Por favor, use este identificador para citar o enlazar este ítem:
https://repositorio.uti.edu.ec//handle/123456789/3415
Registro completo de metadatos
Campo DC | Valor | Lengua/Idioma |
---|---|---|
dc.contributor.author | Bonilla-Bedoya, Santiago | - |
dc.contributor.author | Mora, Argenis | - |
dc.contributor.author | Vaca, Angélica | - |
dc.contributor.author | Estrella, Anabel | - |
dc.contributor.author | Herrera, Miguel-Angel | - |
dc.date.accessioned | 2022-06-29T22:17:47Z | - |
dc.date.available | 2022-06-29T22:17:47Z | - |
dc.date.issued | 2020 | - |
dc.identifier.uri | https://www.sciencedirect.com/science/article/pii/S0198971519303898 | - |
dc.identifier.uri | http://repositorio.uti.edu.ec//handle/123456789/3415 | - |
dc.description.abstract | The rapid process of global urbanisation engenders changes in urban socio-ecological systems and in the landscape structure. However, the future processes of urban expansion in Latin American cities has been little studied even though the wellbeing of its citizens will depend on territorial management and on planning the provision of ecosystemic benefits and services. This research, considering different socio-ecological dimensions, proposed to determine the causes of potential urban expansion, analysing the dimensions and possible predictors that would explain the expansion of a high Andean city and its influence on peri-urban forest landscapes. To develop a model that integrates the complexity of the system, we used the following five dimensions: biophysics, land cover and management, infrastructure and services, socio-economics, and landscape metrics, and we opted for a binomial analysis through a spatial logistic regression model developed from 33 predictors. Considering the odd radio of the model, we observe that the independent increase in predictors, including building blocks, drinking water, sewerage, waste collection, average land size, the Interspersion and Juxtaposition Index (IJI) and Largest Patch Index (LPI), and the constant behaviour of the others predictors, would increase the probability of a potential urbanisation of the territory. Similarly, the independent increase in predictors, including the presence of protected areas, the presence of protected forests, land cover, unemployment, and the Shannon Diversity Index(SHDI), reduce the probability of the urbanisation process. Our results suggest that the territorial vulnerability from a potential urbanisation process is strongly related to an increase in infrastructure, services, and the average size of properties variables. Moreover, the landscape with the greatest potential for urbanisation presents an adequate intercalation of the different patches that compose it. However, the presence of variables such as protected areas and protective forests, in addition to monitoring indicators such as landscape diversity and mitigation strategies, could be considered to focus the analysis on the current dynamics of urbanisation processes in Latin America. © 2019 Elsevier Ltd | es |
dc.language.iso | eng | es |
dc.publisher | Computers, Environment and Urban Systems. Volume 79 | es |
dc.rights | openAccess | es |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | es |
dc.title | Modelling the relationship between urban expansion processes and urban forest characteristics: An application to the Metropolitan District of Quito | es |
dc.type | article | es |
Aparece en las colecciones: | Artículos Científicos Indexados |
Ficheros en este ítem:
No hay ficheros asociados a este ítem.
Este ítem está sujeto a una licencia Creative Commons Licencia Creative Commons