Zoom to desired area, click in the map and click the link to download 2016 Aerial Imagery at 3" resolution of the selected Index Grid. Image downloads are a .zip MrSid file with the .sid and the .sdw. The .sdw contains the georeferencing information for the .sid image.

Download the entire imagery for Dunwoody here: https://dungis.dunwoodyga.gov/SIDZIP/

Download / Reference / get a spreadsheet of the Image Index Grid Polygon here: https://get-dunwoody.opendata.arcgis.com/datasets/aerial-image-index-grid-layer

Originally produced by the Farm Security Administration, these are georeferenced aerial images from Morton County, North Dakota. Historic print images housed at the Mandan, North Dakota ARS Long-Term Agricultural Research facility were digitized, georeferenced, and processed for use in both professional and consumer level GIS applications, or in photo-editing applications. The original images were produced by the Farm Security Administration to monitor government compliance for farm land agreements. Current applications include assessing land use change over time with regard to erosion, land cover, and natural and man-made structures. Not for use in high precision applications. Resources in this dataset:Resource Title: 1938_AZY_3_89. File Name: 1938_AZY_3_89_0.zipResource Description: Contains IIQ, JPG, OVR, XML, AUX, and TIF files processed in ArcMap / ArcGIS that can be used in ArcGIS applications, or in other photo or geospatial applications. Resource Title: 1938 Mosaic Index. File Name: 1938_mosaic_index_1.zipResource Description: This is the index key for the 1938 Mandan aerial images from Morton County, ND. To find the geographic location for each uploaded 1938 image, consult this map. File titles are arranged as follows: Year_Area_Roll_Frame. The mosaic map displays Roll_Frame coordinates to correspond to these images. Contains TIF, OVR, JPG, AUX, IIQ, and XML files. Resource Title: 1938_AZY_5_113. File Name: 1938_AZY_5_113_2.zipResource Description: Contains IIQ, JPG, OVR, XML, AUX, and TIF files processed in ArcMap / ArcGIS.

Our Co-design team is from the University of Texas, working on a Department of Energy-funded project focused on the Beaumont-Port Arthur area. As part of this project, we will be developing climate-resilient design solutions for areas of the region. More on www.caee.utexas.edu. We captured aerial photos in the Port Arthur Coastal Neighborhood Community and the Golf Course on Pleasure Island, Texas, in June 2024. Aerial photos taken were through DroneDeploy autonomous flight, and models were processed through the DroneDeploy engine as well. All aerial photos are in .JPG format and contained in zipped files for each area. The processed data package includes 3D models, geospatial data, mappings, and point clouds. Please be aware that DTM, Elevation toolbox, Point cloud, and Orthomosaic use EPSG: 6588. And 3D Model uses EPSG: 3857. For using these data: - The Adobe Suite gives you great software to open .Tif files. - You can use LASUtility (Windows), ESRI ArcGIS Pro (Windows), or Blaze3D (Windows, Linux) to open a LAS file and view the data it contains. - Open an .OBJ file with a large number of free and commercial applications. Some examples include Microsoft 3D Builder, Apple Preview, Blender, and Autodesk. - You may use ArcGIS, Merkaartor, Blender (with the Google Earth Importer plug-in), Global Mapper, and Marble to open .KML files. - The .tfw world file is a text file used to georeference the GeoTIFF raster images, like the orthomosaic and the DSM. You need suitable software like ArcView to open a .TFW file. This dataset provides researchers with sufficient geometric data and the status quo of the land surface at the locations mentioned above. This dataset could streamline researchers' decision-making processes and enhance the design as well.

This dataset is a derivative of the Federal Township Plats for Lake County, Illinois, the originals of which were captured on a high-resolution scanner by the Illinois State Archives. The Lake County GIS/Mapping division received permission to acquire and georeference these images using ERDAS Imagine. Since the source material was distorted in an unsystematic way due to the rigors of time and points of reference were abundant, the rubber sheeting model in Imagine with the linear option was chosen to rectify the images. The USGS delineations of the section corners for their 1:24,000 scale 7.5 minute quadrangles were chosen as a base because they are a publicly available resource that exists for the entire state of Illinois should any other counties or organizations wish to make a similar product. This final product consists of a mosaic of the townships in Lake County also created in Imagine using their mosaic tool with each township being cropped to its border in the process.

