTION: January 2013