Predicting multidimensional poverty with machine learning algorithms : an open data source approach using spatial data

ABSTRACT: This paper presents a methodology to estimate the multidimensional poverty index using spatial data at the street block level. The data used in this study were obtained from Open Street Maps and ESA’s land use cover, which are freely available sources of spatial information. The study empl...

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Autores:
Muñetón Santa, Guberney
Manrique Ruiz, Luis Carlos
Tipo de recurso:
Article of investigation
Fecha de publicación:
2023
Institución:
Universidad de Antioquia
Repositorio:
Repositorio UdeA
Idioma:
eng
OAI Identifier:
oai:bibliotecadigital.udea.edu.co:10495/34949
Acceso en línea:
https://hdl.handle.net/10495/34949
Palabra clave:
Multidimensional poverty index
Spatial analysis
Poverty
Machine learning
Indice de pobreza multidimensional
Pobreza
Análisis espacial
Medellín, Colombia
Rights
openAccess
License
https://creativecommons.org/licenses/by/4.0/