![]() Though, the reliability of these datasets heavily depends on their ability to replicate the observed temporal variability and distribution patterns. ![]() ![]() Gauge-based gridded precipitation datasets provide an opportunity to assess the climate where stations are sparsely located. Modelled gridded population estimates for the Haut-Katanga, Haut-Lomami, Ituri, Kasaï, Kasaï Oriental, Lomami and Sud-Kivu provinces in the Democratic Republic of the Congo (2021), version 3.0.The rough topography, harsh climate, and sparse monitoring stations have limited hydro-climatological studies in arid regions of Pakistan. École de Santé Publique de Kinshasa, Bureau Central du Recensement and Institut National de la WorldPop, University of Southampton, Flowminder Foundation, Republic of the Congo (2021), version 3.0. Modelled gridded population estimates for the HautKatanga, Haut-Lomami, Ituri, Kasaï, Kasaï-Oriental, Lomami and Sud-Kivu provinces in the Democratic G Boo, R Hosner, PZ Akilimali, E Darin, HR Chamberlain, WC Jochem, P Jones, R Shulungu Runika, HM ![]() TheĪuthors acknowledge the support of their respective institutions in the completion of this work. (Bureau Central du Recensement), Attila N Lazar (WorldPop) and Andrew J Tatem (WorldPop). (WorldPop), Roger Shulungu Runika (Institut National de la Statistique), Henri Marie Kazadi Mutombo (WorldPop), Heather R Chamberlain (WorldPop), Warren C Jochem (WorldPop), Patricia Jones (Flowminder Foundation), Pierre Z Akilimali (École de Santé Publique de Kinshasa), Edith Darin The production of these data was led by Gianluca Boo (WorldPop]( ) ) with support from Roland Hosner The study was approved by theįaculty Ethics Committee of the University of Southampton (ERGO II 62716). Programme funded by the Bill and Melinda Gates Foundation (BMGF) and the United Kingdom’s Foreign,Ĭommonwealth & Development Office (INV 009579, formerly OPP 1182425). Was a continuation of the GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development) Kinshasa and both the Bureau Central du Recensement and the Institut National de la Statistique. University of Southampton and national partners including, but not limited to, the École de Santé Publique de Network ( CIESIN) at Columbia University, in collaboration with the WorldPop Research Group at the The project was led by the Flowminder Foundation and the Center for International Earth Science Information Health, Hygiene and Prevention of the DRC and funded by Gavi, the Vaccine Alliance (RM 867204 20A2). This project was delivered under the leadership of the Ministry of Public These data were produced by the WorldPop Research Group at the University of Southampton as part of the Imagery used for automatic delineation was outdated. May be impacted by the accuracy of the building footprints, particularly in the areas where the satellite The modelled population estimates represent the period of the microcensus but their consistency Other essential input data include metrics derived from building footprints, which were automaticallyĭelineated by Ecopia.AI in 2021 using satellite imagery collected by Maxar Technologies between 2010Īnd 2021. École de Santé Publique de Kinshasa, the WorldPop Research Group at the University of SouthamptonĪnd the Bureau Central du Recensement, which is part of the Institut National de la Statistique of the DRC. ![]() The microcensus was led by the Flowminder Foundation, the Provinces throughout March and April 2021. The main input data were derived from a dedicated microcensus survey carried out in the targeted Population counts created using a Bayesian statistical model and post-hoc breakdowns in 40 age and sex Sud-Kivu provinces in the Democratic Republic of the Congo (DRC). These data consist of modelled gridded population estimates produced at a spatial resolution ofĪpproximately 100m across the Haut-Katanga, Haut-Lomami, Ituri, Kasaï, Kasaï-Oriental, Lomami and ![]()
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