7 research outputs found
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Mapping and Classifying Settlement Locations
“Mapping and Classifying Settlement Locations” discusses GRID3’s work on collecting and analyzing settlements data. GRID3’s settlements work has two areas of focus: creating a comprehensive settlement layer that enables a real-world picture of communities, and using building footprints, geospatial data layers, and machine learning algorithms to classify structures and local areas within settlements. The paper also discusses the applications of GRID3’s methods in Nigeria, the Democratic Republic of the Congo, and Zambia.
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: area-level classification; building footprints; comprehensive settlement layer; extent; intra-settlement categorisation; machine learning; polygon layer; point layer; settlement; settlement data; settlement layer; settlement mapping; settlement point; ; GRID3; database schema; geospatial data; neighbourhood classification; open-source; health zones; participatory cartography; GIS; vaccination; immunisation; census; micro-plans; CIESIN; UNFPA; Flowminder; WorldPop; probability model; areal; built-up areas; small settlements; hamlets; hamlet areas; polio; Afric
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Cartographie et classification des localités
Ce document présente le travail de GRID3 sur le recueil et l'analyse des données de localité. Les activités de GRID3 sur les localités se s’articule autour de deux axes principaux : la création d'une couche des localités exhaustive qui permet d'obtenir une image réelle des communautés, et l'utilisation d'empreintes de bâtiments, de couches de données géospatiales et d'algorithmes d'apprentissage automatique pour classer les structures et les zones locales au sein des localités. Ce document aborde également les applications des méthodes de GRID3 au Nigeria, en République démocratique du Congo et en Zambie.
GRID3 accompagne les pays dans la création, la validation et l'utilisation des données géospatiales de population, localités, infrastructures et de limites infranationales. Pour plus d'informations, voir https://grid3.org/.
Keywords (Mots clés) : classification au niveau de la zone ; empreintes de bâtiments ; couche de localités complète ; étendue ; catégorisation intra localité ; apprentissage automatique ; couche de polygones ; couche de points ; localités ; données de localités ; couche de localités ; cartographie de localités ; point de localités ; GRID3 ; schéma de base de données ; données géospatiales ; classification des quartiers ; source ouverte ; zones de santé ; cartographie participative ; SIG ; vaccination ; immunisation ; recensement ; micro-plans ; CIESIN ; UNFPA ; Flowminder ; WorldPop ; modèle de probabilité ; aréal ; zones bâties ; petites agglomérations ; hameaux ; zones de hameaux ; polio ; Afriqu
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Mapping Health Facilities
“Mapping Health Facilities” discusses GRID3’s work with local stakeholders and data collectors to build capacity for the production and management of geospatial data on health facilities. This paper first discusses GRID3's approach to mapping health facility data. In the next section, it discusses GRID3's support of routine and non-routine immunisation campaigns in Nigeria and the consolidation of existing health facilities data and collection of new data in the Democratic Republic of the Congo. Following that, new GRID3 initiatives are discussed, including data consolidation and collection in Zambia and work around health facilities data in Sierra Leone. For more information, see https://grid3.org/
Keywords: COVID-19; health facilities; community health workers; GIS; GTS; health catchment; microplan; microplanning; points of interest; sustainable development; Democratic Republic of the Congo; Nigeria; Sierra Leone; Zambia; GRID3; health zones; vaccination; immunisation; CIESIN; UNFPA; Flowminder; WorldPop; polio; Africa; Bill & Melinda Gates Foundation; District Health Information Software 2; Directorate of Planning, Policy, and Information; Division of the National Health Information System; Expanded Program on Immunization; Geographic Information System; Geospatial Tracking System; Local Government Area; Mapping For Health; Maternal and Child Survival Program; National Primary Health Care Development Agency; National Spatial Data Infrastructure; Open Data Kit; Public Health Services and Solutions; Quality analysis and quality control; routine immunisation; non-routine immunisation; Service Availability and Readiness Assessment; United States Agency for International Development; Vaccination Tracking System; Wild Polio Virus; Zambia Statistics Agenc
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Harmonising Subnational Boundaries
“Harmonising Subnational Boundaries” discusses GRID3’s work to support the harmonisation, production, and use of digitised legal/administrative units, operational units, and statistical areas. GRID3’s boundaries work has three primary areas of focus: improving and harmonising operational units; fostering improved collaboration on boundary harmonisation among disparate government bodies; and using boundaries harmonisation to support census efforts. The paper focuses on case studies in Nigeria, the Democratic Republic of the Congo, and Zambia.
