7ee7bd55-23fb-456b-841b-450f4ea56486 The Malaria Atlas Project malariaatlas@telethonkids.org.au https://malariaatlas.org/ WWW:LINK-1.0-http--link mundialis GmbH & Co. KG info@mundialis.de 2021-10-25T12:27:22 ISO 19115:2003/19139 1.0 3 1 30 1 30 1 1 WGS 1984 Accessibility to Cities 2015 2018-06-01 dataset This global accessibility map enumerates land-based travel time to the nearest densely-populated area for all areas between 85 degrees north and 60 degrees south for a nominal year 2015. Densely-populated areas are defined as contiguous areas with 1,500 or more inhabitants per square kilometer or a majority of built-up land cover types coincident with a population centre of at least 50,000 inhabitants. This map was produced through a collaboration between the University of Oxford Malaria Atlas Project (MAP), Google, the European Union Joint Research Centre (JRC), and the University of Twente, Netherlands. The underlying datasets used to produce the map, include roads (comprising the first ever global-scale use of Open Street Map and Google roads datasets), railways, rivers, lakes, oceans, topographic conditions (slope and elevation), landcover types, and national borders. These datasets were each allocated a speed or speeds of travel in terms of time to cross each pixel of that type. The datasets were then combined to produce a “friction surface”, a map where every pixel is allocated a nominal overall speed of travel based on the types occurring within that pixel. Least-cost-path algorithms (running in Google Earth Engine and, for high-latitude areas, in R) were used in conjunction with this friction surface to calculate the time of travel from all locations to the nearest city (by travel time). Cities were determined using the high-density-cover product created by the Global Human Settlement Project. Each pixel in the resultant accessibility map thus represents the modeled shortest time from that location to a city. Full Citation D.J. Weiss, A. Nelson, H.S. Gibson, W. Temperley, S. Peedell, A. Lieber, M. Hancher, E. Poyart, S. Belchior, N. Fullman, B. Mappin, U. Dalrymple, J. Rozier, T.C.D. Lucas, R.E. Howes, L.S. Tusting, S.Y. Kang, E. Cameron, D. Bisanzio, K.E. Battle, S. Bhatt, and P.W. Gething. A global map of travel time to cities to assess inequalities in accessibility in 2015. (2018). Nature. doi:10.1038/nature25181. The Malaria Atlas Project malariaatlas@telethonkids.org.au https://malariaatlas.org/ WWW:LINK-1.0-http--link https://data.mundialis.de:/geonetwork/srv/api/records/7ee7bd55-23fb-456b-841b-450f4ea56486/attachments/accessibility_to_cities.png Travel time World MOOD-H2020 Transport networks Human health and safety GEMET - INSPIRE themes, version 1.0 2008-06-01 geonetwork.thesaurus.external.theme.httpinspireeceuropaeutheme-theme None no limitations to public access Creative Commons Attribution 4.0 International License (CC BY 4.0) | Creative Commons Namensnennung - 4.0 International (CC BY 4.0) { "id": "cc-by/4.0", "name": "Creative Commons Attribution 4.0 International License", "url": "http://creativecommons.org/licenses/by/4.0/", "quelle": "Source: The Malaria Atlas Project" } 1000 geoscientificInformation transportation World 2015-01-01 2015-12-31 -180.00 180.00 -90.00 90.00 GeoTIFF 1.0 https://malariaatlas.org/research-project/accessibility-to-cities/ WWW:LINK-1.0-http--download Accessibility to Cities 2015 COMMISSION REGULATION (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services 2010-12-08 http://data.europa.eu/eli/reg/2010/1089/2014-12-31 See specified reference true derived from Open Street Map data and Google roads database