Resolution: 1.0 Meter Bands: 3-band: G, R, NIR DelDOT Delivered as 172 Quarter-quads. Each tile is 137 MB (TIF). Scale: 1:12,000 SRS: NAD83 State Plane meters The State of Delaware contracted with PhotoScience Inc. to develop 1-meter resolution color-infrared digital ortho-photos for the entire state. PhotoScience Inc. became Earth Data International. For more detailed information about the source data, contact EarthData (http://www.earthdata.com). Airphotos were taken in March, 1992 at a 1:12000 scale, digitized and georeferenced to Delaware State Plane coordinates (meters, North American Datum 1983). Airphotos were taken in March, 1992, digitized and georeferenced to Delaware State Plane coordinates (meters, North American Datum 1983, based on GRS 1980 spheroid). The source data are 140 MB 24-bit color files for each of the 172 quarter-quads in Delaware. To facilitate dissemination of these data, the Spatial Analysis Lab resampled the 172 DOQ's covering the state to UTM coordinates (meters, NAD 1983) at 5-meter resolution in 8-bit color, achieving initial file size reductions of almost 99 percent. The Spatial Analysis Lab used a nearest-neighbor (i.e. center-cell selection) resampling procedure which generates a high-contrast image with some blockiness in very small features. Each transformation used four 3.75-minute-interval reference points located near the corners of each image. Each resampled image is approximately 1210 x 1510 pixels, with a 10-pixel (50-meter) border cropped out to eliminate slight edge skewness resulting from the reprojection. Images still have at least 500 meters of edge overlap. Color palettes were brightened and adjusted for improved consistency using Adobe Photoshop. Sun glare has been masked out of water pixels in most coastal images in order to correct color palettes. Cell resolution is exactly 5 x 5 meters. The original 1992 and 1997 series have differing degrees of positional error, and thus are not perfectly congruent. Earth Data used a larger set of ground control points to geo-reference the 1997 series, so these should have better positional accuracy. Most images were brightened and contrast-enhanced using Adobe Photoshop. To reduce file size and eliminate sun glare, large water areas are masked to black.

Abstract

The dataset was derived by the Geological and Bioregional Assessment Program. Georeferenced TIF image of the magentics of the Beetaloo Sub-basin and adjacent area. Total magnetic intensity (TMI) data measures variations in the intensity of the Earth magnetic field caused by the contrasting content of rock-forming minerals in the Earths crust. Magnetic anomalies can be either positive (field stronger than normal) or negative (field weaker) depending on the susceptibility of the rock. The 2015 Total magnetic Intensity (TMI) grid of Australia has a grid cell size of ~3 seconds of arc (approximately 80 m). This grid only includes airborne-derived TMI data for onshore and near offshore continental areas.

Attribution

Geological and Bioregional Assessments

History

This dataset is a clip of the Total Magnetic Intensity (TMI) Grid of Australia 2015 (sixth edition) for the area immediately surrounding the Beetaloo GBA region. The clip was carried out in ArcGIS software and saves in GEOTIFF format. For more information on the parent dataset please see http://pid.geoscience.gov.au/dataset/ga/89595 .

Abstract The dataset was derived by the Geological and Bioregional Assessment Program. Georeferenced TIF image of the magentics of the Beetaloo Sub-basin and adjacent area. Total magnetic intensity (TMI) data measures variations in the intensity of the Earth magnetic field caused by the contrasting content of rock-forming minerals in the Earths crust. Magnetic anomalies can be either positive (field stronger than normal) or negative (field weaker) depending on the susceptibility of the rock. The 2015 Total magnetic Intensity (TMI) grid of Australia has a grid cell size of ~3 seconds of arc (approximately 80 m). This grid only includes airborne-derived TMI data for onshore and near offshore continental areas. ## Attribution Geological and Bioregional Assessments ## History This dataset is a clip of the Total Magnetic Intensity (TMI) Grid of Australia 2015 (sixth edition) for the area immediately surrounding the Beetaloo GBA region. The clip was carried out in ArcGIS software and saves in GEOTIFF format. For more information on the parent dataset please see http://pid.geoscience.gov.au/dataset/ga/89595 .