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: administrative units; census; community health workers; digital boundaries; emergency operations; enumeration area; GIS; gridded population data; harmonisation; health catchment; microplan; operational units; points of interest; pre-enumeration area; routine operations; semi-automated delineation; settlement; settlement layer; settlement mapping; statistical areas; statistical infrastructure; subnational boundaries; sustainable development; GRID3; health zones; participatory mapping; vaccination; immunisation; CIESIN; UNFPA; Flowminder; WorldPop; poli
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Harmoniser les limites infranationales
“Harmoniser les limites infranationales” aborde le travail de GRID3 de soutien à l'harmonisation, la production et l'utilisation d'unités légales/administratives, d'unités opérationnelles et de zones statistiques numérisées. Le travail de GRID3 sur les frontières s'articule autour de trois axes principaux: l'amélioration et l'harmonisation des unités opérationnelles, la promotion d'une meilleure collaboration sur l'harmonisation des limites entre des organismes gouvernementaux disparates et l'utilisation de l'harmonisation des limites pour soutenir les efforts de recensement. Le document se penche sur des études réalisées au Nigeria, en République démocratique du Congo et en Zambie.
GRID3 accompagne les pays dans la création, la validation et l'utilisation des données géospatiales de population, localités, infrastructures et de limites infranationales. Pour plus d'informations, voir https://grid3.org/.
Keywords (Mots clés) : unités administratives ; recensement ; agents de santé communautaires ; limites numériques ; opérations d'urgence ; zone de dénombrement ; SIG ; données de population carroyées ; harmonisation ; bassin de santé ; microplan ; unités opérationnelles ; points d'intérêt ; zone de pré-dénombrement ; opérations de routine ; délimitation semi-automatique ; établissement ; couche d'établissement ; cartographie de l'établissement ; zones statistiques ; infrastructure statistique ; limites infranationales ; développement durable ; GRID3 ; zones de santé ; cartographie participative ; vaccination ; immunisation ; CIESIN ; UNFPA ; Flowminder ; WorldPop ; polio
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Generating and Evaluating Digitised Census Enumeration Areas
“Generating and Evaluating Digitised Census Enumeration Areas” discusses GRID3's support of countries’ efforts to create and/or strengthen their EA boundaries. The paper discusses GRID3's two main areas of focus in GRID3’s work in the field of EA demarcation: 1) Creating and/or updating “pre-EA” boundaries using a semi-automated delineation approach, with a case study in the Democratic Republic of the Congo, and 2) Providing GIS training and technical assistance to assess the potential difficulty of visiting EAs, so as to reduce the count of persons “missed” by census enumerators, with a case study in Ghana. The paper also discusses EA support currently underway in Zambia. For more information, see https://grid3.org/.
Keywords: Census; cartography; sustainable development; Democratic Republic of the Congo; Ghana; Zambia; GRID3; CIESIN; UNFPA; Flowminder; WorldPop; Africa; Bill & Melinda Gates Foundation; enumeration areas; pre-enumeration areas; Hard to Count tool; GIS; 2nd National Population and Housing Census; Ghana Statistical Service; Zambia Statistics Agency; Sustainable Development Goals; Columbia University; data; geospatial; GPS; semi-automated; national statistical office; building footprints