Distribución de las islas de calor urbano superficial en relación con los niveles socioeconómicos de la población de la ciudad de Medellín, para el año 2022
This study addresses the distribution of Surface Urban Heat Islands (SUHI) in relation to the socioeconomic levels of the population in Medellín, highlighting the socioenvironmental implications of the phenomenon. The main objective was to determine the distribution of Surface Urban Heat Islands (SU...
- Autores:
-
Álvarez López, Durley Johana
Zapata Henao, Ana Sofía
- Tipo de recurso:
- Trabajo de grado de pregrado
- Fecha de publicación:
- 2025
- Institución:
- Universidad de Antioquia
- Repositorio:
- Repositorio UdeA
- Idioma:
- spa
- OAI Identifier:
- oai:bibliotecadigital.udea.edu.co:10495/46263
- Acceso en línea:
- https://hdl.handle.net/10495/46263
- Palabra clave:
- Factores Socioeconómicos
Socioeconomic Factors
Clase Social
Social Class
Pobreza
Poverty
Diseño urbano
Urban design
Cambio climático
Climate change
Ola de calor
Heatwaves
Isla de calor urbana superficial, desigualdad, distribución,
http://aims.fao.org/aos/agrovoc/c_1666
http://aims.fao.org/aos/agrovoc/c_c728b4f8
http://vocabularies.unesco.org/thesaurus/concept6161
https://id.nlm.nih.gov/mesh/D012959
https://id.nlm.nih.gov/mesh/D012923
https://id.nlm.nih.gov/mesh/D011203
ODS 16: Paz, justicia e instituciones sólidas. Promover sociedades pacíficas e inclusivas para el desarrollo sostenible, facilitar el acceso a la justicia para todos y construir a todos los niveles instituciones eficaces e inclusivas que rindan cuentas
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-sa/4.0/
| Summary: | This study addresses the distribution of Surface Urban Heat Islands (SUHI) in relation to the socioeconomic levels of the population in Medellín, highlighting the socioenvironmental implications of the phenomenon. The main objective was to determine the distribution of Surface Urban Heat Islands (SUHI) in relation to the socioeconomic levels of Medellín's population in 2022. A cross-sectional descriptive study with an ecological approach was conducted, based on secondary data. Variables such as the Multidimensional Poverty Index (MPI), NDVI, NDBI, population density, road area, and elevation were considered for univariate, bivariate, and multivariate analysis. The results showed a high spatial autocorrelation between MPI and SUHI, indicating that the distribution is not random. A moderate negative correlation was found, suggesting that areas with lower poverty levels exhibit higher SUHI intensities. However, exceptions were identified, demonstrating the influence of other factors. This study is one of the first to analyze the relationship between SUHI and MPI in Medellín. It highlights the importance of examining these dynamics at more detailed scales and incorporating variables such as land use, local meteorological data, and others for a more precise understanding. This would allow for better identification of local factors influencing the spatial variability of SUHI and the design of specific interventions to mitigate its effects in particularly vulnerable areas. |
|---|