Dataset description: This repository contains data pertaining to the manuscript "Mawrth Vallis, Mars, classified using the NOAH-H deep-learning terrain classification system." submitted to Journal of Maps. NOAH-H Mosaics: Mawrth_Vallis_NOAHH_Mosaic_DC_IG_25cm4bit_20230121_reclass.zip This folder contain mosaics of terrain classifications for Mawrth Vallis, Mars, made by the Novelty or Anomaly Hunter - HiRISE (NOAH-H) deep learning convolutional neural network developed for the European Space Agency (ESA) by SCISYS Ltd. In coordination with the Open University Planetary Environments Group. These folders contain the NOAH-H mosaics, as well as ancillary files needed to display the NOAH-H products in geographic information software (GIS). Included are two large raster datasets, containing the NOAH-H classification for the entire study area. One uses the 14 descriptive classes of the terrain, and the other with the five interpretative groups (Barrett et al., 2022). · Mawrth_Vallis_NOAHH_Mosaic_DC_25cm4bit_20230121_reclass.tif Contains the full 14 class “Descriptive Classes” (DC) dataset, reclassified so that pixel values reflect the original NOAH-H ontology, and not the priority rankings described in Wright et al., (2022) and Barrett et al., (2022b). It is accompanied by all auxiliary files required to view the data in GIS. · Mawrth_Vallis_NOAHH_Mosaic_IG_25cm4bit_20230121_reclass.tif Contains the 5 class “Interpretive Groups” (IG) dataset, reclassified so that pixel values reflect the original NOAH-H ontology, and not the priority rankings described in Wright et al., (2022) and Barrett et al., (2022b). It is accompanied by all auxiliary files required to view the data in GIS. Symbology layer files: NOAH-H_Symbology.zip This folder contains GIS layer file and colour map files for both the Descriptive Classes (DC) and interpretive Groups (IG) versions of the classification. These can be applied to the data using the symbology options in GIS. Georeferencing Control points: Mawrth_Vallis_Final_Control_Points.zip This file contains the control points used to georeferenced the 26 individual HiRISE images which make up the mosaic. These allow publicly available HiRISE images to be aligned to the terrain in Mawrth Vallis, and thus the NOAH-H Mosaic. Twenty-six 25 cm/pixel HiRISE images of Mawrth Vallis were used as input for NOAH-H. These are:

