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...
- 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/
