ARTÍCULO
TITULO

Generating and Mapping Amazonian Urban Regions Using a Geospatial Approach

Pablo F. Cabrera-Barona    
Manuel Bayón    
Gustavo Durán    
Alejandra Bonilla and Verónica Mejía    

Resumen

(1) background: Urban representations of the Amazon are urgently needed in order to better understand the complexity of urban processes in this area of the World. So far, limited work that represents Amazonian urban regions has been carried out. (2) methods: Our study area is the Ecuadorian Amazon. We performed a K-means algorithm using six urban indicators: Urban fractal dimension, number of paved streets, urban radiant intensity (luminosity), and distances to the closest new deforested areas, to oil pollution sources, and to mining pollution sources. We also carried out fieldwork to qualitatively validate our geospatial and statistical analyses. (3) results: We generated six Amazonian urban regions representing different urban configurations and processes of major cities, small cities, and emerging urban zones. The Amazonian urban regions generated represent the urban systems of the Ecuadorian Amazon at a general scale, and correspond to the urban realities at a local scale. (4) conclusions: An Amazonian urban region is understood as a set of urban zones that are dispersed and share common urban characteristics such a similar distance to oil pollution sources or similar urban radiant intensity. Our regionalization model represents the complexity of the Amazonian urban systems, and the applied methodology could be transferred to other Amazonian countries.

Palabras claves

 Artículos similares

       
 
Chao Jiang, Lin Liu, Xiaoxing Qin, Suhong Zhou and Kai Liu    
The importance of combining spatial and temporal aspects has been increasingly recognized over recent years, yet pertinent pattern analysis methods in place-based crime research still need further development to explicitly indicate spatial-temporal local... ver más

 
Raffaele Albano, Caterina Samela, Iulia Craciun, Salvatore Manfreda, Jan Adamowski, Aurelia Sole, Åke Sivertun and Alexandru Ozunu    
Large-scale flood risk assessment is essential in supporting national and global policies, emergency operations and land-use management. The present study proposes a cost-efficient method for the large-scale mapping of direct economic flood damage in dat... ver más
Revista: Water

 
Azelle Courtial, Achraf El Ayedi, Guillaume Touya and Xiang Zhang    
Among cartographic generalisation problems, the generalisation of sinuous bends in mountain roads has always been a popular one due to its difficulty. Recent research showed the potential of deep learning techniques to overcome some remaining research pr... ver más

 
Benjamin Ulmer, John Hall and Faramarz Samavati    
Geospatial sensors are generating increasing amounts of three-dimensional (3D) data. While Discrete Global Grid Systems (DGGS) are a useful tool for integrating geospatial data, they provide no native support for 3D data. Several different 3D global grid... ver más

 
Yunfei Zhang, Zexu Zhang, Jincai Huang, Tingting She, Min Deng, Hongchao Fan, Peng Xu and Xingshen Deng    
With the rapid development of urban traffic, accurate and up-to-date road maps are in crucial demand for daily human life and urban traffic control. Recently, with the emergence of crowdsourced mapping, a surge in academic attention has been paid to gene... ver más