PSP_002140_2025_RED

PSP_002074_2025_RED

ESP_057351_2020_RED

ESP_053909_2025_RED

ESP_053698_2025_RED

ESP_052274_2025_RED

ESP_051931_2025_RED

ESP_051351_2025_RED

ESP_051219_2030_RED

ESP_050217_2025_RED

ESP_046960_2025_RED

ESP_046670_2025_RED

ESP_046525_2025_RED

ESP_046459_2025_RED

ESP_046314_2025_RED

ESP_045536_2025_RED

ESP_045114_2025_RED

ESP_044903_2025_RED

ESP_043782_2025_RED

ESP_043637_2025_RED

ESP_038758_2025_RED

ESP_037795_2025_RED

ESP_037294_2025_RED

ESP_036872_2025_RED

ESP_036582_2025_RED

ESP_035804_2025_RED NOAH-H produced corresponding 25 cm/pixel rasters where each pixel is assigned a terrain class based on the corresponding pixels in the input HiRISE image. To mosaic the NOAH-H rasters together, first the input HiRISE images were georeferenced to the HRSC basemap (HMC_11E10_co5) tile, using CTX images as an intermediate step. High order (spline, in ArcGIS Pro 3.0) transformations were used to make the HiRISE images georeference closely onto the target layers. Once the HiRISE images were georeferenced, the same control points and transformations were applied to the corresponding NOAH-H rasters. To mosaic the georeferenced NOAH-H rasters the pixel values for the classes needed to be changed so that more confidently identified, and more dangerous, classes made it into the mosaic (see dataset manuscript for details. To produce a HiRISE layer which fits the NOAH-H classification, download one of the listed HiRISE images from https://www.uahirise.org/, Select the corresponding control point file from this archive and apply a spline transformation through the GIS georeferencing toolbar. Manually Mapped Aeolian Bedforms: Mawrth_Manual_TARs.zip The manually mapped data was produced by Fawdon, independently of the NOAH-H project, as an assessment of “Aeolian Hazard” at Mawrth Vallis. This was done to inform the ExoMars landing site selection process. This file contains two GIS shape files, containing the manually mapped bedforms for both the entire mapping area, and the HiRISE image ESP_046459_2025_RED where the two datasets were compared on a pixel scale. The full manual map is offset slightly from the NOAH-H, since it was digitised from bespoke HiRISE orthomosaics, rather than from the publicly available HiRISE Red band images. It is suitable for comparison to the NOAH-H data with 100m-1km aggregation as in figure 8 of the associated paper. It is not suitable for pixel scale comparison. The map of ESP_046459_2025_RED was manually georeferenced to the NOAH-H mosaic, allowing for direct pixel to pixel comparisons, as presented in figure 6 of the associated paper. Two GIS shape files are included: · Mawrth_Manual_TARs_ESP_046459_2025.shp · Mawrth_Manual_TARs_all.shp Containing the high fidelity data for ESP_046459_2025, and the medium fidelity data for the entire area respectively. The are accompanied by ancillary files needed to view them in GIS. Gridded Density Statistics This dataset contains gridded density maps of Transverse Aeolian Ridges and Boulders, as classified by the Novelty or Anomaly Hunter – HiRISE (NOAH-H). The area covered is the runner up candidate ExoMars landing site in Mawrth Vallis, Mars. These are the data shown in figures; 7, 8, and S1. Files are presented for every classified ripple and boulder class, as well as for thematic groups. These are presented as .shp GIS shapefiles, along with all auxiliary files required to view them in GIS. Gridded Density stats are available in two zip folders, one for NOAH-H predicted density, and one for manually mapped density. NOAH-H Predicted Density: Mawrth_NOAHH_1km_Grid_TAR_Boulder_Density.zip Individual classes are found in the files: · Mawrth_NOAHH_1km_Grid_8TARs.shp · Mawrth_NOAHH_1km_Grid_9TARs.shp · Mawrth_NOAHH_1km_Grid_11TARs.shp · Mawrth_NOAHH_1km_Grid_12TARs.shp · Mawrth_NOAHH_1km_Grid_13TARs.shp · Mawrth_NOAHH_1km_Grid_Boulders.shp Where the text following Grid denotes the NOAH-H classes represented, and the landform classified. E.g. 8TARs = NOAH-H TAR class 8. The following thematic groups are also included: · Mawrth_NOAHH_1km_Grid_8_11continuousTARs.shp · Mawrth_NOAHH_1km_Grid_12_13discontinuousTARs · Mawrth_NOAHH_1km_Grid_8_10largeTARs.shp · Mawrth_NOAHH_1km_Grid_11_13smallTARs.shp · Mawrth_NOAHH_1km_Grid_8_13AllTARs.shp When the numbers denote the range of NOAH-H classes which were aggregated to produce the map, followed by a description of the thematic group: “continuous”, “discontinuous”, “large”, “small”, “all”. Manually Mapped Density Plots: Mawrth_Manual_1km_Grid.zip These GIS shapefiles have the same format as the NOAH-H classified ones. Three datasets are presented for all TARs (“_allTARs”), Continuous TARs (“_con”) and Discontinuous TARs (“_dis”) · Mawrth_Manual_1km_Grid_AllTARs.shp · Mawrth_Manual_1km_Grid_Con.shp · Mawrth_Manual_1km_Grid_Dis.shp Related public datasets: The HiRISE images discussed in this work are publicly available from https://www.uahirise.org/. and are credited to NASA/JPL/University of Arizona. HRSC images are credited to the European Space Agency; Mars Express mission team, German Aerospace Center (DLR), and the Freie Universität Berlin (FUB). They are available at the ESA Planetary Science Archive (PSA) https://www.cosmos.esa.int/web/psa/mars-express and are used under the Creative Commons CC BY-SA 3.0 IGO licence. SPATIAL DATA COORDINATE SYSTEM INFORMATION All NOAH-H files and derivative density plots have the same projected coordinate system: “Equirectangular Mars” - Projection: Plate Carree - Sphere radius: 3393833.2607584 m SOFTWARE INFORMATION All GIS workflows (georeferencing, mosaicking) were conducted in ArcGIS Pro 3.0. NOAH-H is a deep learning semantic segmentation software developed by SciSys Ltd for the European Space Agency to aid preparation for the ExoMars rover mission.

Our Co-design team is from the University of Texas, working on a Department of Energy-funded project focused on the Beaumont-Port Arthur area. As part of this project, we will be developing climate-resilient design solutions for areas of the region. More on www.caee.utexas.edu. We used a DJI Mavic 2 Pro to capture aerial photos in Beaumont-Port Arthur, TX, in February 2023, including: I. Beaumont Soccer Club II. Corps’ Port Arthur Resident Office III. Halbouty Pump Station comprises its vicinity IV. Lamar University (Including Exxon Power Plants close to Lamar Univ.) V. MLK Boulevard for aerial images of the industry and the ship channel VI. Salt Water Barrier (include some aerial images about the Big Thicket) Aerial photos taken were through DroneDeploy autonomous flight, and models were processed through the DroneDeploy engine as well. All aerial photos are in .JPG format and contained in zipped files for each location. The processed data package including 3D models, geospatial data, mappings, point clouds, and the animation video of Halbouty Pump Station has various file types: - The Adobe Suite gives you great software to open .Tif files. - You can use LASUtility (Windows), ESRI ArcGIS Pro (Windows), or Blaze3D (Windows, Linux) to open a LAS file and view the data it contains. - Open an .OBJ file with a large number of free and commercial applications. Some examples include Microsoft 3D Builder, Apple Preview, Blender, and Autodesk. - You may use ArcGIS, Merkaartor, Blender (with the Google Earth Importer plug-in), Global Mapper, and Marble to open .KML files. - The .tfw world file is a text file used to georeference the GeoTIFF raster images, like the orthomosaic and the DSM. You need suitable software like ArcView to open a .TFW file. This dataset provides researchers with sufficient geometric data and the status quo of the land surface at the locations mentioned above. This dataset could streamline researchers' decision-making processes and enhance the design as well. In October 2023, we had our follow-up data collection, including: I. Beaumont Soccer Club II. Shipping and Receiving Center at Lamar University After the aerial collection, we obtained aerial photos of those two locations mentioned above, as well as processed data (such as point clouds and models).

Digital aerial photography of the Springs Coast coastal waters flown by 3001 for benthic mapping purposes. Benthic GIS data were generated from these imagery. Note that seagrass exists beyond the Western extent of this collected imagery. Imagery were colleted in April 2007 using. A DMC digital camera was used at ~2900 ft with 120mm focal length. IMU and GPS data were collected in flight and used by 3001 to georeference the images.

The Southeast Texas Urban Integrated field lab’s Co-design team captured aerial photos in the Port Arthur Coastal Neighborhood Community and the Golf Course on Pleasure Island, Texas, in June 2024. Aerial photos taken were through autonomous flight, and models were processed through the DroneDeploy engine. All aerial photos are in .JPG format and contained in zipped files for each area. The processed data package includes 3D models, geospatial data, mappings, and point clouds. Please be aware that DTM, Elevation toolbox, Point Cloud, and Orthomosaic use EPSG: 6588. And 3D Model uses EPSG: 3857. For using these data: - The Adobe Suite gives you great software to open .Tif files. - You can use LASUtility (Windows), ESRI ArcGIS Pro (Windows), or Blaze3D (Windows, Linux) to open a LAS file and view the data it contains. - Open an .OBJ file with a large number of free and commercial applications. Some examples include Microsoft 3D Builder, Apple Preview, Blender, and Autodesk. - You may use ArcGIS, Merkaartor, Blender (with the Google Earth Importer plug-in), Global Mapper, and Marble to open .KML files. - The .tfw world file is a text file used to georeference the GeoTIFF raster images, like the orthomosaic and the DSM. You need suitable software like ArcView to open a .TFW file. This dataset provides researchers with sufficient geometric data and the status quo of the land surface at the locations mentioned above. This dataset will support researchers' decision-making processes under uncertainties.

The Yukon Digital Geology CD-ROMs present a variety of geoscience data sets in digital format on the geology of the Yukon Territory. They include syntheses of bedrock geology and glacial limits, compilations of geochronology, paleontology, mineral occurrences, oil and gas wells, and a compendium of aeromagnetic images. A subset of a public domain topographic data set (Digital Chart of the World, by ESRI, Inc.) is included for georeference purposes. For ease of use, data sets are divided geographically into 45 map tiles corresponding to the National Topographic System (NTS) 1:250,000 quadrangles. Data sets spanning the entire Yukon Territory are also included for use on sufficiently powerful computers and GIS software. Each theme for all of the 45 map tiles is presented in two projections. An Albers Equal Area projection, on disc 1, is provided to allow seamless integration of adjoining tiles throughout the Yukon. The complete data set is also provided on disc 2 in the UTM coordinate system, which is commonly used for accurately plotting data at the local scale (see Projections). Vector data files are also presented in several different file formats (ArcInfo coverages; Interchange (.e00), dBase (.dbf), shapefiles (.shp), and image data files are presented in band interleaved by line (.bil), and tagged image file format (*.tif) to allow easy importing of data into commercial GIS software. These CD-ROMs also include a limited edition of SurView, a viewing application for Microsoft Windows, developed at the Geological Survey of Canada and originally released as GSC Open File 2661. SurView runs directly off the CD-ROM. It can display, print, and query the *.shp and *.bil files. This provides an opportunity for those without specialized GIS software to delve into the realm of digital geoscience data and explore the Yukon Digital Geology databases on their own PC.

The Department of Information Technology and Telecommunications, GIS Unit, is providing the raw orthoimagery for download. This orthoimagery is used to create the Aerial Photography Tile Layer services described in further detail here: https://maps.nyc.gov/tiles/. Full metadata on the Aerial & Orthoimagery can be found at: https://github.com/CityOfNewYork/nyc-geo-metadata/blob/master/Metadata/Metadata_AerialImagery.md The 2014 Orthoimagery Tile Index can be used to geo-reference the individual image tiles across the City (https://data.cityofnewyork.us/City-Government/2014-Orthoimagery-Tile-Index/jxmq-5dde)

We were required to Georeference topographical maps which had been shared. I digitised a polygon shapefile within the mosaicked image. I used the polygon to clip the raster dataset in which I digitised line, polygon and point features within the clipped raster. The final product was a map of Meru which is shown. We added Kenya counties layer, Kenya schools layer, Kenya health layer and Kenya streets layer to Arcmap. I then clipped my respective county which is Laikipia County,in Kenya. I then clipped the added layers to fit my county so that I could process the required data. I buffered health layer so that it could help me know which schools were within 120 m from the health facilities. Also, i buffered steets to 55m from the schools to know which were closest and their accessibility. This data was to be used by the Ministry of Health to plan for polio vaccination in the county. The finished product was a map as shown below.

Image Service | OGC WCS | OGC WMS | KMZ | Tile DownloadContains high resolution color CITIPIX Ortho-rectified Digital Images (ODIs) from GLOBEXPLORER. These digital images result from ortho-rectification and mosaicking of scanned color aerial photographs. Each pixel represents a planimetric square 1/2 foot on a side on the ground. Digital file features include high quality ground-level georeferencing, derived from accurate positioning and geometric corrections, and provide a digital photographic map suitable for applications requiring a 1:1200 National Map Accuracy Standard (NMAS). Based on the CITIPIX nation-wide standard for urban aerial coverage, georeference and distribution, CITIPIX ODIs serve the GIS industry, state and local governments as well as private sector, supplying 6-inch (15-cm) ground pixel size map-accurate continuous digital photographic coverage.

This feature layer is part of SDGs Today. Please see sdgstoday.orgGlobally, an estimated 58% of students will not reach minimum proficiency levels (MPL) in reading and mathematics by the time they finish primary school. For Sub-Saharan Africa, 88% percent of students will not reach those same MPLs. SDG 4 aims to ensure inclusive and equitable quality education for all, but access remains a major challenge. While enrollment rates continue to increase, other quality barriers remain for many students and learners. Physical distance to educational facilities is one such barrier.Using open-source georeferenced data and satellite data products, we construct travel-time isochrones from school locations and overlay subnational population counts to construct a dataset of age-specific population counts within travel-time catchment areas in Africa. The resulting walk-time data can help support gaps in existing education data and highlight open-source methods. Our School location data is derived from OpenStreetMap, a powerful open-source data repository of georeferenced buildings, roads, amenities, and other physical features. While OpenStreetMap is vast, data quality varies by region and many schools remain missing across the globe. Please review the methodological note where we discuss the implications of missing data. Finally, population data is derived from WorldPop constrained Sex/Age demographic population images.Additional school locations are georeferenced using ArcGIS 123 Survey data collected as a part of My School Today!, an SDGs Today call to action that encourages participants to georeference school buildings in Africa with OpenStreetMap.For more information, contact SDGs Today at sdgstoday@unsdsn.org.